阅读说明：本技术 菜谱的推荐方法及装置、智能烹饪机器人、可读存储介质 (Menu recommendation method and device, intelligent cooking robot and readable storage medium ) 是由 张志青 于 2021-07-17 设计创作，主要内容包括：本申请提供一种菜谱的推荐方法及装置、智能烹饪机器人、可读存储介质。菜谱的推荐方法包括：获取用户的基础信息；所述基础信息包括：身体质量指数和体重改变需求；根据所述身体质量指数和所述体重改变需求确定影响数值；根据所述影响数值和预设的标准体重确定建议摄入卡路里；根据所述建议摄入卡路里确定所述用户的推荐菜谱；展示所述推荐菜谱。该推荐方法用以实现菜谱的精准化推荐。(The application provides a menu recommendation method and device, an intelligent cooking robot and a readable storage medium. The menu recommendation method comprises the following steps: acquiring basic information of a user; the basic information includes: body mass index and weight change requirements; determining an impact value from the body mass index and the weight change requirement; determining a recommended calorie intake according to the influence value and a preset standard weight; determining a recommended recipe for the user based on the suggested intake calories; and displaying the recommended menu. The recommendation method is used for realizing accurate recommendation of the menu.)

1. A method for recommending a recipe, comprising:

acquiring basic information of a user; the basic information includes: body mass index and weight change requirements;

determining an impact value from the body mass index and the weight change requirement;

determining a recommended calorie intake according to the influence value and a preset standard weight;

determining a recommended recipe for the user based on the suggested intake calories;

and displaying the recommended menu.

2. The recommendation method according to claim 1, wherein the basic information further comprises: waist circumference; said determining an impact value from said body mass index and said weight change need, comprising:

determining an impact value based on the body mass index, the weight change requirement, and the waist circumference.

3. The recommendation method according to claim 1, wherein prior to said determining the user's recommended recipe based on said suggested calorie intake, said recommendation method further comprises:

acquiring a dish making record of the user; the cooking record is used for indicating the cooking times of the user on the current day and the calorie of the cooking in each time;

the determining a recommended recipe for the user based on the suggested intake calories, comprising:

determining recommended recipe calories from the cooking record and the suggested intake calories; the recommended recipe calories are less than the recommended intake calories;

and determining the recommended menu according to the calorie of the recommended menu.

4. The recommendation method according to claim 3, wherein said determining recommended recipe calories from said cooking record and said suggested intake calories comprises:

if the number of times of cooking the dish on the current day of the user is 0, determining the calorie of the recommended menu according to the recommended calorie intake;

if the number of times of cooking the dish of the user on the current day is 1, acquiring the calorie which is already ingested by the user on the current day, and determining the calorie of a recommended menu according to the recommended ingested calorie, the calorie of the cooked dish and the calorie which is already ingested on the current day;

and if the number of times of cooking of the user on the current day is more than 1, determining the calorie of the recommended menu according to the calorie of the recommended intake calorie and the calorie of the dish cooked each time.

5. The recommendation method according to claim 4, wherein determining recommended recipe calories from the recommended intake calories, calories of the dish made, and calories that have been ingested on the current day comprises:

determining the recommended recipe calories from the suggested intake of calories, the calories of the dish made, the calories that have been taken on the current day, and a preset relationship;

the preset relational expression is as follows: K-K1-K2-30% -K3; wherein K is the recommended recipe calories, K1 is the recommended intake calories, K2 is the calories that have been taken on the day, and K3 is the calories of the dish made.

6. The recommendation method according to claim 3, wherein said determining a recommended recipe from said recommended recipe calories comprises:

acquiring the cooking requirement of the user; the dish making requirements comprise the number of required recipes;

determining the number of recommended recipes and the calorie corresponding to each recommended recipe according to the number of the required recipes and the calorie of the recommended recipes;

and determining the recommended recipes from a plurality of preset recipes according to the number of the recommended recipes and the calorie corresponding to each recommended recipe.

7. The recommendation method of claim 1, wherein the recommended recipe is a weekly recommended recipe, the recommended intake calories are a single day recommended intake calories; the determining a recommended recipe for the user based on the suggested intake calories, comprising:

determining at least 7 recipes from a preset plurality of recipes according to the recommended calorie intake;

arranging and combining the at least 7 recipes according to the suggested intake calories to generate 7 groups of recommended recipes; the 7 groups of recommended recipes are recommended recipes for one week, and the calorie corresponding to each group of recommended recipes is less than the calorie intake suggested.

8. A menu recommendation device, comprising:

the acquisition module is used for acquiring basic information of a user; the basic information includes: body mass index and weight change requirements;

a processing module to: determining an impact value from the body mass index and the weight change requirement; determining a recommended calorie intake according to the influence value and a preset standard weight; determining a recommended recipe for the user based on the suggested intake calories;

and the display module is used for displaying the recommended menu.

9. An intelligent cooking robot, comprising:

a robot body;

a processor disposed within the robot body; and a memory communicatively coupled to the processor;

wherein the memory stores instructions executable by the processor to enable the processor to perform a recipe recommendation method as claimed in any one of claims 1 to 7.

10. A readable storage medium, characterized in that the readable storage medium has stored thereon a computer program which, when executed by a computer, performs a method of recommending a recipe according to any one of claims 1-7.

Technical Field

The application relates to the technical field of artificial intelligence, in particular to a menu recommendation method and device, an intelligent cooking robot and a readable storage medium.

Background

In the prior art, some menu application programs or intelligent cooking robots can provide menu recommendation functions for users.

When an existing menu application program or an intelligent cooking robot carries out menu recommendation, a body mass index is calculated according to the age, the height, the weight, the waist circumference and the like, and then some diet suggestions and suggested calorie intake of a user are provided based on the body mass index. By the method, accurate recommendation of the menu cannot be realized.

Disclosure of Invention

The embodiment of the application aims to provide a menu recommendation method and device, an intelligent cooking robot and a readable storage medium, which are used for realizing accurate recommendation of menus.

In a first aspect, the present application provides a method for recommending recipes, including: acquiring basic information of a user; the basic information includes: body mass index and weight change requirements; determining an impact value from the body mass index and the weight change requirement; determining a recommended calorie intake according to the influence value and a preset standard weight; determining a recommended recipe for the user based on the suggested intake calories; and displaying the recommended menu.

In the present application, in contrast to the prior art, in addition to considering the effect of body mass index on the recommended calorie intake, the user's weight change needs are also incorporated; the influence value is determined through the weight change demand and the body mass index, more scientific and reasonable suggested intake calorie is determined based on the influence value, and then the recommended menu determined based on the suggested intake calorie is more accurate, more accords with the demand of the user, and the accurate recommendation of the menu is realized.

As a possible implementation manner, the basic information further includes: waist circumference; said determining an impact value from said body mass index and said weight change need, comprising: determining an impact value based on the body mass index, the weight change requirement, and the waist circumference.

In the present application, waist circumference information of the user is combined in addition to the body mass index and the weight change need; based on the influence values determined by the three, more scientific and reasonable suggested intake calorie can be determined, and the accuracy of the finally recommended menu is further improved.

As one possible implementation, before the determining the recommended recipe for the user according to the suggested intake calories, the recommendation method further includes: acquiring a dish making record of the user; the cooking record is used for indicating the cooking times of the user on the current day and the calorie of the cooking in each time; the determining a recommended recipe for the user based on the suggested intake calories, comprising: determining recommended recipe calories from the cooking record and the suggested intake calories; the recommended recipe calories are less than the recommended intake calories; and determining the recommended menu according to the calorie of the recommended menu.

In the method, before the recommended menu is determined, a dish making record of a user is obtained; determining the calorie of a recommended menu by combining the suggested calorie intake through the dish making record of the user, and further determining the recommended menu according to the calorie of the recommended menu; namely, the finally determined recommended menu is related to the actual dish making condition of the user, and the accuracy is higher.

As one possible implementation, the determining recommended recipe calories from the cooking record and the suggested intake calories includes: if the number of times of cooking the dish on the current day of the user is 0, determining the calorie of the recommended menu according to the recommended calorie intake; if the number of times of cooking the dish of the user on the current day is 1, acquiring the calorie which is already ingested by the user on the current day, and determining the calorie of a recommended menu according to the recommended ingested calorie, the calorie of the cooked dish and the calorie which is already ingested on the current day; and if the number of times of cooking of the user on the current day is more than 1, determining the calorie of the recommended menu according to the calorie of the recommended intake calorie and the calorie of the dish cooked each time.

In the application, if the user does not have done the dish on the day, the calorie of the recommended menu is determined directly according to the intake calorie of the suggestion; if the user has done the dish 1 time the day, determining recommended recipe calories in combination with calories of the dish done and calories already ingested on the day; if the user does the dish more than 1 time on the same day, determining the calorie of the recommended menu by combining the calorie of the dish; the method and the device realize effective and accurate determination of the recommended menu calories by combining different calorie information according to different dish making conditions.

As one possible implementation, the determining recommended recipe calories from the suggested intake calories, the calories of the dish made, and the calories that have been ingested on the current day includes: determining the recommended recipe calories from the suggested intake of calories, the calories of the dish made, the calories that have been taken on the current day, and a preset relationship; the preset relational expression is as follows: K-K1-K2-30% -K3; wherein K is the recommended recipe calories, K1 is the recommended intake calories, K2 is the calories that have been taken on the day, and K3 is the calories of the dish made.

In the method and the device, the calorie of the recommended menu is effectively and accurately calculated through the preset relational expression.

As a possible implementation manner, the determining a recommended recipe according to the recommended recipe calories includes: acquiring the cooking requirement of the user; the dish making requirements comprise the number of required recipes; determining the number of recommended recipes and the calorie corresponding to each recommended recipe according to the number of the required recipes and the calorie of the recommended recipes; and determining the recommended recipes from a plurality of preset recipes according to the number of the recommended recipes and the calorie corresponding to each recommended recipe.

In the method, the number of the recommended recipes and the calorie corresponding to each recommended recipe are determined by combining the number of required recipes and the calorie of the recommended recipes in the dish making requirement of a user, and then the recommended recipes are determined by combining the number of the recommended recipes and the calorie corresponding to each recommended recipe; by the method, the requirements of multiple menus of the user can be met, and more flexible and more accurate menu recommendation is realized.

As one possible implementation, the recommended recipe is a weekly recommended recipe that is a single day of recommended intake calories; the determining a recommended recipe for the user based on the suggested intake calories, comprising: determining at least 7 recipes from a preset plurality of recipes according to the recommended calorie intake; arranging and combining the at least 7 recipes according to the suggested intake calories to generate 7 groups of recommended recipes; the 7 groups of recommended recipes are recommended recipes for one week, and the calorie corresponding to each group of recommended recipes is less than the calorie intake suggested.

In the application, if a recommended menu of a week is finally provided, a plurality of menus corresponding to the week can be determined first; and then the menus are grouped, so that the daily menu of 7 days of a week is determined, and further the precise recommendation of the menu of a week is realized.

In a second aspect, the present application provides a menu recommending apparatus, including: the method for recommending recipes as described in the first aspect and any one of the possible implementations of the first aspect.

In a third aspect, the present application provides an intelligent cooking robot, comprising: a robot body; a processor disposed within the robot body; and a memory communicatively coupled to the processor; wherein the memory stores instructions executable by the processor to enable the processor to perform the recipe recommendation method as described in the first aspect and any one of the possible implementations of the first aspect.

In a fourth aspect, the present application provides a readable storage medium, on which a computer program is stored, where the computer program is executed by a computer to perform the method for recommending recipes as described in the first aspect and any one of the possible implementation manners of the first aspect.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments of the present application will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and that those skilled in the art can also obtain other related drawings based on the drawings without inventive efforts.

Fig. 1 is a flowchart of a menu recommendation method provided in an embodiment of the present application;

fig. 2 is a schematic structural diagram of a menu recommending device according to an embodiment of the present application;

fig. 3 is a schematic structural diagram of an intelligent cooking robot provided in an embodiment of the present application.

Icon: 200-a menu recommending device; 210-an obtaining module; 220-a processing module; 230-a display module; 300-an intelligent cooking robot; 310-a processor; 320-a memory; 330-a display; 340-input/output module.

Detailed Description

The technical solutions in the embodiments of the present application will be described below with reference to the drawings in the embodiments of the present application.

The menu recommendation method provided by the embodiment of the application can be applied to various application scenes needing menu recommendation, such as: the menu application program pushes a recommended menu to the user so that the user can apply the recommended menu; for another example: the intelligent cooking robot pushes the recommended menu to the user, then the user selects the appointed menu, and the intelligent cooking robot cooks the appointed menu in combination with the appointed menu.

It will be appreciated that the recipe is used to record the cooking of the dish, including the various steps of cooking the dish, as well as the proportions, names, etc. of the ingredients and side dishes.

Based on the application scenario of the recipe, the hardware environment corresponding to the recommendation method of the recipe may be: a device on which the recipe application is installed, or a back-end server of the recipe application; intelligent cooking robot, etc.

Based on the introduction of the application scenario and the hardware environment, referring to fig. 1, a flowchart of a menu recommendation method provided in an embodiment of the present application is shown, where the menu recommendation method includes:

step 110: and acquiring basic information of the user. The basic information includes: body mass index and weight change requirements.

Step 120: determining an impact value based on the body mass index and the weight change requirement.

Step 130: and determining the recommended intake calorie according to the influence value and the preset standard weight.

Step 140: the recommended recipe for the user is determined based on the suggested intake of calories.

Step 150: and displaying the recommended menu.

A detailed implementation of steps 110-150 is described next.

In step 110, the body quality index in the basic information of the user may be directly input by the user; it can also be: the user inputs information for calculating the body mass index and then calculates the body mass index based on the information, which is not limited in the embodiment of the present application. Wherein the information for calculating the body mass index comprises: sex, age, height, weight, and calculating the body mass index based on these information are conventional in the art and will not be described herein.

As an alternative embodiment, the weight change need comprises: fat reduction, muscle enhancement, maintenance of the present condition, and the like. Wherein, fat reduction represents that the user wants to reduce the fat content in the body. Muscle building represents a user's desire to increase muscle content in the body. The present status was maintained, and the fat content and the muscle content were not changed.

In the basic information, the following may be further included: the waist circumference of the user; based on the waist circumference information, more accurate calculation of the recommended calorie intake can be achieved, as described in the following embodiments.

Based on the basic information obtained in step 110, an impact value is determined in step 120 based on the body mass index and the weight change need, wherein the impact value may be understood as an intermediate value for calculating the recommended calorie intake. As an alternative, the corresponding relationship between the body mass index, the weight change requirement, and the influence value is preset, and in step 120, the influence value can be determined according to the preset corresponding relationship.

Referring next to table 1, an example of an alternative correspondence relationship provided in the embodiments of the present application is shown, in table 1, when BMI (body mass index) is less than 18.5, its grade is a; 18.5< ═ BMI <24, grade B; when 24< ═ BMI <28, its grade is still C; when 28< ═ BMI <32, its grade is still C; at 32 ═ BMI, the rating is still C.

BMI	Demand for	Influence value
			A	Fat reduction	25
B	Fat reduction	20
			C	Fat reduction	20
A	Muscle increasing	30
			B	Muscle increasing	25
C	Muscle increasing	20
			A	Maintenance of	30
B	Maintenance of	25
			C	Maintenance of	20

TABLE 1

In combination with the correspondence illustrated in table 1, in step 120, in the case where the body mass index and the weight change need are known, a corresponding look-up in table 1 can determine the impact value. For example: assuming a BMI of 17, corresponding to a rating of A, and a weight change requirement of fat reduction, the impact value at this time is determined to be 25.

It is mentioned in the foregoing embodiments that, in addition to the BMI and the weight change need, the basic information may include: waist circumference. Thus, as an alternative embodiment, step 120 includes: determining an impact value according to the body mass index, the weight change demand and the waist circumference.

In the present application, waist circumference information of the user is combined in addition to the body mass index and the weight change need; based on the influence values determined by the three, more scientific and reasonable suggested intake calorie can be determined, and the accuracy of the finally recommended menu is further improved.

In this embodiment, too, a correspondence between the body mass index, the weight change requirement and the waist circumference and the influence value can be preset, and the influence value can then be determined from this correspondence.

As an alternative implementation, please refer to table 2, which is an example of the correspondence between the body mass index, the body weight change requirement, and the waist circumference and the influence value provided in the examples of the present application, in table 2, the correspondence between the waist circumference level and the waist circumference value is: male: when the waist circumference is more than 90, the grade is F, and when the waist circumference is less than 90, the grade is G; for the woman: when the waist circumference is greater than 80, the grade is F, and when the waist circumference is less than 80, the grade is G.

TABLE 2

In combination with the correspondence illustrated in table 2, in step 120, in the case that the body mass index, the weight change requirement and the impact value are known, the corresponding impact value can be determined in combination with the correspondence. Assuming that the BMI is 17, the corresponding grade is A; the user is male, waist is 91, the corresponding grade is F, the weight change requirement is fat reduction, and the corresponding influence value of the user is 20.

Further, in this embodiment, since the level of waist circumference is related to the gender of the user, the gender information of the user may also be acquired at the same time when the basic information is acquired in step 110; alternatively, in step 110, the gender information and the waist circumference of the user are simultaneously obtained, and the waist circumference level is directly determined according to the corresponding relationship between the waist circumference, the gender and the waist circumference level, that is, the waist circumference obtained in step 110 is the waist circumference level. Or other implementable embodiments, and are not limited in the examples of the present application.

After the impact value is determined in step 120, a recommended calorie intake is determined in step 130 based on the impact value and a preset standard weight. As an alternative embodiment, the standard weight of a male is-100; the standard weight for women is height-105. For example, assuming that the user is 180 in height and male in gender, the standard weight is: 180-; if the gender is female, the standard weight is 180-.

In this embodiment, in implementation, it is required to first obtain the height and the gender of the user, and then determine the standard weight of the user according to the preset corresponding relationship between the height, the gender and the standard weight.

In another embodiment, the standard body weight may also be preset to a fixed value and then the recommended calorie intake determined directly based on the fixed value and the impact value.

As an alternative embodiment, it is recommended that calorie intake affects the value of standard body weight. For example, assuming an impact value of 20 and a standard weight of 80, the recommended calorie intake is: 1800.

further, the recommended intake calories determined in step 130 are single day recommended intake calories, i.e., a day of recommended intake calories.

After the suggested intake calories are determined in step 130, a recommended recipe for the user is determined based on the suggested intake calories in step 140. In the present embodiment, the step 140 may adopt various corresponding implementations in combination with different application scenarios, and the following describes an implementation of the step 140.

In step 140, the determined recommended menu may be the current day recommended menu of the user or the week recommended menu of the user, i.e. the recommended menu from monday to sunday.

If it is a week's recommended recipe, as an alternative embodiment, step 140 includes: determining at least 7 recipes from a predetermined plurality of recipes based on the recommended calorie intake; arranging and combining at least 7 recipes according to the suggested calorie intake to generate 7 groups of recommended recipes; the 7 groups of recommended recipes are the recommended recipes of one week, and the calorie corresponding to each group of recommended recipes is less than the recommended calorie intake.

Wherein, the calorie corresponding to at least 7 recipes is less than the recommended calorie intake, thus ensuring that the calorie of the recommended recipe is less than the recommended calorie intake every day.

Different embodiments are possible when at least 7 recipes are combined in a permutation. Such as: assuming there are only 7 recipes, the 7 recipes are randomly assigned to 7 days of the week, i.e., there is only one recipe per recommended recipe. For another example: assuming that the number of recipes is greater than 7, 7 groups of recommended recipes may be combined based on the condition that the calories of each group of recommended recipes are less than the suggested intake calories, each group of recommended recipes including one or more recipes. Then 7 groups of recipes are randomly distributed to 7 days of a week, and generation of the recommended recipes for the week is realized.

In the application, if a recommended menu of a week is finally provided, a plurality of menus corresponding to the week can be determined first; and then the menus are grouped, so that the daily menu of 7 days of a week is determined, and further the precise recommendation of the menu of a week is realized.

In such an embodiment, the embodiment of determining at least 7 recipes may be the same as the embodiment of determining at least one recipe when a recipe for the current day is recommended, and the embodiment of determining one or more recommended recipes for the current day from a plurality of recipes will be described next.

In this embodiment, before performing step 140, the recommendation method may further include: acquiring a dish making record of a user; the cooking record is used for indicating the cooking times of the user on the day and the calorie of the dish made each time. Correspondingly, step 140 may include: determining the calorie of a recommended menu according to the dish making record and the intake calorie recommended; the recommended recipe calories are less than the recommended intake calories; and determining the recommended menu according to the calorie of the recommended menu.

In this embodiment, before determining the recommended menu, a cooking record of the user is obtained; determining the calorie of a recommended menu by combining the suggested calorie intake through the dish making record of the user, and further determining the recommended menu according to the calorie of the recommended menu; namely, the finally determined recommended menu is related to the actual dish making condition of the user, and the accuracy is higher.

If the recommendation method is applied to the menu application program, the cooking record of the user can be the cooking record actively input into the menu application program after the user cooks every time. If the recommendation method is applied to the intelligent cooking robot, the user does not cook once, and the cooking record is correspondingly generated on the intelligent cooking robot, namely, the cooking record of the user can be directly obtained from the local.

In the cooking record, may include: the cooking time of the user, the information of the dishes made by the user, and based on the information, the cooking times of the user on the day and the calories of the dishes made by the user (included in the information of the dishes made by the user) can be indicated.

As an alternative embodiment, the determination of recommended recipe calories from cooking records and recommended calories ingested includes: if the number of times of cooking the dish on the current day of the user is 0, determining the calorie of the recommended menu according to the recommended calorie intake; if the number of times of cooking the dish on the day is 1, acquiring the calorie which is already ingested by the user on the day, and determining the calorie of the recommended menu according to the calorie which is suggested to be ingested, the calorie of the cooked dish and the calorie which is already ingested on the day; and if the cooking times of the user on the current day are more than 1, determining the calorie of the recommended menu according to the recommended intake calorie and the calorie of the dish cooked each time.

In such an embodiment, if the user has not done the dish on the day, the recommended recipe calories are determined directly from the suggested intake calories; if the user has done the dish 1 time the day, determining recommended recipe calories in combination with calories of the dish done and calories already ingested on the day; if the user does the dish more than 1 time on the same day, determining the calorie of the recommended menu by combining the calorie of the dish; the method and the device realize effective and accurate determination of the recommended menu calories by combining different calorie information according to different dish making conditions.

If the number of times the user made dishes on the current day is 0, the recommended recipe calories are less than the recommended intake calories, for example: the recommended intake calories is 800, then the recommended recipe calories may be: 750 or 700, etc.

As an alternative embodiment, the recommended recipe calories may be forty percent of the recommended intake calories.

If the number of times of cooking the dish on the day is 1, the calorie which is already taken by the user on the day is obtained firstly. In one embodiment, the calories that have been ingested on the day may be equal to the calories of the dish that is being made; in another embodiment, the calories that have been ingested on the day may be less than the calories of the dish that is being made; in yet another embodiment, the calories that have been ingested on the day may be manually input calories by the user.

The recommended recipe calories may be calculated based on the calories that the user has taken and the calories of the dish made on the current day, as well as the suggested intake of calories. As an alternative embodiment, the recommended recipe calories are determined based on the recommended calories to be ingested, the calories of the dish to be made, the calories that have been ingested on the day, and a preset relationship. Wherein, the preset relational expression is as follows: K-K1-K2-30% -K3. K is the recommended recipe calories, K1 is the recommended calories ingested, K2 is the calories already ingested on the day, and K3 is the calories of the dish made.

In the method and the device, the calorie of the recommended menu is effectively and accurately calculated through the preset relational expression.

In actual application, other implementable relational expressions can be preset in a specific application scenario, and the preset relational expression is not limited in the embodiment of the present application.

If the user has made more than 1 dish on the same day, the recommended recipe calories may equal the recommended intake calories minus the calories of the dish made, where the calories of the dish made are the sum of the calories of all dishes made.

Further, based on the recommended recipe calories, a recommended recipe may be determined. As an alternative embodiment, a preset number of recommended recipes, which are less than the calories of the recommended recipe, is determined from the preset number of recipes, such as: the preset number may be 8.

It is understood that if the user does not have a particular required amount of the number of recipes, and recommends a plurality of recipes to the user at a time, the user can select a recipe to cook. If the user selects a plurality of recipes, the user needs to calculate the total calories of the selected plurality of recipes by himself or herself so as to ensure that the recommended calorie intake is not exceeded.

As another embodiment, the user may also directly give the required amount of the number of recipes, and then determine a plurality of recipes matching the required amount, so that the user does not need to judge whether the total calories of the plurality of recipes exceed the recommended intake calories. Accordingly, the process of determining the recommended recipe may include: acquiring the dish cooking requirement of a user; the dish making requirements comprise the number of required recipes; determining the number of recommended recipes and the calorie corresponding to each recommended recipe according to the number of required recipes and the calorie of the recommended recipes; and determining the recommended recipes from the preset plurality of recipes according to the number of the recommended recipes and the calorie corresponding to each recommended recipe.

In the embodiment, the number of the recommended recipes and the calorie corresponding to each recommended recipe are determined by combining the number of the required recipes and the calorie of the recommended recipes in the user's dish making demand, and then the recommended recipes are determined by combining the number of the recommended recipes and the calorie corresponding to each recommended recipe; by the method, the requirements of multiple menus of the user can be met, and more flexible and more accurate menu recommendation is realized.

The number of required recipes can be understood as the number of recipes required in the day, such as: the user wants to make 3 dishes on the same day, and the number of the required dishes on the same day is 3.

The number of recommended recipes and the corresponding calories of each recommended recipe can be determined by dividing the recommended recipe calories into a plurality of shares based on the number of required recipes. For example: assuming that the calories of the recommended recipes are 300 and the number of required recipes is 3, the number of recommended recipes is 3, and the calories corresponding to each recommended recipe is 100. Assuming that the calories of the recommended recipes are 300 and the number of required recipes is 1, the number of recommended recipes may be a preset number (for example, 8), and the calories of the preset number of recommended recipes are all less than or equal to 300.

Based on the number of the recommended recipes and the calorie corresponding to each recommended recipe, the recommended recipes can be determined from a plurality of preset recipes. Such as: the number of the recommended recipes is 3, the calorie corresponding to each recommended recipe is 100, the recommended recipes are 3 recipes with less calories than 100, and the 3 recipes should be different recipes. The number of the recommended recipes is a preset number (for example, 8), and the calories corresponding to the preset number of recommended recipes are all less than or equal to 300, so that the recommended recipes are the preset number of recipes with the calories less than or equal to 300.

In the above embodiment, if a recommended recipe that meets the requirement cannot be determined according to the number of recommended recipes and the calorie corresponding to each recommended recipe, prompt information indicating that there is no recommended recipe that meets the requirement is output. Or, regardless of the limiting condition of the number of the recommended recipes, at least one recipe which can meet the calorie of the recommended recipe is determined from a plurality of preset recipes to be used as the final recommended recipe.

In the embodiment of the present application, the recommended recipe determined in step 140 is the recommended recipe determined based on the current real-time information, and in actual application, if any update information in the above information is obtained, the recommended recipe is re-determined according to the update information in the above embodiment. Such as: if the waist circumference of the user is changed, re-determining the recommended menu based on the changed waist circumference; for another example: and if the cooking record of the user is updated, re-determining the recommended menu based on the updated cooking record.

After determining the recommended recipes in step 140, if there is only one recommended recipe, the recommended recipe may be directly presented in step 150. If there are more recommended recipes, in step 150, a list of recommended recipes is generated from the recommended recipes and displayed.

Specifically, if the recommended recipes are weekly recommended recipes, the recommended recipes are displayed in a preset weekly recommended recipe form. If the plurality of recommended recipes are recommended recipes on the same day, the plurality of recommended recipes can be displayed in an arrangement mode according to the order of the calories, the recommendation index of the recipes and the like.

The form of the preset weekly recommended menu may be set in combination with an actual application scenario, and is not limited in the embodiment of the application. And, the recommendation index of the recipe is generally known information in the recipe application or the intelligent cooking robot, and generation or acquisition of the known information is not described herein.

Based on the same inventive concept, please refer to fig. 2, an embodiment of the present application further provides a menu recommending apparatus 200, including: an acquisition module 210, a processing module 220, and a presentation module 230.

The obtaining module 210 is configured to: acquiring basic information of a user; the basic information includes: body mass index and weight change requirements; the processing module 220 is configured to: determining an impact value from the body mass index and the weight change requirement; determining a recommended calorie intake according to the influence value and a preset standard weight; determining a recommended recipe for the user based on the suggested intake calories; the display module 230 is used for displaying the recommended menu.

In this embodiment of the application, the processing module 220 is specifically configured to: determining an impact value based on the body mass index, the weight change requirement, and the waist circumference.

In this embodiment of the application, the obtaining module 210 is further configured to obtain a cooking record of the user; the cooking record is used for indicating the cooking times of the user on the current day and the calorie of the cooking in each time; the processing module 220 is specifically configured to: determining recommended recipe calories from the cooking record and the suggested intake calories; the recommended recipe calories are less than the recommended intake calories; and determining the recommended menu according to the calorie of the recommended menu.

In this embodiment of the application, the processing module 220 is specifically configured to: if the number of times of cooking the dish on the current day of the user is 0, determining the calorie of the recommended menu according to the recommended calorie intake; if the number of times of cooking the dish of the user on the current day is 1, acquiring the calorie which is already ingested by the user on the current day, and determining the calorie of a recommended menu according to the recommended ingested calorie, the calorie of the cooked dish and the calorie which is already ingested on the current day; and if the number of times of cooking of the user on the current day is more than 1, determining the calorie of the recommended menu according to the calorie of the recommended intake calorie and the calorie of the dish cooked each time.

In this embodiment of the application, the processing module 220 is specifically configured to: determining the recommended recipe calories from the suggested intake of calories, the calories of the dish made, the calories that have been taken on the current day, and a preset relationship; the preset relational expression is as follows: K-K1-K2-30% -K3; wherein K is the recommended recipe calories, K1 is the recommended intake calories, K2 is the calories that have been taken on the day, and K3 is the calories of the dish made.

In this embodiment of the present application, the obtaining module 210 is further configured to: acquiring the cooking requirement of the user; the dish making requirements comprise the number of required recipes; the processing module 220 is specifically configured to: determining the number of recommended recipes and the calorie corresponding to each recommended recipe according to the number of the required recipes and the calorie of the recommended recipes; and determining the recommended recipes from a plurality of preset recipes according to the number of the recommended recipes and the calorie corresponding to each recommended recipe.

In this embodiment of the application, the processing module 220 is specifically configured to: determining at least 7 recipes from a preset plurality of recipes according to the recommended calorie intake; arranging and combining the at least 7 recipes according to the suggested intake calories to generate 7 groups of recommended recipes; the 7 groups of recommended recipes are recommended recipes for one week, and the calorie corresponding to each group of recommended recipes is less than the calorie intake suggested.

Each functional module of the menu recommendation device 200 corresponds to each step of the menu recommendation method, and therefore, the implementation of each functional module refers to the implementation of each step of the menu recommendation method, and is not repeatedly described in the embodiments of the present application.

Based on the same inventive concept, please refer to fig. 3, an embodiment of the present application further provides an intelligent cooking robot 300, which includes a robot body, a processor 310 and a memory 320 disposed in the robot body, and a display 330 and an input/output module 340 disposed on the robot body.

The intelligent cooking robot 300 may be an execution subject of a recipe recommendation method. The embodiment of the robot body can refer to the structures of various cooking robots in the prior art, and is not described in the embodiment of the present application.

The processor 310, the memory 320, the display 330, and the input/output module 340 are electrically connected directly or indirectly to realize data transmission or interaction. For example, electrical connections between these components may be made through one or more communication or signal buses. The recipe recommendation method includes at least one software function module that can be stored in the memory 320 in the form of software or firmware (firmware), for example, a software function module or a computer program included in the recipe recommendation apparatus 200, respectively.

The processor 310 may be an integrated circuit chip having signal processing capabilities. The Processor 310 may be a general-purpose Processor including a CPU (Central Processing Unit), an NP (Network Processor), and the like; but may also be a digital signal processor, an application specific integrated circuit, an off-the-shelf programmable gate array or other programmable logic device, discrete gate or transistor logic, discrete hardware components. Which may implement or perform the methods, steps, and logic blocks disclosed in the embodiments of the present application. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.

The memory 320 may store various software programs and modules, such as program instructions/modules corresponding to the menu recommending method and apparatus provided in the embodiments of the present application. The processor 310 executes various functional applications and data processing by executing software programs and modules stored in the memory 320, that is, implements the method in the embodiment of the present application.

The Memory 320 may include, but is not limited to, a RAM (Random Access Memory), a ROM (Read Only Memory), a PROM (Programmable Read-Only Memory), an EPROM (Erasable Read-Only Memory), an EEPROM (electrically Erasable Read-Only Memory), and the like.

The display 330 provides an interactive interface (e.g., a user interface) for the user and for presenting recommended recipes. In the embodiment of the present application, the display 330 may be a liquid crystal display or a touch display. In the case of a touch display, the display can be a capacitive touch screen or a resistive touch screen, which supports single-point and multi-point touch operations. Supporting single-point and multi-point touch operations means that the touch display can sense touch operations from one or more locations on the touch display at the same time, and the sensed touch operations are sent to the processor 310 for calculation and processing.

The input/output module 340 can be used as an input or output tool, such as: mouse, keyboard lamp, through input output module 340, the user can accomplish various calibration operations better.

It is understood that the structure shown in fig. 3 is only an illustration, and the intelligent cooking robot 300 may also include more or less components than those shown in fig. 3, or have a different configuration from that shown in fig. 3, such as a robot body further provided with a mechanical arm to implement intelligent cooking. The components shown in fig. 3 may be implemented in hardware, software, or a combination thereof.

Based on the same inventive concept, an embodiment of the present application further provides a readable storage medium, where a computer program is stored on the readable storage medium, and when the computer program is executed by a computer, the method for recommending a recipe according to any of the above embodiments is executed.

In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one logical division, and there may be other divisions when actually implemented, and for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of devices or units through some communication interfaces, and may be in an electrical, mechanical or other form.

In addition, units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.

Furthermore, the functional modules in the embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.

In this document, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions.

The above description is only an example of the present application and is not intended to limit the scope of the present application, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application.