阅读说明：本技术 可配置的烹饪系统和方法 (Configurable cooking system and method ) 是由 S-Y·成 M·让诺夫 R·梅茨勒 J·普莱曾特 D·岳 T·艾德姆斯 D·丹克尔 于 2018-08-11 设计创作，主要内容包括：本发明提供了用于用户可配置的烹饪器具的系统和方法,包括：接收具有相关联的预算的系统资源；促进用户将所述系统资源分配给多个加热元件而不超出所述相关联的预算；将所述系统资源应用于所述加热元件以加热烹饪腔室内的一种或多种食品物质,并且选择行地调节所述系统资源向所述加热元件的递送,使得被递送至所述加热元件的系统资源不超出每个所述系统资源的所述相关联的预算。计算部件能够执行加热算法,以在所述烹饪腔室内烹饪至少一种食品物质,检测所述食品物质的状态变化,以及修改所述加热算法,以及响应于所述状态变化并且根据所述系统资源的用户配置的分配和相关联的预算来重新配置供应给所述加热元件的所述系统资源。(The present invention provides systems and methods for a user-configurable cooking appliance, comprising: receiving a system resource having an associated budget; facilitating a user to allocate the system resources to a plurality of heating elements without exceeding the associated budget; applying the system resource to the heating element to heat one or more food substances within a cooking chamber, and selectively adjusting delivery of the system resource to the heating element in rows such that the system resource delivered to the heating element does not exceed the associated budget for each of the system resources. The computing component is capable of executing a heating algorithm to cook at least one food product substance within the cooking chamber, detect a change in state of the food product substance, and modify the heating algorithm, and reconfigure the system resources supplied to the heating elements in response to the change in state and in accordance with a user-configured allocation and associated budget of the system resources.)

1. A cooking appliance comprising:

a cooking chamber;

a plurality of heating elements operable to heat one or more food substances within the cooking chamber;

an input operable to receive one or more system resources for the plurality of heating elements, each system resource having an associated budget;

a control component operable to selectively regulate delivery of the one or more system resources to one or more of the heating elements;

a user interface operable to allocate one or more of the system resources to the plurality of heating elements within the budget associated with each allocated system resource; and

a computing component comprising logic to ensure that a budget delivered by the control component to the plurality of heating elements does not exceed the associated budget for each of the one or more system resources.

2. The cooking appliance of claim 1, wherein one of the one or more system resources is power, current, or energy.

3. The cooking appliance of claim 2, wherein one or more system resources comprise power and the control component comprises a power control component; and wherein the power control component is operable to receive electrical power from an external source and distribute the received electrical power among the plurality of heating elements to implement a heating algorithm, the power control component including power control logic to track power usage of each of the heating elements and select one of the plurality of heating elements to activate.

4. The cooking appliance of claim 2, wherein the one or more system resources include power, the control component is a power control component; and wherein the power control component is operable to adjust the received power in accordance with a system power constraint indicated by the associated budget for the resource.

5. The cooking appliance of claim 1, wherein the cooking chamber comprises a plurality of cooking zones; and wherein the heating element is selectively operable to heat one or more food substances within each of the plurality of cooking zones.

6. The cooking appliance of claim 5, wherein a heating algorithm is operable to allocate the associated budget of one or more system resources across a plurality of heating elements to selectively heat one or more food substances within each of a plurality of cooking zones without exceeding the associated budget.

7. The cooking appliance of claim 1, wherein the user interface provides an indication of the associated budget for one or more system resources to the user.

8. The cooking appliance of claim 7, wherein indicating to the user the associated budget for one or more system resources comprises an indication of remaining system resource budget and/or an indication of current system usage during operation of one or more heating elements.

9. The cooking appliance of claim 1, wherein the user interface does not provide the user with an indication of the associated budget for one or more system resources.

10. The cooking appliance of claim 7, wherein the computing component is operable to project recipe results based on a user-configured allocation of system resources to the plurality of heating elements; and wherein indicating to the user the associated budget for one or more system resources comprises an indication of an impact of the user-configured allocation of the system resources on the recipe results.

11. The cooking appliance of claim 10, wherein the computing component is further operable to adjust a heating algorithm according to expected recipe results and/or budget system resource status, and wherein the indication to the user includes an adjusted cooking time and/or other recipe adjustments.

12. The cooking appliance of claim 11, wherein the computing component is further operable to facilitate user-configured allocation of system resources to the plurality of heating elements to heat a plurality of zones within a multi-zone cooking chamber.

13. The cooking appliance of claim 1, wherein the interface facilitates user control of the heating element and associated system resource depletion.

14. The cooking appliance of claim 1, wherein the control component comprises logic and circuitry to facilitate automatic allocation of one or more system resources to the plurality of heating elements according to associated budgets and/or user settings of one or more system resource budgets.

15. The cooking appliance of claim 1, wherein the heating element comprises a quartz tungsten halogen heater.

16. The cooking appliance of claim 1, wherein the computing component is further operable to execute a heating algorithm to cook at least one food substance in the cooking chamber, detect a change in state of the at least one food substance, and modify the heating algorithm to reconfigure the system resources supplied to one or more heating elements in response to the change in state and in accordance with a system resource budget.

17. A method, comprising:

receiving one or more system resources, each of the one or more system resources having an associated budget;

facilitating, via a user interface, a user to allocate one or more system resources to a plurality of heating elements without exceeding any associated budgets for the one or more system resources;

applying the one or more system resources to the plurality of heating elements to heat one or more food substances within the cooking chamber; and

selectively adjusting delivery of the one or more system resources to one or more heating elements such that the associated budget for each of the one or more system resources is not exceeded for delivery to the plurality of heating elements.

18. The method of claim 17, wherein one of the one or more system resources is power, current, or energy.

19. The method of claim 18, wherein one of the one or more system resources is power; wherein applying the one or more system resources to a plurality of heating elements comprises operating a power control component to receive electrical power from an external resource and distributing the received electrical power among the plurality of heating elements to implement a heating algorithm; and wherein the power control component comprises power control logic to track power usage of each of the heating elements and select one of the plurality of heating elements to activate.

20. The method of claim 18, wherein one of the one or more system resources is power; and wherein applying the one or more system resources to the plurality of heating elements comprises operating a power control component to regulate the received electrical power in accordance with a system power constraint indicated by the associated budget.

21. The method of claim 17, wherein the cooking chamber comprises a plurality of cooking zones; and wherein the heating element is selectively operable to heat one or more food substances within each of the plurality of cooking zones.

22. The method of claim 21, wherein heating algorithm is operable to allocate the associated budget of one or more system resources across a plurality of heating elements to selectively heat one or more food substances within each of a plurality of cooking zones without exceeding the budget.

23. The method of claim 17, wherein the user interface provides an indication of the associated budget for one or more system resources to the user.

24. The method of claim 23, wherein indicating to the user the associated budget provided to the one or more system resources for use comprises an indication of remaining system resource budget and/or an indication of current system usage during operation of one or more heating elements.

25. The method of claim 17, wherein the user interface does not provide the user with an indication of the associated budget for one or more system resources.

26. The method of claim 17, wherein the computing component is operable to project recipe results based on a user-configured allocation of budget system resources to the plurality of heating elements; and wherein the indication of the associated budget for one or more system resources comprises an indication of an impact of a user-configured allocation of the system resources on the recipe results.

27. The method of claim 26, wherein the computing component is further operable to adjust a heating algorithm according to projected recipe results and/or budget system resource status, and wherein the indication comprises an adjusted cooking time and/or other recipe adjustments.

28. The method of claim 27, wherein the computing component is further operable to facilitate user-configured allocation of system resources to the plurality of heating elements to heat a plurality of zones within a multi-zone cooking chamber.

29. The method of claim 17, wherein the interface facilitates user control of the heating element and associated system resource depletion.

30. The method of claim 17, wherein the control component comprises logic and circuitry to facilitate automatic allocation of one or more system resources to the plurality of heating elements in accordance with the associated budget and/or user settings.

31. The method of claim 17, wherein the heating element comprises a quartz tungsten halogen heater.

32. The method of claim 17, wherein the computing component is further operable to execute a heating algorithm to cook at least one food substance in the cooking chamber, detect a change in state of the at least one food substance, and modify the heating algorithm to reconfigure the system resources supplied to one or more heating elements in response to the change in state and in accordance with the associated budget for the system resources.

Technical Field

Various embodiments relate to a cooking system, such as an oven.

Background

Cooking art remains as an "art" due, at least in part, to the inability of the food industry to systematically help cooks prepare valuable dishes. To make a rich main meal, a cook must typically use multiple cooking appliances, understand the heating patterns of the cooking appliances, and make dynamic decisions based on the cook's observations of the progress of the target food product (e.g., transitions due to cooking/heating) throughout the cooking process. Thus, while some low-end meals (e.g., microwavable meals) may be microwaveable or quickly prepared (e.g., instant noodles), traditionally truly complex meals (e.g., steaks, kebabs, delicate desserts, etc.) are not easily systematically prepared using conventional cooking equipment. An intelligent cooking system capable of automatically and stably preparing complex meals in an accurate, rapid and technician-intervention-free manner has not been created in the industry.

Drawings

Fig. 1 is a block diagram illustrating an adaptive cooking system according to various embodiments.

Fig. 2 is a block diagram illustrating functional components of an adaptive cooking appliance and related systems according to various embodiments.

Fig. 3 is a block diagram illustrating a process for implementing an adaptive cooking system, according to various embodiments.

Fig. 4A is a block diagram illustrating a process for implementing an adaptive cooking system, according to various embodiments.

Fig. 4B-G are exemplary user interface screenshots of an adaptive cooking appliance, according to various embodiments.

Fig. 5 is a block diagram illustrating an adaptive cooking appliance and user equipment according to various embodiments.

Fig. 6 is a flow diagram illustrating a method of operating an adaptive cooking device using image feedback according to various embodiments.

Fig. 7 is a flow diagram illustrating a method of operating an adaptive cooking device using images and probe feedback, according to various embodiments.

Fig. 8 is a block diagram illustrating a recipe generation process according to various embodiments.

Fig. 9 is a flow diagram illustrating a method of operating a cooking appliance to cook edible substances in different modes according to various embodiments.

Fig. 10 is a block diagram of a server system implementing a cloud-based recipe store, according to various embodiments.

Fig. 11 is a control flow diagram illustrating an example of a recipe according to various embodiments.

Fig. 12 is a flow diagram illustrating a method of operating a server system implementing a cloud-based recipe store, according to various embodiments.

Fig. 13 is a flow diagram illustrating a method of configuring a cooking appliance with a recipe, according to various embodiments.

Fig. 14A-14F illustrate an exemplary oven user interface according to various embodiments.

Fig. 15A-C are exemplary screenshots illustrating a "main kitchen mode" according to various embodiments.

Fig. 16 is a flow diagram illustrating a resource allocation method according to various embodiments.

The figures depict various embodiments of the present disclosure for purposes of illustration only. One skilled in the art will readily recognize from the following discussion that alternative embodiments of the structures and methods illustrated herein may be employed without departing from the principles of the embodiments described herein.

Detailed Description

Several embodiments disclose an adaptive cooking appliance (e.g., an oven, a closed cooking chamber, or other means) having one or more heating elements controlled by a computing system (e.g., one or more of a Computer Processing Unit (CPU), controller, Application Specific Integrated Circuit (ASIC), or other system-enabled component). The computing system controls operation of the adaptive cooking appliance, including the peak emission wavelength of the heating element. The computing system may implement an interactive user interface to control or assist a user in controlling the adaptive cooking appliance. The computing system may also adjust the operation of the adaptive cooking appliance according to manual user input, user preferences, and/or learned user behavior. For example, the interactive user interface may be implemented on a touch screen of the cooking appliance or a user device in communication with the adaptive cooking appliance that links to user-specific information stored in an associated user account. In various embodiments, the adaptive cooking appliance operates within a larger ecosystem linking users with meal kit providers, grocery stores, user communities, professional chef recommendations, and other services and functionality.

In various embodiments, the adaptive cooking appliance may instantiate and execute a heat adjustment algorithm (e.g., also referred to as "heating logic" or "heating algorithm") for implementing the recipe. The heat adjustment algorithm may include a set of instructions for configuring and controlling the operation of the cooking appliance adapted to the user information. In some embodiments, the adaptive cooking appliance may directly simulate one or more types of conventional cooking equipment (e.g., an oven, a barbecue grill, a stove, a microwave, a smoker, or any combination thereof). In some embodiments, the adaptive cooking appliance may download or receive one or more recipes from a computer server system (e.g., directly or indirectly), including cooking logic for implementing the recipes on the cooking appliance.

The computer server system may include a recipe design interface that allows for the creation of recipes for cooking appliances and the generation of cooking logic, including directly specifying how the heating elements should operate to cook edible substances given one or more system resources (e.g., total power budget, current budget, and total energy budget). For example, the formulation interface may simulate a time series plot of temperature gradients of different food product profiles (e.g., corresponding to different comestible substances). The recipe interface may configure a simulation of a conventional cooking appliance and translate it into a set of heating element configuration parameters for the adaptive cooking appliance. In another example, the recipe interface may specify a temperature, a duration, an expected cooking appliance simulation type (e.g., direct food grilling, impingement convection cooking, heated tray cooking, burning, etc.), a desired user intervention (e.g., flipping the food product or adding sauce or seasoning), an operational mode (e.g., low stress mode and high speed mode), a desired food end state (e.g., triple, quintuple, full) or any combination thereof.

Referring to fig. 1, an exemplary adaptive cooking system 100 will be described. The adaptive cooking appliance 110 includes a heating component 112, a feedback component 114, and an adaptive cooking engine 116. The heating member 112 comprises a controllable heating element, such as a heated filament. In various embodiments, the feedback component 114 includes one or more cameras, probes, and sensors that provide real-time feedback during the cooking process. The cooking engine 116 executes cooking logic to adaptively control the cooking of edible substances, such as food products, according to recipes and information received from feedback components.

The adaptive cooking appliance 110 operates at a location 120, such as a user's residence. In various embodiments, the user device 130, the smart appliance 134, and other system components may be operated at the location 120 or distributed across two or more locations, allowing the cooking appliance to be operated remotely over the network 150 (e.g., from the user's car). The user device 130 comprises a client application 132 for interfacing with the adaptive cooking appliance 110 and the recipe server 140. In various embodiments, the user device 130 may comprise a mobile device, such as a mobile phone, tablet or laptop computer, desktop computer, or other computing device suitable for communicating with the adaptive cooking appliance 110 and/or the recipe server 140 as described herein. In some embodiments, the smart appliance 134, such as a refrigerator, may provide information to various system components regarding food materials that are available for various recipes. In operation, the adaptive cooking appliance 110 may receive a recipe through a user interface of the cooking appliance, the client application 132 on the user device 130, the recipe server 140, or through another device. The cooking engine 116 implements corresponding cooking logic for controlling the heating component 112 while monitoring the feedback component 114 to adaptively control the cooking process.

The adaptive cooking appliance 110 and the user device 130 may be connected to the recipe server 140 through a network 150, such as the internet. In one embodiment, the recipe server 140 is connected to a recipe database 142 that stores data associated with recipes and cooking logic for implementation by the adaptive cooking appliance 110 and a user database 144 that stores user specific information such as collected recipes, end user generated recipes, user specified preferences (e.g., a user may consider "quarter-ripe" to be more familiar than standard defined), learned user behavior, and other user specific content. In various embodiments, the user-specific information stored in the user database 144 includes information learned from the user's behavior. For example, the user database 144 may store information that the user may wish vegetables to be particularly crisp based on other meals that the user has cooked. The user database 144 may also store the following information: users tend to measure the food product height as 10% below the actual height and/or tend to improperly insert the probe into the protein in a particular manner. For example, the cooking appliance may use the user-specific information to adapt the cooking logic to the address at which the user deviated from the recipe.

In various embodiments, the recipe database 142 stores one or more recipes, food product characteristics, heating algorithms, sensor data, cooking logic, or other relevant information. In various embodiments, the recipe server 140 provides cloud-based recipe storage and access. In some embodiments, the user device 130 may be connected to the cooking appliance 110 via a wireless network, a local area network, a peer-to-peer connection (e.g., bluetooth), or another communication protocol.

In various embodiments, the user database 144 stores information of users of the adaptive cooking system, which may include user preferences, stored recipes, identification of the adaptive cooking appliance 110 associated with the user, learned user behavior, subscription information defining access rights based on paid subscription levels and/or other user-specific information. In one embodiment, the user may pay a subscription that provides the user with access to up-to-date recipes, meal kits, general grocery services, special content (such as special cooking programs or live social media activities), early access to content, special functionality, discounts, and full-scale services (white-day services) through one or more providers 152. In one embodiment, the vendor system 152 is connected to the recipe server 140 through the network 150. A user operating the adaptive cooking appliance 110, the user device 130, or other networked device may access content on the recipe server 140, including recipes and online shopping options, to purchase a corresponding meal kit (e.g., a set of ingredients, cooking items, and/or instructions for preparing a meal prepared according to a user skill level or preferences), a pre-prepared food item (e.g., an uncooked food item that has been prepared for oven cooking), an ingredient, a supply, etc., from a vendor for delivery to the user location 120 or other designated location. The meal kit and the pre-prepared food items may also be purchased from a physical grocery store whose system is linked to the cooking appliance and/or the user account. In one or more embodiments, the cooking appliance may be tied to shopping options to recommend certain meal kits and other items. In one embodiment, when a meal kit or food item is delivered, the vendor system 152 may notify the recipe server 140, the adaptive cooking appliance 110, or the user device 130 that the delivery has arrived, and the recipe server 140 (or the vendor system 152, the user device 130, or other system device) transmits the recipe and associated cooking logic to the adaptive cooking appliance 110, allowing the user to cook the delivered meal kit or food item according to the corresponding recipe.

In various embodiments, the system 100 may also include a content provider 154 that provides content related to the food product to the user, such as videos related to the food product, cooking descriptions, online articles, social media, recipes, and other information associated with the food product. The content provider 154 may include links to the recipe server 140 and the provider system 152 in the online content, allowing the user to access recipes associated with the content and purchase associated food materials or meal packages for delivery. In some embodiments, a guidance video may be provided during meal preparation to provide guidance to the user in meal preparation (e.g., how to measure food height, how to insert a probe). The user may be prompted to view the instructional video based on a determination that the user is to be assisted (e.g., based on user-specific information stored in a user database).

In various embodiments, the recipe server 140 provides various recipe browsing, selection, and configuration options. For example, the recipe server 140 may recommend recipes based on available food materials identified by the user or tracked by the system 100 (and based on user history and usage statistics), such as by the smart appliance 134, or based on a subscription history from the supplier system 152. The user may also manually enter the recipe into the recipe server 140 through the client application 132. In various embodiments, the recipe server 140 and/or the adaptive cooking appliance 110 are configured to transform the recipe into oven-specific cooking instructions, including optimized food preparation instructions for the user and cooking logic for controlling the adaptive cooking appliance 110. In one embodiment, the recipe and cooking logic may be configured to accelerate cooking on the adaptive cooking appliance 110, thereby reducing cooking time compared to conventional cooking devices. In one embodiment, the recipe server also facilitates an online community, allowing users to share and develop recipes and other user-generated content.

Fig. 2 illustrates functional components of an adaptive cooking appliance and related systems according to various embodiments. The adaptive cooking appliance 200 may include a cooking/feedback component 210, a controller 220, a memory 230, a communication interface 240, a user interface component 250, and a power source 260. The cooking/feedback component 210 may include one or more heating/cooling elements 212, a camera 214 or other machine vision component, one or more probes 216, and a plurality of sensors 218.

The controller 220 controls the operation of the cooking appliance 200, including performing various functional components, such as the components represented in the memory 230. For example, memory 230 may store program instructions executed by controller 220, which may include an appliance operating system 232, user interface logic 234, and a cooking engine 270. The cooking engine 270 controls the cooking/feedback component 210 through the cooking logic to implement the recipe. In various embodiments, the data storage device 276 stores configuration, recipe, cooking logic, food characteristics, and system information, including image files or video files captured by the camera 214.

In one embodiment, the heating element 212 is wavelength controllable. For example, the heating elements 212 may comprise quartz tubes, each enclosing one or more heating filaments. Since the operating temperature of the heating filament can be very high, a cooling means can be provided to provide convective cooling to prevent damage to the heating element.

The camera 214 may include one or more optical or thermal cameras, or other machine vision devices, providing a digital representation of the interior of the cooking appliance 200. In one embodiment, the camera 214 in conjunction with the display provides a virtual window to the interior of the chamber of the cooking appliance 200, which may be windowless. In one embodiment, the camera includes a fisheye lens. In various embodiments, the camera streams images to a display on an adaptive cooking appliance (e.g., user interface component 250), to a client application 282 executing on user device 280 (through communication interface 240), or to cooking engine 270 for analysis during cooking. Camera 214 may act as a food package label scanner that configures cooking appliance 200 with a machine-readable optical label that identifies food packages. In some embodiments, the camera 214 may provide an image stream to the cooking engine 270, which may be analyzed to provide feedback during execution of the cooking logic (e.g., to monitor maturity). In some embodiments, the camera 214 includes a light source that can illuminate the interior of the cooking appliance 200 such that the camera 214 can capture an image of the food substance therein.

In one embodiment, the probe 216 may include a temperature probe that is inserted into the edible substance to take a temperature reading of the edible substance during cooking. For example, the temperature probe may be a multi-point temperature probe that sends multiple streams of temperature readings (e.g., each corresponding to a point along the length of the temperature probe) to the cooking engine 270. In various embodiments, the probe is electrically coupled to the interior surface of the oven through a connection adapted to receive one or more signals corresponding to temperature readings. The cooking engine 270 may receive one or more continuous temperature reading feeds from the temperature probe 216 via the connection interface. In these embodiments, the cooking engine 270 may determine the temperature reading by analyzing/decoding the signal. In response to changes in temperature readings from the continuous feed, the computing device may execute a heat adjustment algorithm that is dynamically controlled by the cooking engine 270.

When the adaptive cooking appliance 200 is used to cook edible substances, cooking logic corresponding to the recipe is executed to control the cooking process. The cooking logic may include a heating algorithm that specifies a heat adjustment performed by the cooking engine during cooking. In some embodiments, the cooking engine 270 is configured to detect the center of the edible substance such that the cooking engine 270 can accurately assign a stream of temperature readings to correspond to the center of the edible substance. This enables the cooking engine to monitor the temperature gradient at different parts of the edible substance, thereby achieving an accurate cooking method. In one example, the computing device may detect the center of the edible substance based on a user-entered insertion angle and/or insertion depth of the temperature probe 216 and/or temperature readings from the continuous feed. In another example, the angle of action and/or depth of insertion of the temperature probe 216 is specified by the heating recipe.

In some embodiments, the display of the cooking appliance may present the user with an insertion angle and insertion depth to enable the user to insert the temperature probe 216 into the edible substance according to those specifications. In some embodiments, the connection interface is configured to mechanically couple to a portion of the food tray and communicate with the relay interface of the food tray to the controller 220.

In various embodiments, the cooking engine 270 may analyze images received from the camera 214 and data received from the probe 216, sensor 218, and other feedback devices to enable dynamic control of the heating algorithm. The temperature probe 216 may extract (e.g., harvest) power from the power source 260 by harvesting power from capacitive coupling to AC current through the conductive chamber wall and the food tray. In turn, the temperature probe 216 may utilize the acquired power to generate wired electrical, audio, radio frequency, inductively coupled, and/or capacitively coupled signals to the connection interface. For example, the signal may be generated using one or more passive electronic components that produce different signals in response to receiving electrical power in different temperature ranges. In one embodiment, the probe includes a temperature sensor and is configured for temperature gradient detection.

The communication interface 240 facilitates communication between the cooking appliance 200 and an external computing device. For example, the communication interface 240 may enable a Wi-Fi (e.g., 802.11) or bluetooth connection between the cooking appliance 200 and one or more local devices, such as the user device 280 or a wireless router, that provide network access to the remote server 290, such as over the internet. In various embodiments, the communication interface 240 may include other wired and wireless communication components to facilitate direct or indirect communication between the cooking appliance 200 and another device. In turn, the cooking appliance may access the cloud services through an internet connection.

The user interface components 250 may include a touch-screen display, a keypad, one or more buttons, and other input/output components (e.g., knobs or dials for scrolling through menus and recipe options, an audio microphone) to enable a user to interact directly with the functional components of the cooking appliance 200. For example, the display may present images from the camera 214. The display may also present a user interface implemented by controller 220 and user interface logic 234. The input means may include a touch panel covered with a display (e.g., collectively referred to as a touch screen display). In some embodiments, the input component is one or more mechanical buttons, switches, or capacitive sensing devices. In some embodiments, the output component includes a speaker or one or more external lights. Embodiments of exemplary user interfaces are illustrated herein in fig. 14A-14F, as described below. In various embodiments, the cooking appliance 200 is adapted to receive user input from a user interface provided by one or more of the user interface components 250 physically coupled to the adaptive cooking appliance 200, and a user device 280 that may be remotely connected to the adaptive cooking appliance 200. In one embodiment, the adaptive cooking appliance 200 includes one or more features to prevent unauthorized or inadvertent operation of the adaptive cooking appliance 200, such as requiring a user to physically interact with a physical user interface component 250 physically coupled to the adaptive cooking appliance 200 (e.g., by pressing a physical button on the adaptive cooking appliance 200) in order to initiate a recipe/heating algorithm.

Cooking appliance 200 may implement an adaptive cooking engine 274, a data store 276, and a recipe library 278. In some embodiments, the adaptive cooking engine 274 may execute cooking logic to analyze feedback components, such as images from the camera 214, the probe 216, and the sensor 218. For example, the oven configuration, such as the position of a shelf within the oven or whether the oven door is open or closed, may be determined by feedback from one or more sensors 218 or feedback from the camera 214. In some embodiments, the sensors 218 include one or more of a plurality of temperature sensors, a plurality of power output sensors, an ambient light sensor, a door opening sensor, a rack placement sensor, and other sensors that provide feedback during cooking operations. In one embodiment, the images from the camera 214 may be analyzed to dynamically adjust the cooking algorithm to eliminate possible harmful darkening and smoke generated by overcooked meat fat. In another embodiment, the image from the camera may be illuminated by a particular color of a particular light source when facing the interior of the cooking appliance 200.

In some embodiments, the adaptive cooking engine 275 is configured to analyze the image from the camera to determine if the machine-readable optical label is within the image. For example, the adaptive cooking engine 274 may be configured to select a recipe from the recipe library 278 based on the machine-readable optical label and implement the corresponding cooking logic. In some embodiments, the communication interface 240 is configured to send a message to the user 280 to confirm the automatically selected recipe. In some embodiments, the adaptive cooking engine 274 is configured to present a recipe to a user on a local display and receive a confirmation via a local input component when the recipe is displayed. In response to the selection of the recipe, the adaptive cooking engine may execute cooking logic by controlling the heating element according to a heating algorithm.

A user device 280, such as a mobile device, may be connected to the adaptive cooking appliance 200 through the user interface component 250. For example, user device 280 (e.g., a computer or mobile device) may configure cooking appliance 200 in real-time via user interface logic 234. In one example, the user may select a recipe via a client application 282 running on the user device 280, and the client application 282 may communicate through the user interface logic 234 to cause the cooking appliance 200 to execute corresponding cooking logic. The client application 282 also includes an interface with the cooking appliance 200, which may include placing recipes for any meal purchased by the user or any recipe saved to the cooking appliance 200 by the user, thereby preparing the cooking appliance for cooking recipes by pressing a button. The communication interface 240 may also enable the cooking appliance 200 to access network services, such as cloud services available from the recipe server 290, to facilitate execution of cooking logic from the recipe database 292. User account information, preferences, recipe history, meal kit order history, and other user functionality may be facilitated through the use of user database 294.

The components (e.g., physical or functional) associated with the cooking appliance 200 may be implemented as devices, modules, circuits, firmware, software, or other functional instructions. For example, the functional components may be implemented in the form of dedicated circuitry, across one or more components in the form of one or more suitably programmed processors, single board chips, field programmable gate arrays, network-enabled computing devices, virtual machines, cloud computing environments, or any combination thereof. For example, the described functional components may be implemented as instructions on a tangible storage memory capable of being executed by a processor or other integrated circuit chip. The tangible storage memory may be volatile memory or non-volatile memory. In some embodiments, volatile memory may be considered "non-transitory" in the sense that it is not a non-transitory signal. The memory spaces and storage devices depicted in the figures may also be implemented with tangible storage memory, including volatile memory or non-volatile memory.

Each component may operate separately and independently of the other components. Some or all of the components may execute on the same host device or on separate devices. These independent devices may be coupled through one or more communication channels (e.g., wireless or wired channels) to coordinate their operations. Some or all of the components may be combined into one component. A single component may be divided into subcomponents, each of which performs an independent method step or a method step of the single component.

In some embodiments, at least some of the components share access to a memory space. For example, one component may access data that is accessed or converted by another component. Components may be considered "coupled" if they share a physical or virtual connection, either directly or indirectly, allowing data accessed or modified by one component to be accessed in another component. In some embodiments, at least some components may be upgraded or modified remotely (e.g., by reconfiguring executable instructions that implement a portion of the functional components). The systems, engines, or devices described herein may include additional, fewer, or different components for various applications.

In one embodiment, the cooking engine optimizes oven operation according to various user goals (e.g., goals for burn level, doneness or internal temperature, juiciness, internal moisture content), which may include cooking an optimal meal, reducing cooking time, and cooking multiple meals at a time. Using the various components of cooking appliance 200, the cooking engine identifies the current state of cooking and adjusts cooking parameters to reach future states in terms of temperature, moisture content, shape and surface flavor, and mouthfeel.

The power source 260 provides the power required to operate the physical components of the cooking appliance 200. For example, power source 260 may convert Alternating Current (AC) power to Direct Current (DC) power for physical components or deliver AC directly. In some embodiments, power source 260 may operate a first powertrain to heating element 212 and a second powertrain to other components.

Referring to fig. 3, a block diagram illustrating a process for implementing an adaptive cooking system according to various embodiments will now be described. In step 302, an initial set of recipe data is created for the system using an oven test environment 304, which may include components of the cooking appliance 200, the recipe server 140, and the user device 280. The test environment 304 may include functional components including an adaptive cooking engine 306, thermophysics 308, food characterization algorithms 310, algorithms 312, and a recipe compiler 314. The system includes a database 316 for compiling recipes, sensors, food characteristics, and other data. The recipe may include a pre-existing recipe or a proprietary recipe developed for the adaptive cooking appliance 200. In some embodiments, the user may select a conventional recipe (e.g., baking at 400 degrees for 30 minutes) or a terminal-based recipe (e.g., burning cooking to quarter-cook with a hard fire). In one embodiment, the recipes are developed and tested by professional chefs that define basic food characteristics for a variety of recipes (e.g., chicken cut into weights and shapes) and test various cooking parameters such as cooking temperature, time, and results. The food characteristics and test information are stored in database 316. The food product characteristic parameters may include the type of food product, the cutting, size, shape, and cooking temperature of the food product, sensor data during cooking, and various other cooking parameters. In one embodiment, the food product characteristics include a heating algorithm for controlling the adaptive cooking appliance to properly cook the identified food item.

Next, in step 320, a cooking model is generated that defines the operation of the adaptive cooking appliance 200 for various recipes including one or more food product characteristics. The cooking model may include a range of acceptable cooking parameters including cooking temperature, time, sensors, and probes and image data for proper cooking. The information is compiled to create cooking logic that is provided to the cooking appliance. In step 330, the main kitchen uses the cooking model to generate a new recipe. For example, the food characteristics of chicken may be used in various chicken formulations. The system then generates recipes and adaptive cooking logic for further testing and validation. The validated recipe is then stored in a network accessible memory for access by a user of the adaptive cooking appliance through a recipe server, which may be accessed through a cloud or internet service. The content generation process 340 may be repeated at various times during the life of the adaptive cooking appliance and associated system. In various embodiments, in step 350, the user accesses the recipe server and selects a recipe as described herein, for example, by selecting a recipe, entering a new recipe, or ordering a meal kit with an associated recipe. In step 352, the cooking appliance receives the recipe and corresponding cooking logic that may be started by the user in step 354 to cook the recipe. In various embodiments, the recipe and cooking logic may depend on preferences entered by the user and parameters stored by the adaptive cooking appliance that represent learned user behavior. For example, the user may select a single cook with desired end state parameters selected by the user, multiple cooks with such end state parameters selected, double cooks with such parameters selected, cook at multiple oven levels, a one-stop "cook this" recipe for a pre-designed meal kit, a regular cooking process with a selected process (such as bake/broil), or accelerate. The cooking appliance follows the heating algorithm from the recipe and tracks the temperature, sensors, user data and other information during the cooking process. After the recipe is complete, the user may perform additional manual operations (e.g., perform additional cooking to achieve a desired degree of maturity), discard the recipe, save the recipe, or provide other user-initiated feedback. In various embodiments, selected data accumulated during the cooking process may be uploaded to the recipe server for further processing. In one embodiment, the recipe is stored in the cooking appliance for use by the user after adjustments are made for user feedback and deviations in sensor data, images, and other tracking information compared to the initial cooking model. In one embodiment, the tracked system feedback information includes images from the camera and results of image analysis during cooking. In some embodiments, the accumulated data includes data about the food product, including characteristics before, during, and after cooking, the source of the food product, feedback of inputs used during or after cooking, parameters related to the user, such as how to insert a probe (e.g., angle, depth), how to cut certain edible substances (e.g., relatively small or large compared to a one-inch cut), and/or other tracked information (and relationships between two or more data items).

In various embodiments, a user subscribes to a formula service that includes a prepackaged meal or grocery delivery service. For example, the user may pay a small monthly subscription fee and then purchase a separate meal kit or grocery online. The supplier can prepare a meal kit with fresh food material according to the associated recipe. The supplier can track the delivery and download the recipe and cooking logic to the adaptive cooking appliance after the meal kit arrives. The user may then place the meal kit in the cooking device and select a recipe for cooking. In one embodiment, when the meal kit reaches the user location, the recipe appears on the display of the cooking device (e.g., highlighted as a suggested recipe at the top of the home screen). In another embodiment, a camera of the cooking device images the meal kit as it is placed in the cooking device and identifies the associated recipe and cooking logic. These methods allow a user to activate cooking logic by pressing a single button to cook a fresh meal. In another embodiment, the user selects one or more recipes and the vendor selects the best food material to deliver to the user for the selected recipe. The cooking appliance receives a recipe that includes preparation instructions for a user and automatic cooking logic for the cooking appliance. In some embodiments, the recipe service, cooking appliance, and/or other device tracks user data and makes meal kit and/or grocery recommendations based on user preferences and usage statistics. For example, the recipe service may offer a specific kind of salmon, as the user likes salmon, which tastes better after being placed at a specific internal temperature.

With reference to fig. 4A, an exemplary subscription model will be further described. The user subscribes to a recipe service through the user device 402, which may include discounts, early visit to new recipes, meal package delivery, and online grocery store integration. In various embodiments, one or more subscription options may include other features, such as free shipping, expedited shipping, enhanced functionality on the oven (i.e., functions available only to subscribers), access to special content (cooking videos, local events, parties), and early access to content. In one embodiment, the subscription feature may include automatic delivery of the recipe to the oven (e.g., recipes corresponding to food and other recipe-related items ordered from the supplier) and special recommendations based on user-specific information.

The meal kit provider 420 prepares a meal according to one or more recipes available in the recipe database 412. In various embodiments, a meal kit can include a collection of ingredients (e.g., raw ingredients for meal preparation; pre-prepared ingredients ready for cooking), cooking supplies according to a skill level or preference of a user, and/or instructions for preparing a meal. In one embodiment, the meal kit provider 420 prepares a meal kit for an existing recipe. In other embodiments, a meal kit provider (e.g., a restaurant) may also provide a meal kit for a proprietary recipe according to the provider's food options. The meal suite provider 420 may be, for example, an independent business, a restaurant or grocery store that provides out-of-the-shelf meals. The meal kit provider 420 may be a third party enterprise or a food preparation service associated with or provided by the same entity that operates the recipe server 410. In one embodiment, the meal kit provider 420 may access the recipe server 410 through a web interface and associate the meal kit with the recipe options.

The user may have an associated user account and cooking appliance with an identifier associated with it through the user database 426 of the recipe server 410. In operation, a user accesses the recipe server 410 through a user interface of the cooking appliance 440 or a client application 404 on the user device 402. The client application 404 includes a login screen 406 for logging into the user's subscription account. The user may then browse recipes 408, identify food items for the selected recipe 410, and order food items 414 through providers, such as a meal kit provider 420 and an online grocery provider 422, that deliver uncooked food items for the selected recipe to a location associated with a cooking appliance 440. In one embodiment, the formula appears on the screen with options from the meal kit or grocery provider. The providers 420 and 422 track the delivery of orders to cooking appliance locations and notify the recipe server 410 to download recipes and corresponding cooking logic after the orders are received. In another embodiment, the recipe and cooking logic may be obtained from a client application on the user device, such as by a user-stored recipe 416, and may be dropped to the oven through an oven interface 418. In various embodiments, a user may order a meal kit for pickup at a supplier location, and after the user receives an order from the supplier, the corresponding recipe and cooking logic may be delivered to the cooking appliance. In some embodiments, a user may access the recipe server 410, the meal kit provider 420, and the online grocery provider 422 through a user interface of the cooking appliance 440 to implement an online shopping function as described herein.

In one embodiment, the user may select multiple recipes from the recipe server 410, such as a weekly meal plan, and the online grocery provider 422 may aggregate the necessary food materials, including preparing and cutting into food in a desired proportion according to optimal food characteristics, and preparing and delivering orders as described herein. The selected recipe and cooking logic are then available to the cooking appliance through the client application. In another embodiment, the available food materials can be provided to the recipe server 410, which identifies recipes based on the available food materials, user preferences, and other user specific information. The system may also be integrated with an intelligent device, such as an intelligent refrigerator, that provides current food options to the recipe server for recipe selection.

In one embodiment, advanced food services are provided. The professional master kitchen creates recipes specific to the cooking appliance using controlled portions of food materials available through one or more providers. As described herein, recipes are tested and optimized for professional quality cooking, and quick cook options are available that can increase cooking speed, such as cooking at 1/3 to 1/8 of regular oven time. The provider provides good-quality food materials prepared specifically for each recipe. In this way, the recipe can be accurately reproduced with different skills by different users in different areas. The supplier may deliver fresh food material to the user's home door according to a delivery schedule, such as within 2 days after the order. In one embodiment, the food or meal kit will arrive with instructions to the user and the cooking logic pre-downloaded to the oven. In this way, novice users can prepare a main-kitchen-quality meal without difficulty. The quality of the food material can be controlled and the system described herein produces a simple, easy to follow instruction for the user.

In various embodiments, a user may order a meal kit through a user interface associated with a cooking appliance (e.g., a touch screen interface, a voice control interface, an interface through a communicatively connected mobile device, etc.). The cooking appliance may be linked to one or more user accounts through one or more servers (e.g., recipe server 410 of fig. 4A). After a user purchases a meal kit through (or associated with) a user account, the corresponding recipe and cooking algorithm may be automatically transmitted to the cooking appliance. In various embodiments, the cooking appliance may further bind user-related and cooking-related information (e.g., initial data of food products and cooking environments, food products and cooking environments throughout the cooking process, user assessment of cooking results through a user feedback interface such as that shown in fig. 4G, etc.) to a particular user account via a user account, email, credit card, or other user identifier.

In some embodiments, a user may desire to cook a particular food material (e.g., from a particular supplier/partner and/or obtained independently by the user) or meal to achieve a desired result. For example, a user may obtain a meal package from an online marketplace or formula store (e.g., via a user interface on a cooking appliance, via an application on a mobile device, through a web browser) or via a grocery store (e.g., using a frequent flyer card on a system linked to a cooking appliance over a communications network). The user may order food items upon logging into a user account associated with the cooking appliance, allowing the meal kit contents and recipes to be downloaded to the user's cooking appliance. A frequent flyer card associated with a brick and mortar store or online store may be associated with a third party store account, which may be linked to an account associated with the user's cooking appliance. For example, a user may have a subscription account that automatically downloads food purchases to the user's cooking appliance. The subscription account may link to a third party account service associated with the user (e.g., grocery store) to provide meal kit information or other food purchase information to the cooking appliance and other benefits (e.g., subscriber benefits) to the user.

In some embodiments, recipes, cooking algorithms, and user specific information associated with the meal kit may be downloaded to the cooking appliance. The user-specific information may include user preference information including recipe preferences selected by the user (e.g., cooking meat to four degrees) and/or stored parameters based on past user experiences or settings. For example, a user may order a meal kit and execute a recipe to cook meat to quarter-cooked, but then determine that the cooked meat is too raw and instruct the cooking appliance to post-cook the meat for a longer time after cooking. The user may also "dress" the cooked meat to add additional burns. The user interactions received by the cooking applicant before, during and after the cooking deviating meal kit recipe may be stored as user preferences and used together with the meal kit or a similar meal kit (e.g. another meal kit comprising the same meat) for the next execution of the recipe. For example, after cooking the meal kit, the user may be prompted to provide feedback to the cooking appliance through a user interface (such as the user interface feedback screen presented in fig. 4G), prompting the user to give ratings and other feedback.

In various embodiments, the meal kit recipe information and settings may be accessed through a user interface on the cooking appliance. The user interface may also guide the user to prepare the meal kit in a particular manner and then place it in the chamber of the cooking appliance. Exemplary screenshots of user interfaces for facilitating various aspects of the present disclosure are illustrated in fig. 4B-G. For other non-meal kit cooking scenarios, such as cooking foodstuffs purchased by a user at a local farmer market, a similar interface may be provided to the user.

In one embodiment, the user interface provides meal kit information in a conspicuous location, allowing the user to select a meal kit and execute a recipe. For example, as shown in the embodiment of fig. 4B, the user may log into a user interface (e.g., screen 450) of the cooking appliance to link the cooking appliance to the user's account. The user interface may then provide user specific data such as ordered meal kits 454, the most recent recipes 455 the user cooks on the cooking appliance, tagged recipes of interest 456, recommendations 457 for new recipes, and other information such as the date/time the meal is expected to be delivered via delivery, frequently cooked recipes and preferences, the identity of the person to eat each meal kit or recipe, and their personal preferences such as maturity and burning levels.

The meal kit may include a collection of groceries or food products that are combined in appropriate amounts and proportions to provide a convenient and appealing meal to the user with fewer food product preparations than conventional meal preparation techniques. However, many users will choose to use the cooking appliance and meal kit functionality by preparing their food materials. The contents of the meal kit may be delivered to the user via the recipe. However, the user may find it necessary to conveniently replace different food materials or recipes in an otherwise explicitly specified meal kit. For example, the meal kit may include a fimbria with broccoli and potatoes, and the user may replace the broccoli with green beans having different thermal and cooking characteristics. In some embodiments, known recipes, such as meal kit recipes, may be replicated via a user interface and slightly modified to accommodate different meal preferences. In some embodiments, the user may be prompted to enter changes to the recipe through a user interface. The recipe generator may then adapt the recipe to changing conditions. For example, if broccoli is substituted for green beans, less heat is typically required in order to properly cook (rather than burn) the green beans. In one embodiment, the user may copy the entire recipe of the fizeau broccoli and potatoes, and the cooking engine may adjust the cooking zone in which the broccoli is placed to accommodate the green beans without adversely affecting the rest of the food.

In various embodiments, the recommended formula 455 (e.g., main kitchen pick) may be determined based on one or more of the following: user preferences, information collected from previous cookings of the user, usage statistics and ratings of similar users, user preferences and ratings related to past cookings of the user, and/or other data tracked by the cooking appliance and/or user account. In some embodiments, the recipe suggestions may also take into account the geographic location of the user (e.g., based on the user's preferences in a particular geographic location), which may be determined by IP address determination, user delivery address, address associated with a user account, point of sale location, GPS, or other means.

After the user selects a meal kit (or recipe using food materials purchased by the user) for cooking on the cooking appliance, the user may be prompted by the user interface on the step of the user preparing the meal. An exemplary embodiment of a user interface will now be described with reference to the screenshot of FIG. 4C. In this embodiment, the user is prompted to take certain measures to determine certain characteristics of the food product or cooking environment. For example, the user may be prompted to measure the height of the protein or other edible substance to be cooked to configure the heating algorithm to achieve the desired result. A measurement identifier or reference object associated with the meal kit or cooking appliance may assist the user in providing information about the food product characteristics.

For example, as shown in the screenshot of fig. 4C, the user may be prompted (screen 460) to measure the height of the protein (e.g., chicken) using a temperature probe, such as one used to measure the internal temperature of the edible substance during cooking. In various embodiments, the temperature probe may include a pointed/pointed portion with certain markings or coloration that may assist in height measurement. The user may then be prompted to enter a measured height, such as by entering a numerical measurement or graphically indicating the height (such as by moving the graphical slider 461 to the appropriate position on the probe displayed on the screen 462). In various embodiments, the cooking algorithm may be adjusted based on the detected height of the edible substance and other known food product characteristics. The user interface may also include graphical, audio and/or visual cues and information so that the user can conveniently input food product characteristics (e.g., the height of the food product) in a simple manner, even if the user does not have a priori knowledge of measuring the food product for cooking, or if the user has previously had difficulty accurately measuring the height.

In various embodiments, the cooking appliance may determine whether the user has height measurement difficulties in previous recipes, and the type of difficulty the user has encountered (e.g., overestimating or underestimating the height, and statistics associated therewith), by, for example, determining whether the food product is too burned or not burned during cooking. In this way, the oven may learn the user's behavior and determine user-related parameters that may be stored and used for later cooking (e.g., by adjusting the cooking logic to account for possible erroneous measurements by the user).

The user may also be prompted to place the food in a certain position on the tray, and how and where to insert a temperature probe (such as a multi-point temperature probe) into the protein or other edible substance (screen 464). The user interface may also provide prompts to customize the meal (screen 465), instructions as to where to place the food tray in the oven (screen 466) and when to begin cooking (screen 468).

In various embodiments, a cooking appliance may include one or more processes that may be individually and/or together configured to learn the operation of the cooking appliance and adapt it to characteristics of the food material, the user, and the environment. For example, the cooking appliance and/or recipe may include an initial configuration that may be updated during and/or after cooking based on sensed, calculated, and/or user provided information (e.g., food and cooking environment data throughout the cooking process, user scores for cooking results, etc.) that is used to adjust the operation of the cooking appliance to achieve one or more desired cooking results. In some embodiments, multiple adaptive processes are used in conjunction with a robust user ecosystem to achieve cooking results that far exceed conventional cooking methods in terms of speed and quality, especially when performed by an inexperienced chef.

Further, the cooking appliance may determine certain data about the food product or the cooking environment without direct input from the user. For example, the cooking appliance may include one or more sensors that provide feedback to verify the type of tray used (e.g., correct material, size, and shape) and/or the position of the tray in the cooking appliance (e.g., top and bottom racks). The cooking appliance may then provide feedback to the user prompting the user to change the tray position, change the probe position, or other changes to produce the optimal cooking environment. For example, to optimally track temperature changes during cooking, a certain probe orientation may be required (e.g., a horizontal orientation parallel to the plane of the cooking tray), and the probe may be equipped with certain hardware/software (e.g., an accelerometer and associated software) to determine the probe orientation.

The user may be prompted via a user interface (e.g., touch screen, audio feedback) for suggested and/or mandatory corrections to optimize the cooking environment for food product characteristics, selected recipes, and user preferences. The feedback may indicate, for example, that the tray position and/or probe insertion is incorrect or not optimal, and the user may be advised to modify such position or orientation. In various embodiments, the cooking appliance may also provide instructional soundtracks, graphics, and/or video to the user via the user interface to explain or demonstrate how to change the tray position, how to properly orient the probe, and even how to properly prepare and place the food product on the tray (e.g., the size of the cut vegetables, whether to stack or spread certain edible substances on the tray, where to place the food product, etc.). For example, fig. 4D shows various user interface screen shots for a user of food placement of eggs in egg trays (screen 470), food placement for meals for multi-zone cooking (screen 472), instructions on determining the height of certain foods (screen 474), and tray positions in a cooking appliance (screen 476).

The cooking appliance may also adjust the cooking algorithm or instructions based on other information about the food product, such as the grocery store, distributor, wholesaler, or producer of the food. The information related to the source may be transmitted to the oven via direct user input, by having the oven scan a bar code or food ID, by tracking the food purchased by the user, or via other means. The cooking appliance may include a database that stores data about food products from these sources, and may optimize recipes based on data collected about how the food product (or similar food product) is cooked when a current or similar recipe is executed. The food product related data may also include user feedback on how to cook the food in the recipe. Cooking appliances, recipe servers, other processing systems may track food, recipe and user information to learn from the collected data and adjust future cooking to produce desired results. Supply chain and market products can also be optimized based on characteristics of the food and the user (food and cooking environment initial condition data, food and cooking environment data throughout the cooking process, user assessment of cooking results, etc.).

Although the cooking appliance may instruct the user to correct the identified errors in the environment, the cooking appliance does not need to perform the recipe perfectly to produce the desired result. In various embodiments, the cooking appliance may adjust the cooking algorithm to adapt to learned or detected user behavior. The cooking appliance may learn over time that a particular user tends to deviate from an ideal cooking environment, such as the user preparing and/or arranging the food product in some manner other than a recipe, continuing to orient the probe incorrectly in the food product, and other detected changes. The cooking appliance may use the learned behavior to adjust the recipe based on the learned behavior to still achieve the desired cooking under given environmental conditions. For example, the cooking appliance may learn that the user inserts the probe in such a way that the lowest temperature reading is typically offset by some millimeter from the point where the temperature in the food product is lowest throughout the cooking process (e.g., by inserting the probe too or not deep enough into the protein), and then the cooking appliance will expect the sensor to have a reading that is a certain number of degrees higher than the reading when properly oriented. The cooking appliance may then cook the food product to a point where the probe reads a temperature that is several degrees higher than the final temperature.

In another example of learned behavior, the cooking appliance may learn that the user tends to "over-sit" a meal after the recipe has finished cooking (e.g., the user cuts the food product after a proposed time such that post-cooking temperature flow within the food product raises the core temperature to a maturity level that is above a desired level), and the cooking appliance may modify the recipe to increase the time that the post-cooking protein core will remain within a desired temperature range, thereby providing the user with a longer window to cut the food product. The user interaction in the resting stage may be guided by a user interface that is displayed to the user via a touch screen or communicated to the user via audio, how long the food product should be resting before reaching the desired temperature, and once the food product reaches that temperature, how much time the user will have available to cut the food product before the temperature rises above the desired maturity level (see, e.g., fig. 14B). Thus, the cooking appliance may use the multivariate learning environment to evaluate user behavior and take appropriate measures (e.g., modifying how the oven prompts the user to cut food, such as by sounding a louder sound or a different audible indication) based on many factors available to the cooking appliance, including sensed data (e.g., user placement of a tray or probe), user preferences, food product characteristics (e.g., food product type, height, placement), and user interaction tracked through the user interface. The cooking appliance may determine whether the user is learning and adapting to the instructions over time, whether certain assessments are individual events and/or whether the user assessments suggest historical trends, and adjust the recipe accordingly. In one or more embodiments, the learning environment is a neural network trained to adapt the cooking algorithm in response to various environmental conditions before, during, and after cooking.

In various embodiments, the user-generated recipe may be entered and modified in a variety of ways. In one embodiment, the user may employ existing recipes and meal kits and change the food material, preparation and cooking time/desired result. Fig. 4E shows exemplary user interface screens that may be presented to the user, including a meal kit recipe, a downloaded recipe, a detailed summary of the recipe entered by the user or other recipes (screen 480), and a screen that prompts the user to enter changes to the recipe made by the user (screen 482). The cooking appliance may analyze the changes entered by the user and modify the cooking to achieve the desired result.

In some embodiments, the user may set up the recipe from scratch. Referring to fig. 4F, the cooking appliance may include a user interface component configured to guide the user through the process, allowing the user to enter recipes and food product characteristics in as detail as possible. The cooking appliance and/or server may identify relevant recipes and/or cooking parameters for the type of food product selected by the user and generate basic cooking algorithms associated with the recipes, which may then be further adjusted based on food product characteristics, environmental characteristics, user preferences, user feedback, and other available information. An exemplary user interface for collecting user feedback in accordance with one or more embodiments is shown in fig. 4G. The adapted recipe may then be automatically adjusted each time the user executes the recipe to achieve the desired cooking result. Thus, the next time the user attempts to cook a recipe, the failed attempts to cook the new recipe will be automatically corrected using the description and further adaptations described herein. It should be appreciated that the cooking appliance of the present disclosure can prepare the recipe in less time and effort than conventional methods.

Referring to fig. 4F, an exemplary user interface screen for single food cooking is shown. The user may be prompted to select a food material (screen 483) and the type of food material selected (screen 484), and the cooking appliance automatically selects an appropriate heating algorithm, as described herein. The user may then be prompted to select a cut for the selected food item (screen 486) and identify the location where the food item should be placed on the tray (screen 487). In this process, the cooking appliance prompts the user for information about the optimized recipe and cooking algorithm, such as the height of the protein (screen 488), the placement of the probe in the protein (screen 489), and the placement of the tray in the cooking appliance 490. The user may also choose to enter a "main kitchen mode" that provides more detailed control over recipe creation, while basic user interface prompts may not provide control over recipe creation.

Based on user preferences, similar recipes, characteristics of the base food material, and other available data, the cooking appliance may prompt/suggest to the user to adjust food product size, cooking time, and other aspects of the new recipe. The cooking appliance may track the cooking through various sensors and user feedback, allowing for automatic correction of unsuccessful recipes during the cooking process and further refinement for the next cooking attempt. If the user does not like the result, the cooking appliance may automatically adjust the recipe and/or suggest changes to the user. As disclosed herein, a cooking appliance may produce a desired result even if a recipe of poor quality is executed. In various embodiments, the next cook can be corrected/adjusted to quickly produce the desired result, even based on poor quality recipes.

It will be appreciated that without following the instructions and attempting to cook with an incorrect recipe, good results may still be produced using the cooking appliance of the present application. In various embodiments, the user-generated recipe may include suggestions of recipes similar to the recipe input by the user, liked by most users, and/or liked by users having similar profiles to the user of the cooking appliance. The user interface may also analyze certain information about the user-generated recipes to suggest to the user how to create new recipe content, such as popular heating logic templates to base certain recipes or portions of recipes.

In various embodiments, the cooking appliance generates heat using a multi-spectral light-based heater. Such heaters are relatively sensitive to the geometry of the food product and various food product characteristics, such as heat capacity and moisture content specific to the food product. A full knowledge of the food product characteristics and location allows the heating algorithm to be adjusted to improve cooking. In some embodiments, the food height is determined, in part, using identifiers ("IDs") of the food and the food source. The food identifier may be associated with a meal kit, food brand, or other identifier that may be stored to track cooking characteristics of edible substances, allowing such characteristics to be incorporated into recipes and cooking algorithms. In one approach, an identifier of the meal kit or food source, such as a bar code, may be used to identify the desired food characteristics. The specific characteristics of the edible substance will then be associated with the cooking appliance, the user, or a database communicatively coupled to the cooking appliance. The specific food product characteristic may include an expiration date, a geometry, a height, a specific heat capacity, a weight, a surface infrared absorption characteristic, a moisture content, a recommended formula, and/or an image of the cooked food or plated form thereof or an image of the recommended formula.

When the user replaces food material, not only the characteristics of the food product are changed, but also the proximity of the food material to the heating element. If the cooking appliance does not know the food product selected by the user, the food product may be improperly cooked. By taking into account the height of the food product and other geometric factors, the cooking appliance may produce more accurate cooking results. However, the error rate of manually entered food product height profiles can be very high. In some embodiments, the height of the food item may be entered by using an automatic height measurement system such as LiDAR, stereo vision, and/or other techniques.

The cooking appliance may access the food product ID, which allows the cooking device to access the characteristics of the food. In some embodiments, if the food product identifier is unknown, the user may identify the known characteristic, which may include measuring the food product using a probe, imaging the food product, allowing the cooking appliance and/or online server to identify the food product or another food product having a similar characteristic. An associated heating algorithm may then be applied to the recipe based on the desired characteristics of the food product.

It should be understood that conventional ovens do not operate based on knowledge of the food being cooked as disclosed herein. Even if the food product is not optimally prepared or purchased, the user experience of the present disclosure will guide the user to achieve the desired result regardless of the cooking experience and food material. For example, brussels sprouts may be large, like a small fist, or as small as a thumb nail, and the desired heating algorithm will vary depending on the characteristics of the brussels sprouts used in the formula. In various embodiments, the cooking appliance knows the approximate size of the batch of brussels sprouts, and can brown slightly and cook the desired (or "best") taste of the brussels sprouts, depending on the recipe. In some embodiments, the cooking appliance may be adjusted to desired food product characteristics with or without the use of other advanced sensing systems (such as a camera) capable of determining the maturity of the brussels sprouts. The user does not always need to specify the type and average diameter of brussels sprouts (e.g., 0.7 inch), but may rely on information already present in the cooking appliance and related systems based on the food product at the point of sale and the identifier of the user's account.

In various embodiments, a priori knowledge about the food being cooked allows the cooking apparatus to more accurately estimate the cooking time. The energy required to bring the core temperature of the food product to the desired temperature may vary by several orders of magnitude depending on the surface to volume ratio of the food product. For example, thumb potatoes may have cooking times that vary widely from large potatoes, and heating methods that can be used to produce high quality meals may also vary widely.

For some foods, it may be difficult to create a unique ID that associates a particular food at the point of sale. For example, if a user is to purchase food from a grocery store, rather than from a web site, it may be difficult to obtain a food item identifier if the grocery store is not connected to a cooking appliance and/or user account. In those special cases, the system may use the user's credit card number or other unique identifier associated with the bill in conjunction with the list of items purchased and the time of purchase to allow the cooking appliance to determine the specific characteristics of the food product. For example, if a user purchases organic brussels sprouts, thumb potatoes, and purple corn at 10 am using the user's credit card, the association system may associate the credit card with the user's account and items purchased, which may have unique food identifiers.

In various embodiments, the cooking appliance may determine food product parameters based on the food product identifier, the date and location of purchase, and other available information. These food product parameters may include information such as geometry, moisture content, and recommended recipes for recently purchased food. The user interface allows the user to select a suggested recipe, select an existing recipe, or enter a new recipe. The recommended recipes presented to the user may be selected to prioritize the most recently purchased food materials and their associated recipes. The recommended recipes may be further prioritized by combining the user's preferences with the activity history, such as through statistical information or collaborative filtering. Prioritizing the food in this manner may allow the cooking appliance to significantly reduce scrolling and unnecessary and unpleasant user interface interactions. For example, a user may purchase Brussels sprouts from a grocery store to go home and then find a suggested Brussels sprouts related formula on a cooking device, which is selected based on previous formulas that the user likes. In this way, the user will not need to scroll through tens of pages of food to find the desired recipe.

The information obtained by the cooking appliance may also be provided to the grocery store or other point-of-sale operator to enhance grocery store logistics and purchasing decisions. For example, the cooking appliance may provide additional information about when and how to prepare and use different items, allowing the store to optimize its supply chain and reduce the number of items that must be kept because it knows the cumulative amount of food consumed by the user, presumably when, and which other food they are also consuming together. The online store may also use food consumption and formula preferences and feedback to suggest new formulas and foods to purchase. For example, if a user purchased steak and brussels sprouts, but only cooked the brussels sprouts, the online store may recommend the brussels sprouts (knowing that the user recently consumed the brussels sprouts, and there may still be steaks). This may help provide a more convenient user interface to the user for ordering food items and selecting recipes.

One way to alleviate the problem of manually inputting the height of the food item is to allow the user to compare the height of the food item with other reference objects and to display the same reference objects on the user interface so that the user can make an intuitive comparison between the reference objects and the height of the depiction of the food item in the user interface. There are many convenient reference objects and are shipped with the cooking device in question. For example, the temperature probe tip may be a relatively convenient reference object for measuring the height of the food product during preparation. Another possibility is the user interface display itself, which may have an image like a ruler for height measurement purposes. Another possible embodiment is to engrave or otherwise mark portions of the cooking chamber or tray such that the height or other unit of life is relatively apparent. The user may then enter the height of the food item to indicate the height by visually comparing or manipulating the marker relative to the reference object.

Fig. 5 is a block diagram illustrating an adaptive cooking appliance and user equipment according to various embodiments. In one embodiment, the cooking appliance may dynamically adjust the cooking logic during operation by analyzing images received from the camera. The cooking appliance may use the camera to determine several parameters before or during cooking of the food product, including but not limited to: geometry and thickness of the food product, surface texture changes, level of browning or burning, presence of burning, shrinkage, expansion or deformation of the food product, liquid leakage, presence of smoke, presence of steam, liquid boiling, or any combination thereof. The camera may also ensure safety by detecting unsafe events (such as smoke detection, fire detection, or the presence of extreme temperatures) that may trigger an alarm and turn off the oven.

Camera feedback control is useful for cooking methods where the cooking process follows an exponential or non-linear trajectory. For example, the darker the color of the food product, the greater the amount of heat the food product absorbs during browning. This is particularly evident during baking, which typically produces a nice brown color after 2 minutes, but 2 minutes and 30 seconds may scorch the bread. By stopping or adjusting the cooking process when an appropriate level of toasting is detected, real-time image analysis of the food product can be performed during cooking, so that the toasted bread can be perfectly browned each time. Additionally, for sequential cooking periods during which the cooking device has been pre-heated by a previous cooking period, camera controlled browning may be used to produce consistent results.

Furthermore, the 3-D geometry of the food may also be determined by the camera. For example, a 3-D image may be obtained by adding an additional camera (where 3D geometry can be determined using stereo vision) or by adding an additional structured light source such that a predetermined light pattern is projected onto the food, so that the 3-D structure of the food can be inferred by distortion of the light pattern.

It is also possible to use only a single camera to determine the food product geometry due to the well controlled cavity of the cooking device. However, for food products with little contrast or visible edges, determining an accurate 3-D structure using a single camera may be more challenging. In these cases, different light sources, different camera filters and sensors may be used simultaneously to improve the three-dimensional resolution. The 3-D geometry has a variety of uses: the cooking sequence may be optimized based on the thickness of the food in question. The 3-D geometry may also help generate a preview of the browning or burning session results.

In some embodiments, machine vision via one or more in-oven cameras may be used to improve the user experience. For example, the camera may be used to identify and correct visible errors in food preparation, cooking algorithms, and/or food placement. One common mistake is inserting the food product into the wrong tray rack. Different tray racks place the food product at different distances from the heating element, which can significantly affect the food being cooked. In some embodiments, one or more cameras image the interior of the cooking chamber from a fixed location including a food item placed within the oven, and determine a relationship between the tray and the oven interior to calculate the tray location. If the tray position is incorrect, the user may be notified through the user interface to correct the tray placement and/or to override the evaluation and continue the cooking algorithm through the algorithm.

In several embodiments, the cooking appliance may implement various mechanisms to facilitate the programming process of a developer directed to establishing a virtual heating recipe for the cooking appliance, where the virtual heating recipe includes the use of camera feedback control. The optical properties of the food product may be determined by a camera library and then the state of the food product is converted into an Application Programming Interface (API) that is easy to apply. In one example, control of burning or browning can be programmatically broken into 10 segments: zero is completely non-browning and 10 is turning black. The camera may use the initial shading of the food product to correct the browning scale to a zero value. Based on the type of food product, a browning level of 10 can be calculated. In operation, a user may specify a desired level of browning.

While cooking the food product, the camera may compare the initial browning level to the current browning level to calculate the currently present browning level. Additionally, the camera feedback library may further use the non-linear change to correct its browning level during cooking in the presence of the non-linear change. For example, in a food product in which the shell may be formed by baking, the formation of the shell may be corrected to level 7.

In another example, the presence of steam or bubbles emanating from the food product indicates that the surface temperature of the food product has reached 100 ℃. This information, in combination with the cooking device temperature, other optical information and timing mentioned above, can be used to model the internal temperature of the food product and/or the state of the cooking process.

Referring to fig. 5, the user device 540 runs a client application 542 that includes an interface to cooking appliance features, such as temperature and sensor information, and images of meals while cooking. This allows the user to view the meal in real time as well as diagnostic information about the cooking process.

According to various embodiments, the cooking appliance 500 may include a chamber 502 having a door 506. At least one cooking platform 510 is disposed within the chamber 502. The cooking platform 510 may be a tray, a rack, or any combination thereof. The chamber 502 may be lined with one or more heating elements 514 (e.g., heating element 514A, heating element 514B, etc., collectively "heating elements 514"). Each heating element 514 may comprise a wavelength-controllable filament assembly. The wavelength controllable filament assembly is capable of independently adjusting the emission frequency/wavelength, emission power, and/or emission signal pattern in response to commands from a computing device of the cooking appliance 500. In various embodiments, depending on the wavelength used, the wavelength options allow for various cooking modes (from shortest wavelength to longest wavelength) involving: direct mode (surface of edible substance), direct mode (internal cooking of edible substance), pan mode, oven mode. In one embodiment, two different wavelengths may be implemented, a first shorter wavelength for cooking the outer surface of the food product and a second longer wavelength for cooking the interior of the food product. Computer vision can be used to ensure the desired burn and probe technology can be used to track the desired internal temperature.

In several embodiments, the chamber 502 is windowless. That is, when the door 506 is closed, the chamber 502 including the door 506 is completely enclosed without any transparent (and/or translucent) portions. For example, when the door 506 is closed, the chamber 502 may be sealed within a metal housing, and one or more cameras, such as camera 518, may be arranged to image the interior of the chamber 502 during operation. In some implementations, the camera 518 is attached to the door 506. For example, as shown, the camera 518 may face inward toward the interior of the chamber 502 when the door 506 is closed, and may face upward when the door 506 is open. The camera 518 may be attached to the door 506 or adjacent (e.g., within three inches) the door 506, enabling easy cleaning, convenient scanning of labels, privacy, avoidance of thermal damage, etc.

In some embodiments, the heating element 514 includes one or more wavelength-controllable filament assemblies at one or more locations in the chamber. In some embodiments, each of the one or more wavelength-controllable filament assemblies is capable of independently adjusting its emission frequency (e.g., peak emission frequency) and/or its emission power. For example, the peak emission frequency of the wavelength controllable filament assembly can be tuned over a wide frequency band (e.g., from 20 terahertz to 500 terahertz). Different frequencies may correspond to different penetration depths of the heated food substance.

The heating elements can be controlled to have varying power by using similar fast switching Pulse Width Modulation (PWM) electronics, by having a relay-like control that can be turned on and off relatively quickly compared to the thermal inertia of the heating filament itself. The change in peak emission frequency may be directly related to the amount of power delivered into the heating element. The higher the power, the higher the peak transmit frequency. In some cases, cooking appliance 500 may maintain power constant by activating more heating elements, each with lower power, while reducing the peak emission frequency. Cooking appliance 500 may independently control the peak emission frequency of the filament assemblies and power them by driving them individually.

In some embodiments, using maximum power for each individual heating element to achieve the highest emission frequency is challenging because the AC power source may not be sufficient to provide power consumption (e.g., because it will blow a fuse). In some embodiments, this is addressed by driving each individual heating element in sequence at maximum power rather than driving them in parallel at reduced power. By combining sequential and parallel driving, an intermediate peak transmit frequency can be achieved.

In various embodiments, camera 518 includes an infrared sensor, cooking appliance 500 includes multiple cameras, and camera 518 includes a protective shell. In some embodiments, the heating element 514 and the camera 518 are disposed in the chamber 502 such that the camera 518 is not directly between any pair of heating elements. For example, the heating elements 514 may be disposed along two vertical walls perpendicular to the door 506. The heating element 514 may be a quartz tube (e.g., with heating filaments therein) extending horizontally on a vertical wall and perpendicular to the door 506.

In some embodiments, a display is provided, such as display 522 attached to door 506, or at another location, such as on the top of the oven. Display 522 may be a touch screen display. A display 522 may be attached to the exterior of the chamber 502 on the side of the door 506 opposite the camera 518. The display 522 may be configured to display real-time images or real-time video of the chamber interior captured by and/or streamed from the camera 518. In another embodiment, images from the camera 518 are streamed to the user device 540 over a wireless connection, such as Wi-Fi or bluetooth. In various embodiments, the repeated opening and closing of the door 506 during cooking allows heat to escape, thereby affecting the cooking time and reliability of the cooking algorithm. In addition to real-time progress status and feedback information as described herein, by providing real-time video of the chamber interior to the user during cooking, the user is discouraged from opening the door 506 (e.g., checking edible substances inside the chamber 502) during the cooking process, thereby facilitating reliable meal preparation results.

In one embodiment, the display presents a list of recipes, which may include a picture of the food item, the recipe name and the main food material, and an option to select a recipe by touching or clicking on each recipe. Options such as crispness, burning level and maturity may be selected for various recipes, or the cooking appliance may select options based on a constantly changing algorithm.

The user device 540 includes a display 542 that can be viewed from the oven, over a local area network, or through a recipe server on the internet, allowing the user to monitor the oven and issue commands to the oven from any location. In one embodiment, the user may adjust the recipe based on an image on the user's device. For example, if the food product is the desired shade of brown.

Fig. 6 is a flow diagram illustrating a method 600 of operating a cooking appliance (e.g., cooking appliance 500, cooking appliance 110, and/or cooking appliance 200) to cook a food substance utilizing camera feedback, according to various embodiments. The method 600 may be controlled by an adaptive cooking appliance (e.g., the adaptive cooking appliance 200).

At step 602, a user selects a recipe for use by a cooking appliance. In one embodiment, the cooking appliance presents one or more recipe options to the user, such as recipes from its local recipe library or recipes from a recipe library implemented by a cloud service accessible through a network interface (e.g., communication interface 240). At step 604, a camera (e.g., camera 518) internal to the cooking appliance may stream images of the food substance to a computing device and a display device, such as a display on an oven or one or more user devices. For example, the camera may be directed at a cooking platform (e.g., cooking platform 510) of the cooking appliance.

At step 606, when the cooking appliance receives the image, the cooking appliance may analyze the image to determine the status of the food substance, cooking chamber, or cooking platform. In some embodiments, the computing device may segment the image into portions corresponding to the food substance, portions corresponding to the cooking platform, and/or portions corresponding to the cooking chamber. From the segmentation of the image, the computing device may determine an independent state of the food substance, the cooking platform, and/or the cooking chamber. The state may be a known state (e.g., matching a set of possible states specific to a heating recipe or the whole to a general cooking operation of the cooking appliance) or an unknown state. In various embodiments, the status may be determined with or without the aid of other sensors.

In one example, recipes and cooking logic are generated for cooking steaks. The set of possible states specific to the steak recipe may include states corresponding to different burn levels. In another example, the formula is used to make popcorn. The set of possible states specific to the popcorn making recipe can include states corresponding to an un-popped state, a popped state, and a fully popped state. In yet another example, the formula is used to cook eggs. The set of possible states specific to the recipe of the boiled eggs may include a water boiled state and a water not boiled state. In another example, a heating recipe is used to bake bread to a desired shade of brown. The global state may include a smoke alarm state (e.g., when smoke is present within the cooking chamber) or a fire alarm state (e.g., when fire or burning food substances are present within the cooking chamber). The unknown state is an image that deviates from all known states, making it so unusual that the computing device will stop operation of the cooking appliance or at least alert the user.

At step 608, the user device provides feedback to the computing device, which may include instructions for modifying the cooking algorithm, overriding the current settings, or setting additional preferences for the heating process.

At step 610, the computing device may reconfigure a heating element or other physical component of the cooking appliance in response to a change in state of the food substance, the cooking chamber, and/or the cooking platform. For example, the reconfiguration may include turning off the heating elements, changing a peak emission frequency of one or more heating elements, changing an intensity of one or more heating elements, controlling the cooling system, sending a natural language or media message via a network interface (e.g., communication interface 240), displaying a message on a display (e.g., display 522 or a display on a user device), or any combination thereof.

At step 612, the computing device may store the history of state changes of the food substance, the cooking chamber, and/or the cooking platform in a local memory (e.g., memory 240). In some embodiments, at step 614, the computing device may generate a media file (e.g., a visual image or video) showing the progress of the heating recipe from the state change history and provide feedback to the recipe server or stored locally for the user. The user preferences may then be modified based on the user feedback.

Fig. 7 is a flow diagram illustrating a method 700 of operating a cooking appliance (e.g., cooking appliance 500, cooking appliance 110, and/or cooking appliance 200) to uniformly cook an edible substance according to various embodiments. At step 702, the cooking appliance may identify a food product profile for the edible substance from a database. For example, the cooking appliance may identify the food product profile by scanning (e.g., optically scanning or near-field based) the packaging of the edible substance before starting to heat (e.g., burn and/or toast) the edible substance. For another example, the cooking appliance may identify the food product profile by receiving a user indication of the food product profile via the interactive user interface. The interactive user interface may be implemented on a touch screen of the cooking appliance. The interactive user interface may be implemented on a mobile device (e.g., a smartphone or electronic tablet) having a network connection with the cooking appliance.

In other embodiments, recipes and cooking logic may be automatically obtained on the cooking appliance through a subscription or vendor relationship that also tracks cooking experience and adapts it to user-specific information, as disclosed herein. For example, a user may order a meal kit and deliver it to a location associated with a cooking appliance. The vendor may track the delivery and instruct the recipe server to push the recipe to the cooking device when the meal kit is received. Alternatively, the user may purchase groceries and the associated recipe may be presented to the user for availability on the cooking appliance. In another embodiment, the user selects a recipe, executes a grocery delivery order, and downloads the recipe and cooking logic to the oven while delivering groceries. In another embodiment, the recipe in the cooking appliance is tracked by a smart device in the home and adjusted to show only recipes with food materials available.

At step 704, the cooking engine instantiates (e.g., via a processor or controller) cooking logic including a heat adjustment algorithm based on a recipe selected from a database. For example, the cooking appliance may identify one or more recipes associated with the food product profile and display the recipes for selection by the user. The computing device may then receive a user selection of at least one recipe. The computing device may instantiate corresponding cooking logic including a heat adjustment algorithm based on the selected recipe. In one example, the selected recipe includes a burning step.

At step 706, the cooking appliance may monitor a surface of the edible substance in the cooking chamber via the camera. The user receiving the image via the user device may also monitor cooking and provide feedback when needed at step 708.

At step 710, the cooking appliance may burn the edible substance with camera feedback control based on monitoring of the surface of the edible substance by the cooking engine and a user of the user device via at least a first heating element controlled by the computing device. For example, the computing device may set the cooking appliance to burn by adjusting the peak emission wavelength of the first heating element. For example, a heating concentration of a longer peak emission wavelength may penetrate more through the edible substance. Thus, when burned, the computing device may shorten the peak emission wavelength of the heating element. When burning, a high frequency and shorter peak emission wavelength is used. The radiant heat transfer efficiency during the burning operation may be more than 20 times the radiant heat transfer efficiency of an oven operated at conventional filament temperatures (e.g., a conventional nichrome oven). With this much higher radiant heat transfer efficiency, various portions of the edible substance may never reach an equilibrium heat balance (e.g., radiant heat is added to the surface of the edible substance at a faster rate than the rate of thermal heat conduction into the edible substance). Thus, the inner portion of the edible substance may not fully act as a heat sink for the surface of the edible substance. Thus, when burning the surface of the edible substance, the inner portion of the edible substance is also toasted.

At step 712, the cooking appliance may determine the temperature at the depth center and/or multiple points of the edible substance via a multi-point temperature probe in communication with the computing device. At step 714, the cooking appliance may toast the edible substance in the cooking chamber via at least a second heating element controlled by the cooking appliance after the burning step is completed (e.g., according to camera feedback). The first heating element and the second heating element may be the same heating element or different heating elements. Each heating element may include one or more filament assemblies capable of adjusting its peak emission wavelength. For example, the cooking engine may set the cooking appliance to toast by adjusting the peak emission wavelength of the second heating element.

When toasting, the cooking engine may configure the peak emission wavelength of the second heating element to correspond with a penetration depth through the edible substance to a determined depth center. The cooking engine may scale the peak emission wavelength to a level corresponding to the penetration depth. The food product profile identified in step 702 may specify a depth adjustment function. The depth adjustment function may map the penetration depth to a peak emission wavelength. Thus, the computing device may scale the peak emission wavelength to correspond to the penetration depth according to the food profile/depth adjustment function.

When baking and burning, the cooking engine may operate the heating element differently. In some embodiments, when toasting, the cooking engine drives (e.g., sends control commands to the driver) the filament assembly of the second heating element to emit at a longer peak emission wavelength (e.g., a lower peak emission frequency) than when burning the edible substance. In some embodiments, when baking, the cooking engine drives the filament assembly of the second heating element at a higher power than when burning the edible substance. Compared with the burning time, the peak luminous wavelength is longer, the radiation power is lower, and the radiation heat transfer efficiency is lower. This enables the toasting operation to cook the interior of the edible substance without affecting the surface of the edible substance. This may be due, in part, to the edible substance equilibrating faster because the surface heat of the edible substance is quickly conducted to the center of the edible substance, for example.

While toasting, the computing device may adjust the power driving the heating element (e.g., the second heating element) based on temperature feedback control from a temperature probe inserted into the edible substance. The temperature probe may be in communication with the cooking engine. For example, the cooking engine may monitor temperature readings from the temperature probe via a wired connection to the temperature probe, a Radio Frequency (RF) wireless connection, or a near field inductive or capacitive coupling connection.

In various embodiments of method 700, the cooking appliance burns (e.g., with a powerful surface cooking) prior to baking. For example, baking is performed with less power. In some embodiments, there are three (see, e.g., screen 487 in fig. 4F) or four large cooking zones with multiple heating elements in a multi-zone cooking environment. Due to power limitations, it may be impractical to use all heating elements at maximum power or shortest wavelength on a fire. For example, the cooking appliance may have three heating elements on a top portion of its internal chamber. The cooking appliance may have the heating element run continuously on the top portion (e.g., to overcome power limitations). When baking, the cooking appliance may sequentially drive the heating elements at lower power, or operate all heating elements or all top portion heating elements simultaneously, all having lower filament temperatures and longer wavelengths than when burning.

Generally, driving the heating element to emit longer wavelengths causes the emitted power to penetrate deeper into the food product. However, the thermal gradient of the food product may also contribute to the penetration. Too high a surface temperature can result in a relatively sharp temperature gradient from the surface of the food product to the center of the food product. The relatively low temperature allows all sides of the food to be heated uniformly, similar to radiant heat causing a lower/smoother temperature gradient.

In various embodiments, the recipe server and compiler are designed to increase the cooking speed of various food products. In one embodiment, the cooking ranges and heating algorithms are developed at the front end for food product characteristics and other recipe components. The cooking range of each component may be adjusted according to the user's desired result, such as speed or optimal flavor. For any recipe, the food material includes food characteristics, food type and typical cooking parameters. The recipe can be compared to similar recipes and modified to speed cooking, which can include food preparation (such as cut meat portion size) and heating profile algorithms to adjust cooking time. A user configurable parameter may be selected to adjust the factors to be considered in selecting the quick cook option. In one embodiment, the recipe input is modified according to a known food classification and is further provided as an input to a heating algorithm.

An exemplary embodiment of the recipe generation process is shown in FIG. 8. As shown, a recipe database 804 including food product characteristics and cooking logic may be used as a knowledge base for use in artificial intelligence or machine learning systems for converting recipes into cooking appliance specific cooking logic, including heating algorithms and food preparation parameters. In one embodiment, the new recipe may be input to the recipe generator 800 to produce an optimized output recipe and cooking logic for the oven, including a heating algorithm. Through a machine learning system, recipes and cooking logic can be generated that are optimized for cooking speed and efficiency while maintaining simplicity and flavor. In one embodiment, the recipe and cooking logic are implemented and run in a controlled cooking appliance having controlled ingredients. Various dishes were tested in the cooking appliance using different combinations of ingredients and preparations cooking recipes, and the results were tracked in database 804. The system may then adjust the recipe and cooking logic to speed up the cooking process, adjust the heating model or sensor information, and provide logic for dynamic control.

In one embodiment, a conventional recipe is provided to a recipe server. The recipe is parsed into a series of high level instructions that can be translated into cooking elements and heating algorithms. These high level instructions include commands for controlling the cooking appliance (set temperature, set timer), monitoring sensors such as probes, cameras and timers. Also included in the instructions is analytical information for detecting future events, such as images showing appropriate edible substance profiles, for adjusting the timers for heating and cooling. In one embodiment, the recipe is transformed into cooking appliance instructions. Recipes can be constructed based on cooking appliance data such as optimal food material, sensor monitoring, food preparation, and heating adjustments.

A quick cooking recipe may also be constructed based on stored user data to speed up timing. After following the recipe, the user may provide additional feedback and adjustments to the recipe. The cooking appliance may also provide user specific information that is automatically adjusted and learned during cooking (e.g., based on sensor feedback and camera image analysis), as previously discussed herein. In one embodiment, the user selects from a set of options, such as under-cooking and over-cooking, and adjusts the recipe for future use. In one embodiment, a recipe may be stored, including sensor and image information. User recipes are added to the recipe database and may affect other generated recipes depending on factors such as area, food materials, user profiles, user feedback, and user preferences. For example, a user experience with preferences for food materials or regions of certain sources may result in a recipe changing (e.g., if a recipe executed with a particular source of food material is often overcooked, the heating algorithms for other recipes using that source food material may be adjusted accordingly). In another embodiment, the recipe may change the recipe for the user based on factors such as the user's history of incorrect food material selections and preparations, incorrect food material measurements, common user errors, and/or user preferences. The feedback is used to modify and optimize the recipe for the user (e.g., if the user always cuts the protein to a greater thickness than expected, the heating algorithm can be adjusted to apply glow power to the protein in a shorter time than expected). In one embodiment, the user is recommended recipes from other users with similar user profiles, feedback, and experience. The next recipe is used to generate cooking logic that can be downloaded to the cooking appliance and modified by the user as desired. In one embodiment, the user may modify the recipe on the oven, on the user device, or through the recipe server.

In one embodiment, each recipe includes a thermal script. The recipe server performs thermal modeling of various food characteristics and recipes. Thermal modeling includes timing and sensor based temperature adjustment. The timing, temperature sensor readings are tracked during the cooking process. After cooking, the tracked information is compared to the user feedback information and the initial model. In this way, the user or oven adjusted model can be used the next time the user runs the same recipe. In one implementation, the user is prompted whether to use the adjusted model, the initial model, or make further adjustments to the model. In one embodiment, the adjustments are made automatically in the background, thereby providing the user with the optimal recipe and thermal model each time.

In one embodiment, the cooking appliance allows for user generated recipes. The user may create a new recipe for the oven, for example, from scratch, from a recipe in another medium, or by modifying a recipe received from a cloud recipe store. The recipe can be compared to stored recipes in terms of similar dishes, food materials, thermal models, sensor data and timing information, and user feedback, and transformed into a user-generated recipe for the adaptive cooking appliance. The user may then use the recipe through the oven, client application, or recipe server as desired. In one embodiment, the recipe on the user device may be sent to the cooking appliance over a wireless connection. The oven may then compile the recipe into cooking appliance commands to cook. In one embodiment, the oven includes a recipe compiler for providing basic recipe adjustments. In various embodiments, the cooking appliance may include a "main kitchen mode" to provide the user with detailed control over recipe generation and cooking appliance operation (e.g., to allow selection of emission wavelengths from heating elements or to control allocation of available power resources during cooking).

As previously discussed herein, the user-generated recipe may be further adjusted based on user feedback and other user-specific information collected during execution of the recipe, which may be updated each time the user executes the recipe. For example, after cooking the edible substance according to a user-generated recipe, the user may be prompted for feedback as to whether the user likes the results ("do you like the meal. In one embodiment, an undesirable formulation (as determined by user feedback) may be removed from the formulation storage device, for example, by prompting the user whether it is desired to ameliorate or remove the undesirable formulation.

In other embodiments, the cooking appliance may track various parameters, such as heat and sensor data and user interaction during preparation and execution of the recipe, before, during, and after cooking. For example, the temperature and timing are tracked, as well as the frequency of opening the door of the cooking appliance to check the food product, the frequency of user interaction with the oven or user interface of the user device, the frequency of viewing the edible substance on the application and any user adjustments made during execution of the recipe, and any other user feedback provided after cooking. The cooking appliance events and the user events may be used to update the recipe. In various embodiments, user-generated conventional recipes, including recipes for data received during cooking, adjustments and interactions or feedback from the user, are compiled into heating algorithms and cooking appliance commands for various cooking modes. For example, the cooking appliance may determine low stress and high speed cooking options for each recipe. The low stress and high speed self-managed recipes can be compiled using known food product characteristics and cooking models (e.g., as stored in the food product characteristics and recipe database 316 of fig. 3) that include a range of acceptable cooking parameters, including cooking temperature, time, sensors, and probe and image data for proper cooking in each available cooking mode. When cooking a meal, the user may be prompted by the user interface to cook an offer for the recipe using a low stress or high speed cooking mode.

Fig. 9 is a flow diagram illustrating a method 900 of operating a cooking appliance (e.g., cooking appliance 100, cooking appliance 200, cooking appliance 300, and/or cooking appliance 500A) to cook edible substances in different modes according to various embodiments. At step 902, a computing device of a cooking appliance may be configured to execute a heat adjustment algorithm/process based on a recipe specifying drive logic for operating one or more heating elements of the cooking appliance.

For example, the cooking logic may specify which heating element to turn on (e.g., control the directionality of the heating). For example, the recipe may instruct to turn on the heating element below the tray and turn off the heating element above the tray. In this example, the cooking appliance may simulate a stove top. In another example, each heating element may be independently driven (e.g., a heating element located at a front top position may be driven independently from a heating element located at a rear top position). The cooking appliance may heat the edible substance in a number of ways. The cooking appliance may be configured to directly heat the edible substance. The cooking appliance may be configured to heat its internal chamber (e.g., its chamber wall and its tray) and let radiant heat from its internal chamber heat the edible substance. The cooking appliance may be configured to heat the interior chamber and the edible substance simultaneously. The heated air in the interior chamber may also heat the edible substance. The cooking appliance may be further configured to provide the heated air flow to cook the food item as an impingement convection oven. At lower airflow rates, the cooking appliance may be configured as a conventional convection oven.

Because items within the cooking appliance (e.g., edible substance, air, chamber walls, and trays) may each have one or more excitable wavelengths, by controlling the peak emission wavelength of the heating element, the computing device may heat specifically for different items. Because the item may have multiple excitable wavelengths, the computing device may select different peak emission wavelengths to control the cooking speed/efficiency provided by the heating element.

At step 904, the computing device may configure the thermal adjustment algorithm to operate according to a low stress mode or a high speed mode. In one embodiment, the available cooking profiles are presented to the user through a user interface (e.g., user interface component 250 of fig. 2). An exemplary user interface is shown in fig. 14B, in which the user is prompted to select a low stress mode (e.g., comfort mode) or a high speed mode. In some embodiments, the user may be provided with additional information regarding the differences between available cooking modes, including the total cooking time and the assessed time range in which the user desires to remove the edible substance from the cooking appliance.

In some embodiments, the low stress cooking mode is configured with various protective measures to prevent overcooking, such as by configuring the heating algorithm to turn off before overcooking, adaptively adjusting cooking in response to a feedback control signal to prevent overcooking, configuring the cooking algorithm to have a relatively long time window during which a user may remove edible substances from the cooking appliance, and providing a user completion indicator and other feedback to the user to prompt removal of edible substances from the cooking appliance.

In conventional cooking methods, the internal temperature of the food product typically continues to rise after the food product is removed from the cooking device (as heat continues to flow within the food product). It is often desirable to "rest" the food product outside the cooking device for a period of time before the food product reaches a desired internal temperature (desired degree of maturity) at which the user can cut the food product. In the "high speed" cooking mode, more energy is applied to the food product for a short period of time to speed cooking, which results in the food product continuing to heat after it is removed from the oven (faster than food products cooked using conventional cooking methods). In the "low stress" mode, cooking may proceed more slowly than in the high speed mode (but may still be faster than conventional cooking methods), and includes strategically applying different amounts of energy at various points of cooking to ensure that when the food product is removed from the oven, the internal temperature approaches the desired level of doneness, after which the temperature rises relatively slowly. This results in a longer time after cooking when the user can cut the food product and bring it to the desired internal temperature (desired degree of maturity).

At step 906, the computing device may monitor one or more feedback control signals from one or more sensors of the cooking appliance. For example, the feedback control signal may include a temperature reading signal from a temperature probe, a feedback signal from a camera, or a combination thereof.

At step 908, the computing device may drive one or more heating elements to cook the edible substance based on the recipe and whether the recipe is configured to operate in a low stress mode or a high speed mode. In some embodiments, the computing device may further drive the one or more heating elements based on the feedback control signal. In some embodiments, the computing device may calculate when cooking is complete and turn off the projection of the heating element (e.g., heating trajectory). In some embodiments, control of the heating element is dynamic (e.g., based on feedback control signals from the temperature probe or from the camera), and thus the completion time is not known.

At step 910, the computing device may turn off power to the heating element. At step 912, the computing device may determine when to present a completion indicator for the thermal adjustment algorithm according to whether the recipe is configured in a low stress mode or a high speed mode. In some embodiments, the computing device may determine when to present the completion indicator based on the feedback control signal (e.g., "visually" burn completion from the optical sensor or for a certain period of time when the edible substance reaches a certain temperature).

The high-speed cooking process may include extracting edible substances from the cooking appliance when the completion indicator is presented (e.g., the edible substances would otherwise be overcooked). The low stress mode allows extraction to occur within a preset time frame (e.g., from immediately to within 30 minutes, or from immediately to within two to three hours). In various embodiments, the completion indicator is presented to the user through a user interface of the cooking appliance (e.g., user interface component 250 of fig. 2) or through a user interface on a user device (e.g., user device 280 of fig. 2). An exemplary completion indication message is shown in fig. 14B, including an instruction to remove edible substance to rest at a particular time, an indication that the food product is cooked complete, and a time until the edible substance is overcooked.

Various embodiments of systems and processes for implementing shelf control will now be described. Because the cooking appliance manages the entire cooking, a food product (typically protein) rest guidance system and method is implemented. In operation, the cooking appliance will indicate that cooking (and all heating) has ended and will use additional time to rest the food product so that the food product achieves a higher quality finish and correct maturity. In other embodiments, the heating system may be completely turned off, and the food item may begin and continue to rest in the cooking appliance without indicating that the food item is resting. In these embodiments, there may only be an indication that the user needs to cut the food product for a particular period of time (and the indication may occur at any time, including when the heating system is activated). In one embodiment, the protein may be allowed to sit for 5 minutes in order to relax the protein fiber and absorb some of the water lost during cooking. With light-based heating elements, improvements in efficiency and health delivery increase the cooking balance in some cases. For example, it is not uncommon to see a balance cook of about 15 ° as compared to a conventional oven, which may rise by 5 ° under similar cooking conditions.

In some embodiments, the cooking appliance is configured to make a first indication that cooking has stopped. The indication to the user may include an audible signal, a visual cue, a vibration-based notification, or other method of notifying the user. The cooking appliance is further configured to generate a second indication to the user indicating that the shelving is complete.

In some embodiments, a progress indicator, such as a graphical indicator or countdown timer (e.g., as shown in fig. 14B), displays the current status of the meal and the time remaining to the user. Additional calculation algorithms may be involved which take into account the history of food cooking to calculate the amount of time required for shelving. In other embodiments, the cooking history is used to calculate the cutoff temperature and time so that the user always experiences the same number of resting minutes. For example, by accurately calculating when all heating devices are turned off, the cooking appliance can lock the shelf time within exactly 3 minutes.

In some embodiments, in the high-speed mode, the cooking appliance may present a completion indicator when the computing device turns off power to the heating element. In some embodiments, in the low stress mode, the computing device may present the completion indicator for a certain time after the computing device turns off power to the heating element. For example, after the power of the heating element is turned off, the tray and/or the chamber walls of the cooking appliance remain as a radiant heat source. The inside air is still at a high temperature. In the low stress mode, the computing device may use a computer model to simulate radiant heat and hot air to calculate a heating trajectory for the edible substance. Once the heating trajectory reaches a point sufficient to dissipate the radiant heat and the hot air has cooled such that the edible substance is not overcooked or spoiled even if it remains within the chamber for a time within the preset range, the computing device may present a completion indicator.

In some embodiments, the formulation is provided using variable stress cooking. In one embodiment, a low stress formulation is provided to produce a safety result with less monitoring. The design of the low stress formulation is easy to prepare for various users and requires less maintenance and monitoring to produce consistent results. In one embodiment, low stress cooking will adjust the heating algorithm to turn off after cooking and allow the food product to remain in the oven. Using a low stress formulation, the oven will be configured not to overcook the food product. The fast cook option provides for fast cooking, but may be affected by a greater degree of human error. For example, in one embodiment, the high speed mode may require the user to remove the food product after cooking to reduce the risk of overcooking. High-speed cooking may include more reliance on sensors (such as probes, temperature sensors, optical cameras, and thermal imagers) and data analysis during the cooking process. The recipe can be adjusted for each mode, including thermal models, thermal trajectory models, and sensor and timing models.

A computing device such as a cooking engine may be configured to control the peak emission wavelength of a filament assembly or other heating element. For example, the computing device may be configured to identify a food profile associated with the edible substance from a database and determine one or more excitable wavelengths associated with the food profile. The computing device may be configured to emit at a peak emission wavelength corresponding to at least one of the excitable wavelengths to heat the edible substance.

In some embodiments, the cooking appliance may be configured for side-by-side cooking of two or more different edible substances, such as by controlling a heating element that includes a shield for certain portions of the cooking appliance. For example, the cooking appliance may independently control the heating elements above/below the first cooking zone and above/below the second cooking zone. This enables some control over side-by-side cooking in addition to direct radiant heating. Multi-zone cooking is also contemplated in the present disclosure and may be optimized by the same methods as described above. Zone cooking techniques allow for different food products to be cooked simultaneously even though they require different temperatures and times. In other embodiments, the heating elements may be controlled for dual-level cooking, so that different food items may be cooked simultaneously on multiple oven levels, even if different temperatures and times are required.

Fig. 10 is a block diagram of a recipe server system 1000 implementing a cloud-based recipe storage system, according to various embodiments. The server system 1000 may include a recipe repository 1002, a recipe distribution interface 1004, a recipe design interface 1006, a recipe execution simulator 1010, a food profile database 1014, an instrument profile repository 1016, a meal suite profile database 1018, a template database 1022, or any combination thereof. The recipe store 1002 stores one or more recipes. Each recipe may include one or more heat logic algorithms (e.g., a heat adjustment algorithm). The recipe distribution interface 1004 may present and provide the contents of the recipe store 1002 for download by an external device via a network interface or Application Programming Interface (API). For example, the recipe distribution interface 1004 may be accessible to a cooking appliance (e.g., cooking appliance 110) via a wide area network such as the internet. In at least one example, a user may download a recipe and associated cooking logic onto a mobile device and then transmit the recipe and cooking logic to a cooking appliance. In at least one example, a user of the cooking appliance may download the recipe and cooking logic directly into the cooking appliance.

In various embodiments, the server system 1000 provides a recipe design interface 1006 to facilitate the design of recipes in the recipe repository 1002. When designing a recipe, a recipe designer may access the template database 1022 to copy the recipe template or cooking logic template into the recipe. The server system 1000 may provide a recipe execution simulator 1010 to simulate a recipe from a recipe designer. The server system 1000 can generate one or more visual effects (e.g., videos, charts, graphics, combinations thereof, etc.) to depict transitions of food objects corresponding to the recipe. The server system 1000 may present the analog transformation represented by the visual representation via the recipe design interface 1006. The simulation may result in a visual simulation and/or a temperature gradient simulation. The simulation may access a food profile database 1014 to determine how a unit amount of a target food product (e.g., referred to as a "food target") visually transitions in response to ambient or internal temperature changes. Food profile database 1014 may also specify heat capacity and conductance characteristics per unit quantity of the target food to facilitate the simulation. The recipe execution simulator 1010 may thus provide feedback to the recipe designer to ensure that the recipe can work as intended in the cooking appliance.

The instrument profile repository 1016 may store specifications for multiple versions or embodiments of the disclosed cooking appliance. In some embodiments, the designer may select from the instrument profile repository 1016 to determine which version/embodiment of the disclosed cooking appliance may work with the specified cooking logic. In some embodiments, the recipe execution simulator 1010 may run a simulation based on one of the versions/embodiments in the instrument profile repository 1016.

The meal kit profile database 1018 may store package identifiers for one or more known meal kits/food packages. In some embodiments, the logic of the recipe may reference one or more of the package identifiers. This allows the designer to specify changes to the strategy/logic based on the identification of the package identifier by the cooking device. In various embodiments, the database may include more detailed information about the meal kit, including physical characteristics (height/weight/size), exact food type (e.g., fish), food source (e.g., source pasture of beef), and the like.

In various embodiments, the heating logic may include timing and monitoring of cooking, including monitoring heat, cooking time, probes and sensors, and camera feedback. The heating logic will include the desired heat/time profile and sensor readings. The heating logic may also include events such as temperature of the probe, cooking time, or detection by optical image analysis to further adjust the heating algorithm for the next stage of cooking.

Fig. 11 is a control flow diagram illustrating an example of a recipe 1100 according to various embodiments. Recipe 1100 can be a set of instructions (e.g., electronic and/or computer readable instructions) suitable for configuring a cooking appliance to process a target food product type. In various embodiments, the recipe may be configured to provide instructions for cooking multiple items in different zones, for cooking multiple items on different trays, for acceleration of traditional cooking, meal kit recipes, or for other cooking options.

A cooking appliance (e.g., cooking appliance 110) may download a recipe 1100 from a server system (e.g., server system 1000) and execute cooking logic. Recipe 1100 can include cooking logic (e.g., a heat adjustment algorithm) and instructions for configuring the cooking logic. For example, at step 1102, the cooking appliance may initialize recipe 1100. At step 1106, the cooking appliance determines whether it identifies a meal kit (e.g., the cooking appliance may scan the package identifier with its camera or prompt the user of the cooking appliance to enter the package identifier). At step 1110, in response to identifying a meal kit (e.g., a package corresponding to an entry in the meal kit profile database 1118), the cooking appliance configures a set of cooking logic preset parameters corresponding to the identified package identifier. For example, the cooking appliance may access (e.g., locally or over a network) a meal kit profile database to identify a corresponding set of cooking logic preset parameters. In this example, the cooking appliance may proceed to step 1114 regardless of whether a meal kit is identified.

In other embodiments, the cooking appliance may be configured to identify other cooking conditions, such as multi-zone cooking, accelerated cooking, multi-level cooking, and multi-tray cooking.

At step 1114, the cooking appliance selects the operating mode that the user of the cooking appliance prefers and makes other user-specific adjustments as appropriate. For example, the cooking appliance may prompt the user to enter a mode selection via their touch screen, their one or more buttons, or a mobile device connected to the cooking appliance. At step 1118, in response to selecting the first mode (e.g., low stress mode), the cooking appliance may prompt (e.g., a user) and receive cooking logic user parameters related to the first mode. Similarly, at step 1122, in response to selecting the second mode (e.g., high speed mode), the cooking appliance may prompt and receive cooking logic user parameters related to the second mode. When the first mode is selected, the cooking appliance may execute cooking logic, including the heat adjustment algorithm/heating logic (e.g., referred to as "heating logic a") of the recipe 1100 associated with the first mode at step 1126. When the second mode is selected, the cooking appliance may execute cooking logic, including the heat adjustment algorithm/heating logic (e.g., referred to as "heating logic B") of the recipe 1100 associated with the second mode at step 1130.

The cooking logic parameters may be a function of the cooking logic user parameters specified in step 1118, the cooking logic preset parameters (if any) at step 1110, one or more sensor feeds, a timer, one or more user signals, or any combination thereof. Similarly, the additional cooking logic parameters may be a function of the cooking logic user parameter specified in step 1122, the cooking logic reset parameter (if any) at step 1110, one or more sensor feeds, a timer, one or more user signals, or any combination thereof.

In some embodiments, the state machine may represent a heating logic sequence. For example, a recipe may include a plurality of cooking logic sequences. At least some of the cooking logic sequences may be alternatives to each other. For example, the recipe 1300 may indicate a basic setting of a state machine. The state machine may further be configured by cooking logic preset parameters and/or cooking logic user parameters. Based on these settings, the state machine may configure the components of the cooking appliance differently according to the current operating state. For example, the state machine may specify a heating element configuration (e.g., of one or more heating elements) based on the current operating state. The sensor feed, timer and/or user signal of the cooking appliance may be input signals of a state machine. The cooking logic sequence may indicate whether a change in the input signal may change the current operating state. The recipe 1100 can specify a heating element configuration (e.g., of one or more heating elements) based on the current operating state. In some embodiments, one of the states is a termination state. Once the termination state is reached, the cooking appliance may notify the user (e.g., via an output component) that the contents in the cooking appliance are ready. When designing a recipe, the designer may block access to any of the steps described above. For example, the designer may skip step 1114 and force the cooking appliance to operate only in a low stress mode or only in a high speed mode.

Fig. 12 is a flow diagram illustrating a method 1200 of operating a server system (e.g., server system 1000) that implements cloud-based recipe storage, according to various embodiments. At step 1202, the server system may generate a recipe design interface (e.g., recipe design interface 1006) configured to facilitate design of a recipe for deployment in a cooking appliance (e.g., cooking appliance 110). In various embodiments, the recipe design interface may be implemented on the cooking appliance itself through a "master kitchen mode" interface for creating user-generated recipes. In some embodiments, the recipe design interface has an Integrated Developer Environment (IDE) for inputting cooking logic. The IDE may enforce a format convention to specify cooking logic. The recipe design interface may provide access to a recipe execution simulator (e.g., the recipe execution simulator 1010). The recipe execution simulator can calculate a simulation of the recipe against a known food profile (e.g., from the food profile database 1014). For example, the simulation may include a visual depiction (e.g., a chart or graph) of a food object and/or a visual depiction of the temperature progression of a food object or part of the cooking appliance that is transformed according to the cooking logic. The recipe execution simulator may then present the simulation via the recipe design interface. Known food profiles may specify how a food target is visually transformed in response to environmental or internal temperature changes, as well as the thermal capacity and electrical conductance characteristics per unit quantity of the food target.

The recipe design interface may provide access to one or more cooking logic templates (e.g., in template database 1022). The cooking logic template may be configured as a cooking logic. The cooking logic template may be inheritable. For example, when the cooking logic inherits from a cooking logic template, the cooking logic template may be used as a basis for the cooking logic that prompts the designer to fill in the required subroutines of the cooking logic template. For example, a cooking logic template may provide the basic logic for simulating a conventional cooking appliance (e.g., a stove, grill, nichrome oven, etc.) and allow a designer to specify parameters for the conventional cooking appliance. The cooking logic template may then translate the parameters for the conventional cooking appliance into a heating element configuration of one of the disclosed cooking appliances (e.g., cooking appliance 110). A cooking logic template may be imported into the cooking logic as a subroutine of the cooking logic.

At step 1204, the server system may receive one or more configuration parameters for the recipe via a recipe design interface. The recipe may include one or more cooking logic sequences. For example, the cooking logic sequence may be represented as a state machine (e.g., a deterministic finite automaton or workflow). The state machine may be defined by at least an initial state, a completion state, a state transition function, an output function, a set of input symbols (e.g., possible inputs), and a set of output symbols (e.g., possible outputs). In one example, the input may be a sensor feed value within a preset range. In another example, the output may be a filament driver parameter associated with the heating element for configuring the heating element after transitioning to a particular operating state.

The configuration parameters may include the available states in the state machine. The configuration parameters may include user instructions associated with the state. The user instructions are configured to be displayed in the cooking appliance or a mobile device connected to the cooking appliance. The configuration parameters may include a heating element configuration associated with the state. In some examples, the heating element configuration is specified as a filament driver parameter (e.g., wavelength, amplitude, signal pattern, power, duty cycle, etc.) and a heating element selection (e.g., which heating element to use). In some examples, the heating element configuration is specified as a target temperature, a target spatial region (e.g., a cooking depth and position relative to a chamber of a cooking appliance), a target material (e.g., food, a tray, a chamber wall, a perforated plate, or air), an instrument simulation mode, or any combination thereof.

The configuration parameters may also specify state change conditions associated with the state. The state change condition is a conditional trigger that specifies when to change the current operating state and which state to change to. The state change condition may be a function of one or more sensor feeds, one or more timers, one or more user signals, or any combination thereof. For example, the sensor feed may include a temperature probe inserted into the food item target, a temperature sensor in the cooking appliance, a camera in the cooking appliance, or any combination thereof. The user signal may come from a mobile device connected to the cooking appliance, an input button of the cooking appliance, a touch screen of the cooking appliance, other input components of the cooking appliance, or any combination thereof.

In some embodiments, the server system may cross-check the configuration parameters entered by the recipe designer for errors. For example, the server system may detect (e.g., through simulation or pattern recognition of known problem logic) a possible error or hazard associated with the recipe or heating logic. The server system may then present the possible errors or hazards via a recipe design interface to notify the recipe designer.

In various embodiments, the configuration parameters may be pre-populated with parameters from existing recipes stored in a database, thereby allowing a user to modify existing recipes available to the cooking appliance, including recipes generated by other users. For example, a user may identify another user's recipe, and the server system may import parameters into the recipe design interface and then configure the recipe as needed to alter the ingredients, preparation instructions, cooking modes, time and temperature, and other recipe parameters.

At step 1206, the server system may publish the recipe to an online store (e.g., a recipe store). In some embodiments, the server system provides pattern control of the recipe. In these embodiments, the server system may maintain multiple versions of the recipe (e.g., at least some of these versions are published). After the recipe is published, at step 1208, the server system may present the recipe in a Graphical User Interface (GUI) of the online store (e.g., the recipe distribution interface 1004) for distribution to one or more cooking appliances or one or more mobile devices. Each mobile device may include an application capable of communicating with the cooking appliance.

At step 1210, the server system may distribute the recipe from the server system to the requesting device (e.g., the device that selected the recipe to be downloaded). In some embodiments, prior to distributing the recipe, the server system may utilize a Digital Rights Management (DRM) mechanism to configure the recipe to prevent further unauthorized distribution of the recipe after it is distributed to the requesting device.

Fig. 13 is a flow diagram illustrating a method 1300 of configuring a cooking appliance (e.g., cooking appliance 110) with a recipe, according to various embodiments. At step 1302, the cooking appliance may download a recipe from an external device. For example, the external device may be a server system (e.g., server system 1000), a mobile device, or a portable memory device. The external device may be connected via a wireless network, a physical port of the cooking appliance, or a peer-to-peer connection established by the cooking appliance.

At step 1304, the cooking appliance may execute the recipe and associated cooking logic in the cooking appliance in response to the user input and other user-related parameters. For example, the cooking appliance may detect placement of food items in the cooking appliance. The cooking appliance may execute a cooking logic in response to detecting placement of the food item. For example, the cooking appliance may detect placement of the food item by a camera in the cooking appliance, a weight sensor, a temperature probe connected to the cooking appliance, a mechanical connection sensor of the cooking appliance door, or any combination thereof. The cooking appliance may also adapt the cooking logic to user related information, such as preferences input by the user that the cooking appliance has learned based on previous user activities. For example, if the user selects a maturity level (e.g., quarter-cooked), but provides feedback to the cooking appliance after cooking, indicating that a different result is desired by the user (e.g., feedback via the user interface that the recipe is overcooked; manually instructing the cooking appliance to cook meat for a longer time), then the cooking appliance may adjust the cooking logic to automatically provide the desired result to the user.

The cooking logic may include one or more heating logic sequences represented as state machines. The recipe and cooking logic may be the recipe designed and released in method 1100. At sub-step 1306, in response to executing the cooking logic, the cooking appliance may determine which portion of the cooking logic specified in the recipe is to be used. For example, the recipe may specify one or more meal kit package identifiers associated with one or more cooking logic sequences. The cooking appliance may detect, via a camera of the cooking appliance, an optical tag of a food item object in the cooking appliance. The cooking appliance may match the optical tag with the meal kit package identifier (if any) to select the corresponding cooking logic sequence (e.g., with a corresponding state machine). The cooking appliance may perform a corresponding cooking logic sequence. In various embodiments, the optical label may include a barcode, Quick Response (QR) code, or other optical code identifying an associated recipe from a meal kit or cloud recipe store, which may include heating algorithms, recipe instructions, interactive user prompts for recipe options, and other recipe-related information.

In one embodiment, the complete recipe is encoded on an optical tag and uploaded directly to the cooking appliance when it reads the optical tag. For example, a user may create a recipe using a cooking appliance and print the recipe on a piece of paper (e.g., using an application on the user's device) to be shared with family and friends, including printed optical code containing the complete recipe (e.g., food preparation instructions and heating algorithms executed by the cooking appliance). The recipient of the printed recipe may scan the optical code through the recipient's cooking appliance to read the recipe from the optical label, allowing the cooking appliance to cook the meal as indicated in the recipe. By encoding the recipe in the optical tag, the cooking appliance can upload and store the new recipe without having to access a communication network or a remote device (e.g., the recipe database 140).

The recipe may specify two or more modes of operation and two or more cooking logic sequences associated with the modes of operation. For example, the operating modes may include a low stress mode and a high speed mode. The high speed mode requires that the operating user of the cooking appliance extract the food item target from the cooking appliance at a specific time determined by the cooking logic sequence. The low stress mode corresponds to a cooking logic sequence that implements a period of time during which an operating user may extract a food item target without overcooking or undercooking the food item target.

In some embodiments, the cooking logic may specify exception capture logic that monitors one or more sensor feeds, one or more user signals, one or more timers, or any combination thereof to determine if an unexpected event occurred during execution of the recipe. The cooking appliance may execute exception capture logic to recover from the unexpected event.

In some embodiments, the recipe specifies one or more heating logic configuration parameters to retrieve from an operating user. In these embodiments, the cooking appliance may prompt the operating user to input heating logic configuration parameters via an output component of the cooking appliance or a network interface when executing the recipe. The cooking appliance may receive user input associated with the heating logic configuration parameters via the input component or the network interface.

At sub-step 1308, the cooking appliance may configure one or more heating elements of the cooking appliance according to an initial state of the state machine. At sub-step 1310, the cooking appliance may detect a state change based on one or more sensor feeds, one or more timers, one or more user signals, or any combination thereof. At substep 1312, the cooking appliance may reconfigure at least one of the heating elements of the cooking appliance in response to the state change according to the state machine. In some embodiments, the cooking appliance may reconfigure the heating element to recover from the unexpected event based on the exception capture logic.

During execution of the recipe, at step 1314, the cooking appliance may record data from one or more sensor feeds, one or more user signals, or any combination thereof, relative to one or more timers. At step 1316, the cooking appliance may prompt user feedback after execution of the recipe. At step 1318, the cooking appliance may send the tracked sensor data and user-specific data (including user feedback and other user-related data determined by the cooking appliance) to a server system for analysis. In various embodiments, the cooking appliance may also (or alternatively) maintain and analyze user-specific information.

Fig. 14A-14E illustrate an exemplary oven user interface according to various embodiments. Referring to fig. 14A, the oven user interface may include an option to display a predetermined recipe or to prepare a new recipe from scratch. The pre-existing recipes may include, for example, the most recent cooks stored in the oven memory, an identification of a favorite recipe by use of the identification, or a recipe associated with a meal ordered from a supplier (e.g., by a subscription service). In one embodiment, the oven user interface guides the user through the creation of recipes from scratch, such as by providing the user with categories and subcategories of available food materials. In various embodiments, the recipe may include oven operating instructions (e.g., temperature, cooking time, etc.), or the oven may generate oven operating instructions from the recipe.

Referring to fig. 14B, an exemplary user interface for implementing a cooking process according to various embodiments is shown. As shown, the user interface guides the user through the cooking process. The user can adjust the options for each food material, which allows the user to modify the recipe according to the user preferences or according to the constraints of the food materials or cooking appliances available to the user.

Next, the user interface guides the user through placement of the food items on the tray and placement of the meal in the oven. In various embodiments, the tray may be made of glass or other material that includes optically transparent regions that allow visible light to travel substantially through two opposing surfaces of the tray. The tray may be used with instructions to assist the user in preparing the food product according to the recipe. For example, the meal kit may include a meal preparation instruction sheet that indicates a desired location for placing one or more edible substances on the tray. A user of the cooking appliance may place the meal kit instruction sheet under the glass tray while arranging one or more edible substances received from the meal kit on the tray as indicated on the instruction sheet. In some embodiments, the user may overlay one or more particular edible substances directly at one or more desired locations shown on the meal kit instruction sheet. In an alternative embodiment, instructions may be presented to the user through the user interface that include an image of the tray with the label zones and an animation of the food items placed in the desired locations within those zones.

In various embodiments, the user may select between a normal cooking mode and a fast cooking mode. The user interface displays feedback and status information to the user during cooking and resting or cooling, and notifies the user when the meal is complete.

Referring to fig. 14C, in various embodiments, the user may instruct the oven to perform additional cooking operations according to the user preferences. For example, the user may be presented with a "rinse" option that allows the user to increase the burning or maturity of the meal. In one embodiment, as shown in fig. 14C, the user can select one or more food materials for additional cooking (e.g., by presenting the user with a list of food materials in the recipe in a user interface). The computing device of the cooking appliance may then provide instructions to the user regarding suggested food product modifications (e.g., removing all food items from the tray except items that need further cooking) and placement of items to be further cooked in the oven. The user may also indicate the type of heating algorithm to be applied (e.g., burning or maturity) and the maturity level (e.g., time or end result). In one embodiment, the user's feedback is tracked and associated data is stored with the recipe to automatically refine the burn or maturity when the recipe is executed in the future.

The user may then provide feedback to the oven as shown in fig. 14D. This feedback may be used in various embodiments to adjust the formula according to the user's preferences for future meal preparations. In some embodiments, a computing system of a cooking appliance tracks user interactions (e.g., touch interactions to increase burning or maturity) and user feedback, and adjusts a stored recipe to achieve a user-desired result in future realizations of the recipe. As shown in fig. 14D, the user feedback may include a "like" or "dislike" input, further prompting to request additional feedback as to why the recipe is liked or disliked (e.g., "get burned badly," "maturity is not enough," "is disliked"). In response to the user feedback, the computing system may implement a solution to address the user's feedback. For example, the next time the user selects a recipe, the computing system may suggest a recipe adjustment to address the user feedback problem or suggest an alternative recipe from the cloud recipe store (e.g., based on similar feedback from other users). In some embodiments, user feedback on a recipe downloaded from a cloud recipe store (or other recipe server) is combined with feedback from other users to provide a community user rating for the recipe, thereby ranking or identifying high-rated and low-rated recipes in the cloud recipe store. The cloud recipe server may highlight the higher scoring recipe to the user while not paying attention to the lower scoring recipe.

In some embodiments, user feedback is used to assist a user in generating a self-managed recipe by tracking and implementing user-selected recipe changes and suggesting recipe changes from recipe knowledge (e.g., a cloud recipe server). The ability of the cooking appliance to adapt to user feedback improves user satisfaction with the oven and increases confidence that a less skilled user is preparing a complex meal. User feedback may also be used to generate community consensus on recipes from the recipe server so that higher scoring recipes are displayed prominently above lower scoring recipes to the user.

Referring to fig. 14E, the oven user interface may include additional options, such as manual cooking options and oven setting adjustments. The manual cooking options may include cooking options for various types of ovens, for example, options to instruct the ovens to bake, broil, bake, reheat, keep warm, and defrost. An exemplary display for baking, broiling, reheating, and keeping food warm is shown in fig. 14F. In various embodiments, the oven settings may include options such as Wi-Fi network connectivity, cooking history, maintenance, input/output control (e.g., sound, display options), and user account information.

With reference to fig. 15A-C, an embodiment of a user interface for selecting a heating element and a wavelength will now be described. In various embodiments, each heating element may individually reach all of the power that a power source (e.g., a wall outlet) may provide, and the cooking appliance includes a power control system and/or process to regulate power consumption such that the total power drawn from all heaters does not exceed the total power that the power source may provide. The maximum amount of power available to the power source may be a function of the maximum amount of current that can be drawn (e.g., in a residential 120V outlet in the united states). Furthermore, there is a correlation between the power consumed by each individual heating element and the wavelength of the light produced. The higher the power of the heating element, the shorter the wavelength generated.

In some embodiments, certain advanced user interface components, such as power control components, may be accessed through a "main kitchen mode" that provides a flexible user interface for creating user-generated recipes. The "master kitchen mode" may include one or more budget indicators for allocating system resources, which may indicate a maximum available amount or budget for one or more system resources, such as a power budget, a current budget, a total energy budget, and/or an average power budget. In some embodiments, a user (e.g., an experienced main kitchen) may wish to heat food with relatively mild heat from longer infrared wavelengths, and the cooking engine/power control algorithm will operate the heating element at a low duty cycle and low cycle. In other words, a fraction of a second pulse is spaced for several seconds. In some cases, the pulses may be in the order of milliseconds separated by several hundred milliseconds.

If it is desired to impinge edible substances with a relatively short wavelength but not high power density, a suitable control algorithm may apply a short pulse of full power (short wavelength) for a few seconds, but at a longer interval, to keep the average power consumption within the usable range (i.e., relatively low duty cycle, large cycle period).

Referring to fig. 15A-C, in some embodiments, the cooking zones are graphically shown to the user through a user interface, mobile application, or other device. The cooking zone may also include a map indicating the total power budget (or other budget used by the system, if any). When the power budget is exceeded, the settings may be automatically edited, or the user may be notified that changes need to be made to rebalance the power budget again. The interface may also include a user interface showing the amount of power to be programmed into each heater in its respective zone. The user interface may use the human intuition by positioning the top heater control above the cooking target and the lower heater control below the cooking target for each zone, as shown in fig. 15. In some embodiments, the interface may indicate power consumption on a red, orange, or yellow scale, or reference cooking ranges at low/medium/high settings.

The multispectral heating element method of the present disclosure operates differently than conventional ovens. Conventional ovens operate by attempting to maintain a set internal air temperature. These conventional ovens have a simple control, i.e. the heat maintained in the oven-the oven can heat the fat, not heat or maintain a temperature in between. Conventional ovens also have no different heating zones, so the concept of power budget is not important. In conventional ovens, all elements or sub-resistances of elements are always heated in some predetermined pattern in order to maintain as uniform an internal temperature distribution as possible within the cooking chamber. Maximum power means that the entire chamber increases in temperature at the fastest rate possible.

While conventional ovens heat the cavity uniformly, the multi-zone cooking methods disclosed herein allow for non-uniform heating, where different food products in different zones experience significantly different heats. In one embodiment, any of the six heating elements in the cooking chamber can assume up to 100% of the available power of the entire oven. This results in a very uneven distribution of possible heat within the chamber.

A master kitchen using the multi-zone cooking design formulations of the present disclosure may wish to apply maximum control of the heater to optimize cooking. In various embodiments, the user interface includes a "main kitchen mode" that allows a user to control the individual heaters (e.g., the heating component 112 of fig. 1 or the heating/cooling element 212 of fig. 2) and/or heating zones, if desired. Using the "main kitchen mode," the user is presented with one or more budget indicators for allocating system resources for cooking, including multi-zone cooking, such as a power budget, a current budget, a total energy budget, and/or an average power budget. For example, in some embodiments, at any given step in the heating algorithm, any one heater in the cooking chamber may consume up to 100% of the total available power of all heaters (e.g., one or more heaters consume some or all of the available system resources, or a time or set of times when no such system resources are consumed), and setting one heater to maximum power means setting the power of all other heaters to almost zero. If the heaters are configured to enable multi-zone cooking, allocating 100% of the available power to one heater allows the cooking appliance to direct power generally differently to different cooking zones, allowing food in the zone to which power is directed to cook disproportionately more than food in the zone or zones to which power is not directed, which ultimately enables the cooking appliance to complete cooking of food located in different zones substantially simultaneously. As another example, setting one heater to 50% of the total available power may mean that the remaining heaters combined only consume at most 50% of the remaining total available power. Referring to fig. 15, there is shown an embodiment of a screenshot of manual heater control for two different embodiments. In various embodiments, the cooking appliance may automatically adjust the allocation of system resources to the heaters according to a system resource budget and a user multi-zone setting, which may include a limit on the amount of heat that may be directed to a given zone at a given time, and thus a limit on the amount of one or more system resources that may be allocated to one or more heaters.

In various embodiments, the cooking appliance includes a "main cooking mode" of operation that allows a user to create, modify, and/or select a heating algorithm and/or recipe. The heating algorithm is operable to selectively adjust system resources (e.g., power received from power source 260 of fig. 2), such as power, current, or energy, allocation of one or more heating elements (e.g., heating/cooling elements 212 of fig. 2) within a budget of system resources that are commonly available for the heating elements, and to use the heating algorithm to achieve one or more desired cooking results. The creation and/or modification capability of the "master kitchen mode" may be instantiated in a user interface that provides an indication to a user of one or more system resource budgets and/or an indication of allocation of system resources to one or more heating elements in one or more steps of a heating algorithm, and facilitates the user to adjust the system resources to be delivered to each heating element throughout the execution of a recipe.

In various embodiments, the "master kitchen mode" user interface may be configured to include an indicator of system resource usage, but not power budget usage, but such an indicator may still enable or require a user of the "master kitchen mode" to utilize a particular maximum amount of system resources. In some embodiments, a "main kitchen mode" user interface may require a user creating or modifying a recipe in "main kitchen mode" to allocate 100% of the total available current budget to one heater of two or more heaters at any given step of the heating algorithm, thereby allowing the user to allocate the total budget to different heaters at different steps, but requiring the total available current budget to be used at each step. In other embodiments, the "main kitchen mode" user interface may impose the same requirements as the sentence above, except that the interface also permits the user to allocate 0% of the available current budget to all heaters in any given step of the heating algorithm.

In some embodiments, instead of or in addition to indicating the total available system resource budget to the user, the "master kitchen mode" user interface may permit the user to attempt to ostensibly allocate resources beyond the total available system resource budget to one or more heaters at a particular step in the heating algorithm. A computing or processing system in communication with the user interface may identify that the user is attempting to allocate resources beyond the total available system resource budget in a particular step, compute an alternative method to achieve substantially the same result as would be obtained if additional system resources were available (beyond the total available budget), automatically modify the heating algorithm to achieve such alternative method, notify the user that an alternative method to achieve the result is to be used in place of the user-desired method of allocating resources beyond the available system budget, and notify the user of the effect of using the alternative method. For example, if a user attempts to allocate 100% of the total available power budget to each of two heaters in a given step, the computing or processing system may determine that substantially the same desired result should be achieved, in which step 100% of the total available power budget should be allocated to a first heater of the two heaters, and in the immediately subsequent step 100% of the total available power budget should be allocated to a second heater of the two heaters, and will notify the user via the user interface that an alternative method that achieves the desired result will be used in the heating algorithm, and that the use of the alternative method will result in the recipe instantiated by the heating algorithm requiring an additional five seconds to complete. In such embodiments, the cooking appliance may provide an indication to the user regarding the available budget, the recipe results, and/or automatically adjust and balance the heating algorithm, thereby automatically adjusting the recipe to remain within the available power budget.

In some embodiments, the interface allows for selection, creation, and/or modification of a heating algorithm and includes a system resource allocation interface for selectively and interactively specifying the delivery of system resources (i.e., the amount of system resources to be delivered) to each heating element during recipe execution. The "main kitchen mode" interface allows the user to view the steps of the heating algorithm whether recipe creation is complete or in progress, and may provide the user with an indication of the status of system resource usage, including an indication of the total available system resource budget, an indication of the total remaining system resource budget, and/or an indication of the system resource usage of each heater during each step of the recipe. In some embodiments, the "master kitchen mode" projects a recipe result (e.g., a set of food product states cooked by the cooking appliance using the recipe at the termination of recipe execution, such as states related to the temperature of the food product at one or more internal locations, the surface color and/or mouthfeel of the food product, the juiciness of the food product, etc.) based on the user-configured allocation of system resources throughout the recipe, and provides an indication to the user of the system resource states and an indication of the impact of the user-configured system resource allocation on the recipe result. The indication may include an alert, an indication of a heating algorithm modification by the cooking appliance, and/or an interface to the user to make further adjustments in response thereto. In some embodiments, the recipe is adjusted according to projected recipe results, desired recipe results, and/or power budget states, and the adjustment may include, for example, an adjusted cooking time and/or other recipe adjustments.

In various embodiments, a "main kitchen mode" user interface provides a user with an option to select at least one template of a method of implementing a heating algorithm operable to selectively adjust allocation of system resources and then modify one or more aspects of the template. The template may be associated with a complete recipe or a set of one or more components of a recipe associated with one or more cooking events. The template may be stored locally on the cooking appliance or downloaded from a server (e.g., a recipe server). After the user selects a template, the user may edit the template by adjusting the allocation of system resource delivery to one or more heaters in one or more steps as described herein.

In various embodiments, the user interface may include a "simulated cooking" feature that allows the user to test how the user-generated recipe for the "main kitchen mode" will cook a certain food item(s). The user may select one or more food products for which the user-generated recipe will be tested, and the system will simulate the results (e.g., one or more states of the food product at the end of execution of the recipe), providing information about the simulation results and statistical information, such as information about burn levels, internal temperature distributions, cooking times, internal moisture content, and the like. The system may also, in some embodiments, simulate one or more states of one or more food items at one or more points in time during execution of the recipe but before completion of execution of the recipe.

Referring to fig. 16, an embodiment of a method 1600 for allocating system resources for operation of a cooking appliance will now be described. The method 1600 may be implemented by a system disclosed herein (e.g., the system 100 of fig. 1, the cooking appliance 200 of fig. 2) to allocate resources (e.g., power received from the power source 260) to a plurality of heating elements (e.g., the heating component 112 of fig. 1, the heating/cooling element 212) during execution of a heating algorithm (e.g., by the cooking engine 116 of fig. 1, the cooking engine 270 of fig. 2). In various embodiments, user interaction may be facilitated using the user interfaces disclosed herein.

In step 1602, the cooking appliance receives one or more system resources (e.g., power, current, energy), each of which has an associated budget. For example, the cooking appliance may receive electrical power from an electrical outlet, which is input to the cooking appliance through a power source (e.g., power source 260 of fig. 2).

In step 1604, a user interface is provided to facilitate user-configured allocation of one or more system resources to the plurality of heating elements without exceeding any associated budgets of the one or more system resources. In various embodiments, the result of the user interaction is a recipe and/or heating algorithm to be executed by the cooking engine to cook one or more food substances. In some embodiments, an indication of the associated budget is provided to the user, such as an indication of the available system resource budget remaining during operation of the one or more heating elements and/or an indication of current system usage.

In some embodiments, the computing components of the cooking appliance (e.g., the controller 220 and memory 230 of fig. 2) are operable to project recipe results (e.g., quartz tungsten halogen heaters) based on the user-configured allocation of budget system resources to the plurality of heating elements. The indication of the associated budget may include an indication of the impact of the user-configured allocation of system resources on the recipe results. The computing component can also adjust the heating algorithm based on projected recipe results and/or budgeted system resources. In some embodiments, the indication of the budget system resources of the user includes an adjusted cooking time and/or other recipe adjustments.

In various embodiments, the computing component is further operable to facilitate user-configured allocation of system resources to a plurality of heating elements to heat a plurality of zones within a multi-zone cooking chamber. The control component may comprise logic and circuitry to facilitate automatic allocation of one or more system resources to the plurality of heating elements in accordance with an associated budget and/or user settings.

The system resources are then applied to the plurality of heating elements in step 1606 to heat one or more food substances within the cooking chamber according to a heating algorithm. For example, the heating elements may include (or be controlled by) control components that receive electrical power from external sources and distribute the received electrical power among the heating elements to implement a heating algorithm.

In step 1608, delivery of the one or more system resources to the one or more heating elements is adjusted such that the associated budget for each of the one or more system resources is not exceeded during execution of the heating algorithm for delivery to the plurality of heating elements. For example, the cooking appliance may be adjusted to operate within system power constraints indicated by the associated resource budget. In various embodiments, the cooking chamber includes a plurality of cooking zones, and the heating element is selectively operable to heat one or more food substances within each of the plurality of cooking zones. In some embodiments, the computing component executes a heating algorithm to cook at least one food substance in the cooking chamber, detects a change in state of the at least one food substance, and modifies the heating algorithm during cooking to reconfigure system resources supplied to the one or more heating elements in response to the change in state and in accordance with an associated budget for the system resources.

Some embodiments of the present disclosure have other aspects, elements, features and steps in addition to or in place of those described above. These possible additions and substitutions are described in the remainder of the specification. Reference in the specification to "various embodiments" or "some embodiments" means that a particular feature, structure, or characteristic described in connection with the embodiments is included in at least one embodiment of the disclosure. Alternative embodiments (e.g., referred to as "other embodiments") are not mutually exclusive of other embodiments. In addition, various features are described which may be exhibited by some embodiments and not by others. Similarly, various requirements are described which may be requirements for some embodiments but not other embodiments.

While some embodiments of the present disclosure include processes or methods presented in a given order, alternative embodiments may perform routines having steps, or employ systems having blocks, in a different order, and some processes or blocks may be deleted, moved, added, subdivided, combined, and/or modified to provide alternative forms or subcombinations. Each of these processes or blocks may be implemented in a variety of different ways. Further, while processes or blocks are sometimes shown as being performed in series, these processes or blocks may alternatively be performed in parallel, or may be performed at different times. When a process or step is "based on" a value or calculation, the process or step should be interpreted as being based on at least the value or the calculation.

Some embodiments of the present disclosure have other aspects, elements, features and steps in addition to or in place of those described above. These possible additions and substitutions are described in the remainder of the specification.