阅读说明：本技术 一种基于大数据的垃圾分类回收系统及分类回收管理方法 (Garbage classification and recovery system based on big data and classification and recovery management method ) 是由 汤进龙 于 2021-09-10 设计创作，主要内容包括：本申请涉及一种基于大数据的垃圾分类回收系统,包括：包括垃圾回收箱、信息收发终端、垃圾运输车辆、垃圾回收站和大数据平台：所述垃圾回收箱包括：箱体、固定隔板、活动隔板、移动机构、通讯模块、定位模块、图像识别装置；所述信息收发终端分别与垃圾运输车辆、垃圾回收站、大数据平台通过互联网连接通信；所述大数据平台与垃圾回收箱通过通讯模块连接。本申请通过大数据平台计算垃圾回收箱内不同种类垃圾占比,调整垃圾回收箱内的容量配比,充分利用了垃圾回收箱内的空间；通过大数据平台标记出单个种类垃圾占有量较大的位置,调整垃圾回收站位置,可减少垃圾运输距离和运输时间；通过不断自主学习优化,可不断提高大数据平台的算法准确性。(The application relates to a waste classification recovery system based on big data, include: including rubbish collection box, information transceiver terminal, rubbish transport vehicle, rubbish collection depot and big data platform: the garbage collection box includes: the device comprises a box body, a fixed partition plate, a movable partition plate, a moving mechanism, a communication module, a positioning module and an image recognition device; the information receiving and sending terminal is respectively connected and communicated with the garbage transport vehicle, the garbage recycling station and the big data platform through the Internet; the big data platform is connected with the garbage recycling bin through a communication module. The method and the device calculate the proportion of different types of garbage in the garbage recycling bin through the big data platform, adjust the capacity proportion in the garbage recycling bin, and fully utilize the space in the garbage recycling bin; the position with larger occupation of single type of garbage is marked through the big data platform, and the position of the garbage recycling station is adjusted, so that the garbage transportation distance and the garbage transportation time can be reduced; by continuous autonomous learning optimization, the algorithm accuracy of the large data platform can be continuously improved.)

1. The utility model provides a waste classification recovery system based on big data, includes rubbish collection box (1), information transceiver terminal (2), rubbish transport vehicle (3), rubbish collection depot (4) and big data platform (5), its characterized in that:

the garbage collection box (1) comprises: a box body (15) arranged at the lower part of the garbage recycling box (1); the fixed clapboard (16) is arranged in the box body (15) in the middle and is fixedly connected with the box body (15); the movable partition plates (17) are arranged in the box body (15), positioned at two sides of the fixed partition plate (16) and movably connected with the box body (15); the moving mechanisms (18) are arranged on two sides of the box body (15), are respectively in driving connection with the movable partition plates (17) on the two sides, and are electrically connected with the power supply (131) and the control module (134); the communication module (133) is connected with the big data platform (5) through the internet; the positioning module (132) is electrically connected with the communication module (133) and is used for monitoring the position information of the garbage collection box (1) and uploading data to the big data platform (5) through the communication module (133); the image recognition device (14) is used for recognizing the loading amount of different types of garbage in the garbage collection box (1) and uploading data to the big data platform (5) through the communication module (133);

the information receiving and sending terminal (2) is respectively connected and communicated with the garbage transport vehicle (3), the garbage recycling station (4) and the big data platform (5) through the internet;

the big data platform (5) is connected with the garbage recycling bin through a communication module (133).

2. The big data based garbage classification and recycling system according to claim 1, wherein:

the garbage recycling bin (1) further comprises: the electric box (13) is arranged on the side part of the garbage recycling box (1); a power supply (131) provided in the electric box (13); the control module (134) is arranged in the electric box (13) and is electrically connected with the power supply (131); the voice module (135) is arranged in the electric box (13) and is electrically connected with the power supply (131); the ceiling (11) is arranged above the box body (15) and is fixedly connected with the ground; the solar panel (12) is arranged on the upper part of the ceiling (11) and is electrically connected with the power supply (131);

the positioning module (132) is arranged in the electric box (13) and is electrically connected with the power supply (131);

the communication module (133) is arranged in the electric box (13) and is electrically connected with the power supply (131);

the image recognition device (14) is arranged at the lower part of the ceiling (11), is electrically connected with the power supply (131) and the control module (134), and is electrically connected with the voice module (135).

3. The big data based garbage classification and recycling system according to claim 2, wherein:

the case (15) includes: the first sliding chutes (151) are symmetrically arranged in the middle parts of two sides of the box body (15) and are communicated with the moving mechanism (18) and the movable partition plate (17);

the fixed bulkhead (16) comprises: the second sliding chutes (161) are symmetrically arranged in the middle of two sides of the fixed partition plate (16);

the movable partition (17) comprises: the connector (171) is arranged on one side of the movable partition plate (17) close to the inner wall of the box body (15) and is in sliding connection with the first sliding chute (151) of the box body (15); the pulley (172) is arranged on one side of the movable partition plate (17) back to the inner wall of the box body (15) and is connected with the fixed partition plate (16) in a sliding way;

the moving mechanism (18) includes: the sliding rail (1801) is arranged in the middle of the moving mechanism (18), and the horizontal height of the sliding rail is consistent with that of the first sliding groove (151); the first rotating shaft (1802) is arranged in the sliding rail (1801), is connected with the sliding rail (1801) in a sliding manner, and is fixedly connected with the connector (171) of the movable partition plate (17) at one end; the rolling gear (1803) is sleeved on the first rotating shaft (1802) and is rotationally connected with the first rotating shaft (1802); the first belt pulley (1804) is sleeved on the first rotating shaft (1802) and is in driving connection with the first rotating shaft (1802); the rack (1805) is horizontally arranged in the middle of the moving mechanism (18), is positioned below the sliding rail (1801), and is meshed with the rolling gear (1803); the limiting groove (1806) is vertically arranged at the lower part of the moving mechanism (18) and is positioned below the rack (1805); the speed reducing motor (1808) is arranged in the limiting groove (1806), is connected with the limiting groove (1806) in a sliding manner, and is electrically connected with the power supply (131) and the control module (134); the reset spring (1807) is vertically arranged at the lower part of the limit groove (1806), the lower end of the reset spring is fixedly connected with the tail end of the lower part of the limit groove (1806), and the upper end of the reset spring is fixedly connected with the speed reducing motor (1808); the second rotating shaft (1809) is in driving connection with the speed reducing motor (1808); the second belt pulley (1810) is sleeved on the second rotating shaft (1809), is in driving connection with the second rotating shaft (1809), and is in transmission connection with the first belt pulley (1804) through a belt; and two ends of the support rod (1811) are respectively and rotatably connected with the first rotating shaft (1802) and the second rotating shaft (1809).

4. The big data based garbage classification and recycling system according to claim 3, wherein:

the box (15) further comprises: the upright columns (152) are symmetrically arranged on the other two sides of the box body (15) in the middle and are fixedly connected with the bottom of the box body (15); the opening plates (153) are symmetrically arranged at two sides of the upright post (152) and are rotationally connected with the bottom of the box body (15) through hinges (154); a handle (155) which is arranged on the upper part of the opening plate (153) and is fixedly connected with the opening plate (153);

the movable partition (17) further comprises: and the brush (173) is arranged at the bottom of the movable partition plate (17) and is fixedly connected with the movable partition plate (17).

5. The big data based garbage classification and recycling system according to claim 3, wherein:

the length of the support rod (1811) is smaller than the height difference between the slide rail (1801) and the lowest part of the limit groove (1806).

6. A garbage classification and recovery management method based on big data is characterized by comprising the following steps:

step one, integrating data, namely identifying the load capacity of different types of garbage in each regional garbage collection box (1) in a city by an image identification device (14), calculating the proportion of each type of garbage relative to the total amount of the garbage, uploading the proportion data to a big data platform (5) through a communication module (133), determining the position information of each regional garbage collection box (1) in the city by a positioning module (132), importing a city digital map by the big data platform (5), and collecting the consumption level, the industry type, the season and the like of the region in a matching way; after a considerable amount of data is collected, the big data platform (5) integrates the data;

secondly, capacity adjustment is carried out, the position information determined by the positioning module (132) is uploaded to the big data platform (5) by the garbage recycling boxes (1) in each area in the city through the communication module (133), the occupation ratios of different types of garbage of the garbage recycling boxes (1) in each area are calculated by combining factors such as consumption level, industry type, season and the like through the big data platform (5) and a digital map, and the moving mechanisms (18) on two sides of the garbage recycling boxes (1) are controlled to move the movable partition plates (17) through the control module (134) according to the occupation ratios of the different types of garbage of the single garbage recycling box (1) relative to the total amount of the garbage, so that the capacity proportion in the box body (15) of the garbage recycling boxes (1) is controlled;

and step three, planning the position of the garbage recycling station (4), counting the proportion of different types of garbage relative to the total amount of the garbage in each area in the city by using a big data platform (5), marking the position with larger occupation amount of single type of garbage in a digital city map, and planning the position of the garbage recycling station (4) with the type of garbage near the position with larger occupation amount of the type of garbage.

7. The big data-based garbage classification and recycling management method according to claim 6, comprising an autonomous learning optimization function:

the autonomous learning optimization function: the method comprises the steps that various types of garbage ratio data of different areas are collected by a big data platform (5), an algorithm is obtained by combining statistical data of consumption levels, industry types, seasons and the like of the areas, data calculation is carried out on a single case by the aid of the algorithm, various types of garbage ratio data of the different areas are collected continuously at the same time, the process is repeated repeatedly, and the algorithm obtained by the statistical data of the big data platform (5) is optimized continuously.

8. The big data-based garbage classification and recycling management method according to claim 6, comprising a reproducible algorithm function:

the reproducible algorithm function: according to a data algorithm of certain city statistics, a data model based on consumption level, industry type, season and other data of each region of a city can be formed, the data model can be applied to other cities, the occupation ratio of different types of garbage relative to the total amount of garbage in each region of the city can be calculated according to the data model and the actual consumption level, industry type, season and other data of each region of the city, and the capacity of a garbage collection box (1) can be adjusted, the position of a garbage collection station (4) can be planned and the like.

9. The big data based garbage classification and recovery management method according to claim 6, comprising a garbage cleaning function:

the garbage cleaning function is as follows: when the image recognition device (14) recognizes that the garbage in the garbage collection box (1) is fully loaded, a communication module (133) informs a sanitation worker and a garbage transport vehicle (3), the sanitation worker opens the opening plate (153) through a handle (155), the control module (134) controls the speed reduction motors (1808) in the moving mechanisms (18) at the two sides of the garbage collection box (1) to rotate forwards and backwards respectively, drives the two movable partition plates (17) to move towards the two sides of the garbage collection box (1) respectively, pushes out different types of garbage in the garbage collection box (1) successively, cleans the garbage in the bottom brushes (173) of the movable partition plates (17) completely, and the garbage transport vehicle (3) filled with the garbage of the corresponding types by the sanitation worker.

10. The big data based garbage classification and recycling management method according to claim 6, comprising a recycling route planning function:

the recovery route planning function: when a single type of garbage exists in a city and a plurality of garbage recycling stations (4) exist, the garbage transport vehicle (3) is communicated with the garbage recycling stations (4) through the information receiving and sending terminal (2), position information and load data of the garbage recycling stations (4) are obtained, the garbage recycling station (4) with the shortest distance and the load not exceeding the standard is selected, and a running route of the garbage transport vehicle (3) is planned.

Technical Field

The application relates to the field of garbage classification, in particular to a garbage classification and recovery system and a classification and recovery management method based on big data.

Background

The garbage classification is the basis of the operation of garbage terminal treatment facilities, implements the household garbage classification, can effectively improve the urban and rural environment, and promotes the resource recycling.

CN202010855753.6 discloses a community garbage classification big data processing system and method based on the Internet, and the technical scheme is as follows: the system comprises a big data computing platform, a system processing terminal, a sanitation department pushing terminal, a refuse contractor pushing terminal and an information acquisition terminal; the big data computing platform is installed on the cloud server, and the system processing terminal, the environmental sanitation department pushing terminal, the refuse contractor pushing terminal and the information acquisition terminal are respectively connected with the cloud server through the Internet; the information acquisition terminal can be made into a mobile phone WeChat small program and is used for acquiring classification information of garbage to be thrown in the next throwing day of residents in a community in an area and uploading the information to the cloud server; the big data computing platform analyzes and computes data collected by the information collecting terminal, and respectively pushes analysis and computation results to a sanitation department and a community garbage contractor through a sanitation department push terminal and a garbage contractor push terminal; the system processing terminal is used for data management, operation and software development and updating of the system, and displays software on the manufactured terminal and uploads the software to the cloud server.

The community garbage classification big data processing system based on the internet has the following advantages: the garbage data in the collection area can be analyzed, and the yield, the type and the distribution of the garbage in the next period of time can be further predicted; and reasonably scheduling the environmental sanitation force on a scheduling platform based on the garbage type and quantity distribution information obtained by the analysis of the big data platform.

However, the internet-based community garbage classification big data processing system also has the following disadvantages: the space of various kinds of garbage in the garbage recycling bin cannot be fully utilized; the position of the garbage recycling station and the route of the garbage transport vehicle cannot be optimally adjusted, the distance between a partial area and the garbage recycling station is far, the transport distance and the transport time are too long, and the waste of the garbage transport cost is caused.

Therefore, there is a need for a garbage sorting and recycling system that optimizes the space for various types of garbage within the garbage collection bin, and optimally adjusts the position of the garbage collection station and the route of the garbage transport vehicle.

Disclosure of Invention

In order to solve the problem that space is extravagant, rubbish cost of transportation is extravagant in the rubbish collection box, this application provides a categorised recovery system of rubbish based on big data.

The application provides a waste classification recovery system based on big data, including rubbish collection box, information transceiver terminal, rubbish transport vehicle, rubbish recycle bin and big data platform:

the garbage collection box includes: the box body is arranged at the lower part of the garbage recycling box; the fixed partition plate is arranged in the box body in the middle and is fixedly connected with the box body; the movable partition plates are arranged in the box body, positioned on two sides of the fixed partition plate and movably connected with the box body; the moving mechanisms are arranged on two sides of the box body, are respectively in driving connection with the movable partition plates on the two sides and are electrically connected with the power supply and the control module; the communication module is connected with the big data platform through the Internet; the positioning module is electrically connected with the communication module and used for monitoring the position information of the garbage recycling bin and uploading data to the big data platform through the communication module; the image recognition device is used for recognizing the loading amount of different types of garbage in the garbage collection box and uploading data to the big data platform through the communication module;

the information receiving and sending terminal is respectively connected and communicated with the garbage transport vehicle, the garbage recycling station and the big data platform through the Internet;

the big data platform is connected with the garbage recycling bin through a communication module.

Further, the garbage recycling bin further comprises: the electric box is arranged on the side part of the garbage recycling box; the power supply is arranged in the electric box; the control module is arranged in the electric box and is electrically connected with the power supply; the voice module is arranged in the electric box and is electrically connected with the power supply; the ceiling is arranged above the box body and is fixedly connected with the ground; the solar panel is arranged on the upper part of the ceiling and is electrically connected with the power supply; the positioning module is arranged in the electric box and is electrically connected with the power supply; the communication module is arranged in the electric box and is electrically connected with the power supply; the image recognition device is arranged at the lower part of the ceiling, is electrically connected with the power supply and the control module, and is electrically connected with the voice module.

By adopting the technical scheme, the image recognition device can recognize the type of the garbage to be thrown in and prompt through the voice module, so that the situation of garbage throwing errors caused by misjudgment of the type of the garbage when people throw the garbage is prevented, and the accuracy of garbage classification recycling is improved.

Further, the box includes: the first sliding chutes are symmetrically arranged in the middle parts of two sides of the box body and are communicated with the moving mechanism and the movable partition plate; the fixed barrier includes: the second sliding chutes are symmetrically arranged in the middle parts of the two sides of the fixed partition plate; the movable partition includes: the connector is arranged on one side of the movable partition plate close to the inner wall of the box body and is in sliding connection with the first sliding groove of the box body; the pulley is arranged on one side of the movable partition plate, which is back to the inner wall of the box body, and is connected with the fixed partition plate in a sliding manner;

the moving mechanism includes: the sliding rail is arranged in the middle of the moving mechanism, and the horizontal height of the sliding rail is consistent with that of the first sliding groove; the first rotating shaft is arranged in the sliding rail, is connected with the sliding rail in a sliding manner, and is fixedly connected with the connector of the movable partition plate at one end; the rolling gear is sleeved on the first rotating shaft and is in rotating connection with the first rotating shaft; the first belt pulley is sleeved on the first rotating shaft and is in driving connection with the first rotating shaft; the rack is horizontally arranged in the middle of the moving mechanism, is positioned below the sliding rail and is meshed with the rolling gear; the limiting groove is vertically arranged at the lower part of the moving mechanism and is positioned below the rack; the speed reducing motor is arranged in the limiting groove, is connected with the limiting groove in a sliding manner, and is electrically connected with the power supply and the control module; the reset spring is vertically arranged at the lower part of the limit groove, the lower end of the reset spring is fixedly connected with the tail end of the lower part of the limit groove, and the upper end of the reset spring is fixedly connected with the speed reducing motor; the second rotating shaft is in driving connection with the speed reducing motor; the second belt pulley is sleeved on the second rotating shaft, is in driving connection with the second rotating shaft and is in transmission connection with the first belt pulley through a belt; and two ends of the support rod are respectively in rotating connection with the first rotating shaft and the second rotating shaft.

Through the technical scheme, the movable partition plate can be driven by the speed reduction motor to rotate forwards and backwards, the space of various kinds of garbage in the garbage recycling bin can be adjusted, the space in the garbage recycling bin is fully utilized, and the space waste is avoided.

Further, the box still includes: the upright columns are symmetrically arranged on the other two sides of the box body in the middle and are fixedly connected with the bottom of the box body; the opening plates are symmetrically arranged on two sides of the upright post and are rotationally connected with the bottom of the box body through hinges; the handle is arranged at the upper part of the opening plate and is fixedly connected with the opening plate;

the movable partition further includes: the brush is arranged at the bottom of the movable partition plate and is fixedly connected with the movable partition plate.

Through adopting above-mentioned technical scheme, open the opening plate, the gear motor in the control module control rubbish collection box both sides moving mechanism is the corotation earlier respectively afterwards the reversal, drives two movable partition boards and removes to the both sides of rubbish collection box successively respectively to different kind rubbish is released in the rubbish collection box successively, and cleans totally through movable partition board bottom brush, prevents to have the dead angle in the rubbish collection box, leads to rubbish can't clear away, has improved rubbish collection box and has clear away efficiency.

Furthermore, the length of the stay bar is smaller than the height difference between the slide rail and the lowest part of the limiting groove.

A garbage classification recycling management method based on big data comprises the following steps:

step one, integrating data, namely identifying the loading capacity of different types of garbage in garbage recycling boxes in each area in a city by an image identification device, calculating the proportion of the various types of garbage relative to the total amount of the garbage, uploading the proportion data to a big data platform through a communication module, determining the position information of the garbage recycling boxes in each area in the city by a positioning module, importing a city digital map by the big data platform, and collecting the consumption level, the industry type, the season and the like of the area in a matching way; after a considerable amount of data is collected, the big data platform integrates the data;

secondly, capacity adjustment is carried out, the position information determined by the positioning module is uploaded to a large data platform by the garbage recycling boxes in each area in the city through a communication module, the large data platform is matched with a digital map, the proportion of different types of garbage in the garbage recycling boxes in each area is calculated by combining factors such as consumption level, industry type, season and the like, and the control module controls the moving mechanisms on two sides of each garbage recycling box to move the movable partition plate according to the proportion of different types of garbage in a single garbage recycling box relative to the total amount of the garbage, so that the capacity proportion in the box body of each garbage recycling box is controlled;

and step three, planning the position of the garbage recycling station, counting the proportion of different types of garbage relative to the total amount of the garbage in each area in the city by a big data platform, marking the position with larger occupation amount of single type of garbage in a digital map of the city, and planning the position of the garbage recycling station with the type of garbage near the position with larger occupation amount of the type of garbage.

By adopting the technical scheme, the capacity ratio in the garbage recycling bin can be adjusted according to the space required by different types of garbage, the space in the garbage recycling bin is fully utilized, and the space waste is avoided; meanwhile, the position of the garbage recycling station is adjusted, so that the transportation distance and the transportation time of the garbage transportation vehicle can be reduced, and the transportation cost is reduced.

Further, the method also comprises an autonomous learning optimization function: the large data platform collects various types of garbage proportion data of different areas, an algorithm is obtained by combining statistical data of consumption level, industry type, season and the like of each area, then data calculation is carried out on a single case by using the algorithm, and meanwhile various types of garbage proportion data of different areas are collected continuously. The above processes are continuously and repeatedly circulated, and the algorithm obtained by the statistical data of the big data platform is continuously optimized.

By adopting the technical scheme, the algorithm accuracy of the large data platform can be continuously improved through continuous autonomous learning and optimization.

Further, the method also comprises a reproducible algorithm function: according to a data algorithm of certain city statistics, a data model based on consumption level, industry type, season and other data of each region of a city can be formed, the data model can be applied to other cities, the occupation ratio of different types of garbage relative to the total amount of the garbage in each region of the city is calculated according to the data model and the actual consumption level, the industry type, the season and other data of each region of the city, and the garbage collection box capacity adjustment, the garbage collection station position planning and the like are carried out.

By adopting the technical scheme, the data model of a certain city can be directly applied to another city, the process of collecting and integrating data at the initial operation stage of the system is reduced, and the utilization efficiency of the system is improved.

Further, still include the rubbish and clean the function: when the image recognition device recognizes that garbage in the garbage recycling bin is fully loaded, the image recognition device informs sanitation personnel and garbage transport vehicles through the communication module, the sanitation personnel open the opening plate through the handle, the control module controls the speed reduction motors in the moving mechanisms on two sides of the garbage recycling bin to rotate forwards and backwards respectively, drives the two movable partition plates to move towards two sides of the garbage recycling bin respectively and sequentially, pushes out different types of garbage in the garbage recycling bin sequentially, cleans the garbage completely through the brushes at the bottoms of the movable partition plates, and is loaded into the garbage transport vehicles corresponding to the types of garbage by the sanitation personnel.

By adopting the technical scheme, dead angles can be prevented from existing in the garbage collection box, so that garbage can not be removed, and the removing efficiency of the garbage collection box is improved.

Further, the method also comprises a recycling route planning function: when a single type of garbage exists in a city and a plurality of garbage recycling stations exist, the garbage transport vehicle is communicated with the garbage recycling stations through the information receiving and sending terminal to obtain position information and load data of the garbage recycling stations, the garbage recycling station with the shortest distance and the load not exceeding the standard is selected, and a running route of the garbage transport vehicle is planned.

By adopting the technical scheme, the transportation distance and the transportation time of the garbage transportation vehicle can be reduced, and the transportation cost is reduced.

To sum up, the application comprises the following beneficial technical effects:

1. the occupation ratios of different types of garbage in the garbage recycling bin are calculated through the big data platform, the capacity ratio in the garbage recycling bin is adjusted, the space in the garbage recycling bin is fully utilized, and the space waste is avoided;

2. the position with larger occupation of single-kind garbage is marked in the urban digital map through the big data platform, and the position of the garbage collection station is adjusted, so that the transportation distance and the transportation time of a garbage transportation vehicle can be reduced, and the transportation cost is reduced;

3. by continuous autonomous learning optimization, the algorithm accuracy of the large data platform can be continuously improved.

Drawings

Fig. 1 is a structural diagram of a big data based garbage classification recycling system according to an embodiment of the present application.

Fig. 2 is a structural diagram of a garbage collection box of a big data based garbage classification and collection system according to an embodiment of the present application.

Fig. 3 is a structural diagram of an electrical box of a big data based garbage classification recycling system according to an embodiment of the present application.

FIG. 4 is a partial enlarged view of a bin of a big data based garbage classification recycling system according to an embodiment of the present application.

FIG. 5 is a partial enlarged view of a fixed partition of a big data based garbage classification recycling system according to an embodiment of the present application.

FIG. 6 is an enlarged partial view of a movable partition of a big data based garbage classification recycling system according to an embodiment of the present application.

Fig. 7 is a structural diagram of a moving mechanism of a big data based garbage classification and collection system according to an embodiment of the present application.

Fig. 8 is a schematic diagram of an autonomous learning optimization function of a big data-based garbage classification recycling management method according to an embodiment of the present application.

Description of reference numerals:

the garbage collection box 1, the ceiling 11, the solar panel 12, the electric box 13, the power supply 131, the positioning module 132, the communication module 133, the control module 134, the voice module 135, the image recognition device 14, the box body 15, the first sliding chute 151, the upright post 152, the opening plate 153, the hinge 154, the handle 155, the fixed partition 16, the second sliding chute 161, the movable partition 17, the connector 171, the pulley 172, the brush 173, the moving mechanism 18, the sliding rail 1801, the first rotating shaft 1802, the rolling gear 1803, the first belt pulley 1804, the rack 1805, the limiting groove 1806, the return spring 1807, the reducing motor 1808, the second rotating shaft 1809, the second belt pulley 1805, the supporting rod 1811, the 1810, the power supply 131, the positioning module 132, the communication module 133, the control module 134, the voice module 135, the image recognition device 14, the box body 15, the first sliding chute 151, the upright post 152, the first belt pulley 1803, the first belt pulley 1804, the rack 1805, the limiting groove 1806, the return spring 1807, the reducing motor 1808, the second rotating shaft 1809, the second belt pulley 1810, the supporting rod 1811, the supporting rod 1810 and the supporting rod 1810,

The system comprises an information receiving and sending terminal 2, a garbage transport vehicle 3, a garbage recycling station 4 and a big data platform 5.

Detailed Description

The following description of the embodiments with reference to the drawings is provided to describe the embodiments, and the embodiments of the present application, such as the shapes and configurations of the components, the mutual positions and connection relationships of the components, the functions and working principles of the components, the manufacturing processes and the operation and use methods, etc., will be further described in detail to help those skilled in the art to more fully, accurately and deeply understand the inventive concepts and technical solutions of the present invention. For convenience of description, the directions mentioned in the present application shall be those shown in the drawings.

Referring to fig. 1 to 7, a garbage classification and recycling system based on big data includes a garbage recycling bin 1, an information receiving and sending terminal 2, a garbage transport vehicle 3, a garbage recycling bin 4, and a big data platform 5:

the garbage collection box 1 includes: a box body 15 arranged at the lower part of the garbage recycling box 1; the fixed partition plate 16 is arranged in the box body 15 in the middle and is fixedly connected with the box body 15; the movable partition plates 17 are arranged in the box body 15, positioned at two sides of the fixed partition plate 16 and movably connected with the box body 15; the moving mechanisms 18 are arranged on two sides of the box body 15, are respectively in driving connection with the movable partition boards 17 on the two sides, and are electrically connected with the power supply 131 and the control module 134; the communication module 133 is connected with the big data platform 5 through the internet; the positioning module 132 is electrically connected with the communication module 133 and is used for monitoring the position information of the garbage collection box 1 and uploading the data to the big data platform 5 through the communication module 133; the image recognition device 14 is used for recognizing the loading amount of different types of garbage in the garbage collection box 1 and uploading data to the big data platform 5 through the communication module 133;

the information receiving and sending terminal 2 is respectively connected and communicated with a garbage transport vehicle 3, a garbage recycling station 4 and a big data platform 5 through the internet;

the big data platform 5 is connected with the garbage recycling bin through a communication module 133.

The garbage collection box 1 further includes: the electric box 13 is arranged on the side part of the garbage recycling box 1; a power supply 131 disposed in the electric box 13; the control module 134 is arranged in the electric box 13 and is electrically connected with the power supply 131; the voice module 135 is arranged in the electric box 13 and is electrically connected with the power supply 131; the ceiling 11 is arranged above the box body 15 and is fixedly connected with the ground; a solar panel 12 disposed on the ceiling 11 and electrically connected to the power source 131; the positioning module 132 is arranged in the electric box 13 and electrically connected with the power supply 131; the communication module 133 is arranged in the electric box 13 and electrically connected with the power supply 131; the image recognition device 14 is disposed under the ceiling 11, and is electrically connected to the power source 131 and the control module 134, and is electrically connected to the voice module 135.

The case 15 includes: the first sliding chutes 151 are symmetrically arranged in the middle parts of two sides of the box body 15 and are communicated with the moving mechanism 18 and the movable partition plate 17; the fixed bulkhead 16 includes: the second sliding chutes 161 are symmetrically arranged in the middle of two sides of the fixed partition plate 16; the movable partition 17 includes: the connector 171 is arranged on one side of the movable partition 17 close to the inner wall of the box body 15 and is in sliding connection with the first sliding chute 151 of the box body 15; the pulley 172 is arranged on one side of the movable partition 17, which is back to the inner wall of the box body 15, and is connected with the fixed partition 16 in a sliding way;

the moving mechanism 18 includes: the sliding rail 1801 is arranged in the middle of the moving mechanism 18, and the horizontal height of the sliding rail 1801 is consistent with that of the first sliding groove 151; a first rotating shaft 1802 arranged in the sliding rail 1801, slidably connected to the sliding rail 1801, and having one end fixedly connected to the connector 171 of the movable partition 17; the rolling gear 1803 is sleeved on the first rotating shaft 1802 and is in rotating connection with the first rotating shaft 1802; the first belt pulley 1804 is sleeved on the first rotating shaft 1802 and is in driving connection with the first rotating shaft 1802; a rack 1805 horizontally arranged in the middle of the moving mechanism 18, located below the sliding rail 1801, and engaged with the rolling gear 1803; a limit groove 1806 vertically arranged at the lower part of the moving mechanism 18 and positioned below the rack 1805; the speed reducing motor 1808 is arranged in the limiting groove 1806, is connected with the limiting groove 1806 in a sliding manner, and is electrically connected with the power supply 131 and the control module 134; the reset spring 1807 is vertically arranged at the lower part of the limit groove 1806, the lower end of the reset spring is fixedly connected with the tail end of the lower part of the limit groove 1806, and the upper end of the reset spring is fixedly connected with the speed reducing motor 1808; a second rotating shaft 1809, which is in driving connection with the speed reducing motor 1808; a second belt pulley 1810 sleeved on the second rotating shaft 1809, in driving connection with the second rotating shaft 1809, and in driving connection with the first belt pulley 1804 through a belt; the strut 1811 has two ends respectively connected to the first rotating shaft 1802 and the second rotating shaft 1809.

The case 15 further includes: the upright posts 152 are symmetrically arranged on the other two sides of the box body 15 in the middle and are fixedly connected with the bottom of the box body 15; the opening plates 153 are symmetrically arranged on two sides of the upright post 152 and are rotatably connected with the bottom of the box body 15 through hinges 154; a handle 155 disposed on the upper portion of the opening plate 153 and fixedly connected to the opening plate 153;

the movable partition 17 further includes: and the brush 173 is arranged at the bottom of the movable partition 17 and is fixedly connected with the movable partition 17.

The length of the support rod 1811 is smaller than the height difference between the slide rail 1801 and the lowest part of the limit groove 1806.

A garbage classification recycling management method based on big data comprises the following steps:

step one, integrating data, namely identifying the loading capacity of different types of garbage in the garbage recycling boxes 1 in each area in the city by the image identification device 14, calculating the proportion of the various types of garbage relative to the total amount of the garbage, uploading the proportion data to the big data platform 5 through the communication module 133, determining the position information of the garbage recycling boxes 1 in each area in the city by the positioning module 132, importing a city digital map by the big data platform 5, and collecting the consumption level, the industry type, the season and the like of the area in a matching way; after a considerable amount of data is collected, the big data platform 5 integrates the data;

step two, capacity adjustment, namely uploading the position information determined by the positioning module 132 to a big data platform 5 through a communication module 133 by the garbage collection boxes 1 in each area in the city, calculating the proportion of different types of garbage in the garbage collection boxes 1 in each area by combining factors such as consumption level, industry type, season and the like by matching the big data platform 5 with a digital map, and controlling the moving mechanisms 18 at the two sides of the garbage collection boxes 1 to move the movable partition plates 17 by the control module 134 according to the calculated proportion of different types of garbage in a single garbage collection box 1 relative to the total amount of the garbage, so as to control the capacity proportion in the box body 15 of the garbage collection box 1;

and step three, planning the position of the garbage recycling station 4, counting the proportion of different types of garbage relative to the total amount of the garbage in each area in the city by using a big data platform 5, marking the position with larger occupation amount of single type of garbage in a digital map of the city, and planning the position of the garbage recycling station 4 with the type of garbage near the position with larger occupation amount of the type of garbage.

The system also comprises an autonomous learning optimization function: the big data platform 5 collects various garbage occupation ratio data of different areas, an algorithm is obtained by combining statistical data of consumption level, industry type, season and the like of each area, then data calculation is carried out on a single case by using the algorithm, and meanwhile various garbage occupation ratio data of different areas are collected continuously. The above process is continuously repeated and circulated, and the algorithm obtained by the statistical data of the big data platform 5 is continuously optimized.

Also included are replicable algorithm functions: according to a data algorithm of certain city statistics, a data model based on consumption level, industry type, season and other data of each region of a city can be formed, the data model can be applied to other cities, the occupation ratio of different types of garbage relative to the total amount of garbage in each region of the city can be calculated according to the data model and the actual consumption level, industry type, season and other data of each region of the city, and the capacity of the garbage collection box 1 can be adjusted, the position of the garbage collection station 4 can be planned and the like.

Still include the rubbish and clean the function: when the image recognition device 14 recognizes that the garbage in the garbage collection box 1 is fully loaded, the communication module 133 notifies the sanitation personnel and the garbage transport vehicle 3, the sanitation personnel opens the opening plate 153 through the handle 155, the control module 134 controls the speed reduction motors 1808 in the moving mechanisms 18 on the two sides of the garbage collection box 1 to respectively rotate forwards and backwards, the two movable partition plates 17 are driven to respectively move towards the two sides of the garbage collection box 1 in sequence, different types of garbage in the garbage collection box 1 are pushed out in sequence, the garbage is cleaned through the brushes 173 at the bottom of the movable partition plates 17, and the garbage transport vehicle 3 corresponding to the types of garbage is loaded into the sanitation personnel.

Also includes a recovery route planning function: when a single type of garbage exists in a city and a plurality of garbage recycling stations 4 exist, the garbage transport vehicle (3) is communicated with the garbage recycling stations 4 through the information receiving and sending terminal (2), position information and load data of the garbage recycling stations 4 are obtained, the garbage recycling station 4 with the shortest distance and the load not exceeding the standard is selected, and a running route of the garbage transport vehicle 3 is planned.

In the embodiment of the application, a working principle of a garbage classification and recovery system based on big data is as follows: the proportion data of various types of garbage in the garbage collection boxes in each area in the city relative to the total amount of the garbage are combined with position information and a digital map, the consumption level, the industry type, the season and the like of the area are collected, and after a large amount of data are integrated, the proportion of different types of garbage in each garbage collection box in each area in the city relative to the total amount of the garbage can be calculated:

according to the classification of industry types, when the area where the garbage recycling bin is located is identified as a factory, the harmful garbage, other garbage and recyclable garbage account for more than 80 percent, and the kitchen garbage accounts for less; when the area where the garbage recycling bin is located is identified as the catering industry, the kitchen garbage accounts for more than 80%, the recyclable garbage and other garbage account for less, and the harmful garbage is almost 0; when the area where the garbage recycling bin is located is identified as a residential area, kitchen garbage and other garbage account for more than 80%, and harmful garbage and recyclable garbage account for less;

according to the season classification, the summer weather is hot, the eating amount of melons and fruits is obviously increased compared with other seasons, and the ratio of kitchen garbage to the total amount of garbage is obviously increased; in winter and spring, the cold is high, the use amount of the facial tissue is obviously increased, and the proportion of other garbage is increased; in autumn, the fallen leaves of trees are more and belong to kitchen garbage, so the kitchen garbage accounts for a significant amount;

depending on the consumer level, the more economically a good is developed, the more packaging materials, disposable materials and supplies, the greater the proportion of other waste and recyclable waste.

And the positions of the garbage recycling stations of different types of garbage are planned near the position with larger occupation of the types of garbage, so that the transportation distance and the transportation time of a garbage transportation vehicle are reduced, and the transportation cost is reduced.

In the embodiment of the application, the type of garbage to be thrown into can be identified through the image identification device, and prompt is carried out through the voice module, so that the situation of garbage throwing errors caused by misjudgment of the type of garbage when people throw the garbage into is prevented, and the accuracy of garbage classification recycling is improved.

Through opening the opening plate, the control module controls the speed reduction motors in the moving mechanisms on the two sides of the garbage collection box to rotate forwards and backwards respectively, drives the two movable partition plates to move towards the two sides of the garbage collection box respectively and sequentially push out different types of garbage in the garbage collection box, cleans the garbage through the brushes at the bottoms of the movable partition plates, prevents dead angles from existing in the garbage collection box, leads to the fact that the garbage cannot be cleared, and improves the clearing efficiency of the garbage collection box.

By the aid of the autonomous learning optimization function, the algorithm accuracy of the large data platform can be continuously improved.

The present invention and its embodiments have been described above in an illustrative manner, and the description is not intended to be limiting, and the drawings are only one embodiment of the present invention, and the actual structure is not limited thereto. Therefore, if the person skilled in the art receives the teaching, the technical scheme and the embodiments similar to the technical scheme are not creatively designed without departing from the spirit of the invention, and the invention shall fall into the protection scope of the invention.