CN115034415A - Intelligent kitchen garbage recycling Internet of things system - Google Patents
Intelligent kitchen garbage recycling Internet of things system Download PDFInfo
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Abstract
The invention provides an intelligent kitchen garbage recycling Internet of things system, which comprises: the intelligent garbage can is arranged at each contracted merchant; the garbage recycling vehicle is used for recycling kitchen garbage stored in each intelligent garbage can; the Internet of things platform is in communication connection with the intelligent garbage can and the garbage recycling vehicle respectively; the Internet of things platform executes the following operations: acquiring the storage condition of kitchen waste in the intelligent garbage can in real time; determining an intelligent garbage can to be cleared based on kitchen garbage storage conditions; determining a first garbage clearing route based on the setting position of the intelligent garbage can to be cleared; and sending the first garbage clearing route to a garbage recycling vehicle. The intelligent kitchen waste recycling Internet of things system provided by the invention can be used for realizing the whole process management and the whole flow monitoring of kitchen waste sources, collection, transportation, disposal and recycled product utilization, improving the enterprise collection and transportation efficiency, ensuring the kitchen waste recycling efficiency and promoting the implementation of kitchen waste resource utilization and harmless treatment.
Description
Technical Field
The invention relates to the technical field of Internet of things, in particular to an intelligent kitchen garbage recycling Internet of things system.
Background
At present, the existing kitchen garbage recycling is carried out regularly or according to experience; the kitchen waste is often accumulated in some merchants, which is not favorable for the treatment of the kitchen waste of merchants, and sometimes the recycling cost is increased because of the running out or the too little kitchen waste.
Disclosure of Invention
One of the purposes of the invention is to provide an intelligent kitchen waste recycling internet-of-things system, which realizes the whole-process management and the whole-process monitoring of kitchen waste sources, collection, transportation, disposal and recycled product utilization, improves the enterprise collection and transportation efficiency, ensures the kitchen waste recycling efficiency, and promotes the implementation of kitchen waste resource utilization and harmless treatment.
The embodiment of the invention provides an intelligent kitchen garbage recycling Internet of things system, which comprises:
the intelligent garbage can is arranged at each signed merchant and used for storing kitchen garbage by each signed merchant;
the garbage recycling vehicle is used for recycling kitchen garbage stored in each intelligent garbage can;
the Internet of things platform is in communication connection with the intelligent garbage can and the garbage recycling vehicle respectively;
the Internet of things platform executes the following operations:
acquiring the storage condition of kitchen waste in the intelligent garbage can in real time;
determining an intelligent garbage can to be cleared based on kitchen garbage storage conditions;
determining a first garbage clearing route based on the setting position of the intelligent garbage can to be cleared;
and sending the first garbage clearing route to a garbage recycling vehicle.
Preferably, the intelligent garbage bin includes:
the barrel body is used for storing kitchen garbage;
a barrel cover;
the RFID electronic tag is arranged on the outer side of the barrel body; the RFID electronic tag is used for storing the model of the barrel and attributing merchant information;
the RFID reader is arranged in the barrel cover;
the volume detection module is arranged on the lower end face of the barrel cover and used for detecting the total amount of kitchen garbage stored in the barrel body;
and the management all-in-one machine is in communication connection with the capacity detection module, the RFID reader and the Internet of things platform.
Preferably, the capacity detection module includes: an acoustic wave probe.
Preferably, the management all-in-one machine comprises: the cloud box, the camera and the power supply device;
the cloud box includes: the system comprises a processor and a first communication module;
the power supply device is electrically connected with the processor, the first communication module and the camera respectively; the processor is respectively and electrically connected with the camera, the capacity detection module, the RFID reader and the communication module; the processor is in communication connection with the Internet of things platform through the first communication module.
Preferably, the processor performs the following operations:
reading information stored in an RFID label on the outer side of the barrel body through an RFID reader at a preset first time interval, and sending the obtained information to an Internet of things platform; the Internet of things platform compares the acquired information with the information acquired last time, and when the acquired information is different from the information acquired last time, preset early warning information is sent to preset staff;
and/or the presence of a gas in the gas,
acquiring a first image of the barrel body and the barrel cover shot by the camera through the camera;
determining the joint state of the barrel cover and the barrel body based on the first image;
when the joint state meets the preset test condition, acquiring detection data detected by the capacity detection module through the capacity detection module;
determining a volume of kitchen waste within the bin based on the probe data and the engagement status;
and/or the presence of a gas in the gas,
identifying persons in the first image;
when it is recognized that a person passes, a first image containing the person is extracted and the extracted first image is stored.
Preferably, the intelligent garbage can further comprises:
and the biological enzyme spraying device is arranged on the lower end face of the barrel cover.
Preferably, the garbage collection vehicle includes:
the positioning module is used for acquiring positioning information;
the vehicle state monitoring module is used for acquiring the running state information of the vehicle;
the personnel monitoring module is used for acquiring a monitoring image of a driver;
the control module is electrically connected with the positioning module, the vehicle state detection module and the personnel monitoring module respectively;
and the second communication module is electrically connected with the control module and is used for being in communication connection with the Internet of things platform.
Preferably, the internet of things platform further performs the following operations when the garbage collection vehicle completes each garbage collection task in the first garbage collection route:
acquiring the garbage recycling condition in the garbage recycling vehicle;
analyzing the garbage recycling situation, and determining the residual capacity of the garbage recycling vehicle;
when the residual capacity is larger than a preset capacity threshold value, acquiring the current position of the garbage recycling vehicle;
determining a setting position of the intelligent garbage can which can be carried along based on the current position and the residual capacity;
generating a second garbage clearing route based on the setting position of the intelligent garbage can which can be carried along;
and sending the second garbage clearing route to a garbage recycling vehicle.
Preferably, the internet of things platform determines the setting position of the intelligent trash can which can be carried along based on the current position and the residual capacity, and executes the following operations:
constructing a virtual map of the garbage storage of the intelligent garbage can; each intelligent garbage can corresponds to each garbage recycling point in the virtual map;
deleting the garbage collection points corresponding to the garbage collection tasks in each dispatched first garbage collection route from the virtual map to form a reference map;
determining a first coordinate point corresponding to the current position of the garbage collection vehicle in a reference map;
determining a second coordinate point of the garbage collection station corresponding to the first garbage clearing route in the reference map;
taking the second coordinate point as a center, taking the distance from the first coordinate point to the second coordinate point as a radius, and taking a semicircular area close to the first coordinate point as an analysis area; the analysis area is symmetrical by a connecting line of the first coordinate point and the second coordinate point;
acquiring the garbage storage of each garbage recycling point in the analysis area;
determining a plurality of pliable waste recovery points based on the remaining capacity and the waste inventory;
and determining the setting position of the intelligent garbage can which can be carried along based on the garbage recycling point.
Preferably, based on the setting position of the intelligent garbage can that can be taken along, a second garbage clearing route is generated, which comprises the following steps:
determining the garbage storage of the garbage recycling points corresponding to the setting positions of the intelligent garbage cans which can be carried along;
arranging and combining the garbage stocks to construct a plurality of sets;
calculating the total amount of garbage of each set;
extracting a set of which the total garbage amount is less than or equal to the residual capacity as a reference group;
constructing a reference route corresponding to each reference group based on the position of each garbage recycling point in each reference group;
acquiring historical monitoring data of each garbage recovery point in each reference group;
determining the time for the garbage collection vehicle to move to each garbage collection point in each reference group;
extracting historical monitoring data based on time to obtain prediction data;
inputting the predicted data into a preset first neural network model to obtain fluctuation probability;
constructing evaluation data of each reference group based on the fluctuation probability of each garbage recovery point in each reference group, the reference route corresponding to each reference group, and the garbage stock and the residual capacity of each garbage recovery point in each reference group;
extracting the features of the evaluation data based on a preset feature extraction template to obtain a plurality of feature values;
inputting the characteristic values into a preset second neural network model, and acquiring evaluation values corresponding to all reference groups;
and taking the reference route corresponding to the reference group with the largest evaluation value and larger than the preset evaluation threshold value as a second garbage cleaning route.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by the practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
fig. 1 is a schematic diagram of an intelligent kitchen garbage recycling internet of things system in the embodiment of the invention.
Detailed Description
The preferred embodiments of the present invention will be described in conjunction with the accompanying drawings, and it will be understood that they are described herein for the purpose of illustration and explanation and not limitation.
The embodiment of the invention provides an intelligent kitchen garbage recycling internet of things system, which comprises the following components as shown in figure 1:
the intelligent garbage can 1 is arranged at each signed merchant and used for storing kitchen waste by each signed merchant;
at least one garbage recycling vehicle 2 for recycling kitchen garbage stored in each intelligent garbage can 1;
the Internet of things platform 3 is in communication connection with the intelligent garbage can 1 and the garbage recycling vehicle 2 respectively;
the internet of things platform 3 performs the following operations:
acquiring the storage condition of kitchen waste in the intelligent garbage can 1 in real time;
determining an intelligent garbage can 1 to be cleared based on kitchen garbage storage conditions;
determining a first garbage clearing route based on the setting position of the intelligent garbage can 1 to be cleared;
the first garbage disposal route is sent to the garbage collection vehicle 2.
The working principle and the beneficial effects of the technical scheme are as follows:
the intelligent garbage can 1 is arranged at each contracted commercial tenant, the commercial tenant dumps the kitchen waste into the intelligent garbage can 1, the intelligent garbage can 1 reports the storage condition of the garbage in the can to the Internet of things platform 3, the Internet of things platform 3 arranges and plans the garbage recycling vehicle 2 to recycle the garbage according to the storage condition of the garbage in the intelligent garbage can 1, and the kitchen waste is timely and efficiently recycled by monitoring the storage condition of the kitchen waste through the intelligent garbage can 1; wherein, the step of arranging the recovery of the garbage recovery vehicle 2 is specifically: acquiring the storage condition of kitchen waste in the intelligent garbage can 1 in real time; determining an intelligent garbage can 1 to be cleared based on kitchen garbage storage conditions; determining a first garbage clearing route based on the setting position of the intelligent garbage can 1 to be cleared; sending the first garbage cleaning route to the garbage collection vehicle 2; this step is mainly to idle rubbish recovery car 2 of berthhing from the garbage collection station, through the storage condition according to intelligent garbage bin 1, plan out first clear route, go according to first rubbish clear route as rubbish recovery car 2, and with the rubbish recovery back of each rubbish recovery point (being intelligent garbage bin 1) on the first rubbish clear route, return the garbage collection station again, through the storage condition of the surplus rubbish in kitchen of control merchant, realize in time dispatching rubbish recovery car 2 and retrieve, improve the collection and transportation efficiency of enterprise, the efficiency of guarantee kitchen garbage recovery.
The intelligent kitchen waste recycling Internet of things system provided by the invention can be used for realizing the whole process management and the whole flow monitoring of kitchen waste sources, collection, transportation, disposal and recycled product utilization, improving the enterprise collection and transportation efficiency, ensuring the kitchen waste recycling efficiency and promoting the implementation of kitchen waste resource utilization and harmless treatment.
In one embodiment, the internet of things platform 3 determines the intelligent trash can 1 to be cleared based on the kitchen garbage storage condition, and performs the following operations:
determining the total amount of garbage in the intelligent garbage can 1 and the capacity of the intelligent garbage can 1;
when the ratio of the total amount of the garbage to the capacity of the intelligent garbage can 1 is larger than a preset first ratio threshold (for example: 3/4), setting the intelligent garbage can 1 to be cleared;
and/or the presence of a gas in the atmosphere,
analyzing historical monitoring data of each intelligent garbage can 1, and determining the time of each intelligent garbage can 1 to dump each day and the amount of garbage dumped each time;
when the dumping time passes a preset first time (for example, one hour), and the ratio of the total garbage amount to the capacity of the intelligent garbage can 1 is greater than a preset second ratio threshold (for example, 2/3), setting the intelligent garbage can 1 to be cleared;
and/or the presence of a gas in the atmosphere,
analyzing historical monitoring data of each intelligent garbage can 1, and determining the time of each intelligent garbage can 1 to dump each day and the amount of garbage dumped each time; for example: the pouring times per day in the historical monitoring data can be averaged as the determined time of pouring per day; averaging the amount of the garbage dumped every day in the historical monitoring data to serve as the determined amount of the garbage dumped each time; furthermore, the garbage dumping time and the garbage dumping amount of 7 days per week can be determined in a grouping mode from Monday to Sunday; during specific analysis, a converged neural network model can be trained and analyzed based on a large amount of data in advance, and then the pouring time per day and the poured garbage amount are determined;
and (3) setting the intelligent garbage can 1 to be cleared when the ratio of the sum of the total garbage amount in the current intelligent garbage can 1 and the determined garbage amount to be dumped (i.e. the garbage amount per dumping analyzed through historical data) to the capacity of the intelligent garbage can 1 is larger than or equal to a third ratio threshold (e.g. 4/5) before the dumping time and a preset second time (e.g. one hour).
The working principle and the beneficial effects of the technical scheme are as follows:
when confirming the intelligent garbage bin 1 of waiting to clear, mainly adopt three aspects, first: monitoring the total amount of the garbage in real time based on a first ratio threshold value; secondly, the method comprises the following steps: analyzing the garbage monitoring data of each intelligent garbage can 1, and determining the dumping time and the dumping amount of a merchant; after the dumping time, based on the second proportion threshold, the intelligent garbage can 1 to be cleared is determined, and the third is that: the garbage monitoring data of each intelligent garbage can 1 is also analyzed, and the dumping time and the dumping amount of a merchant are determined; determining whether the ratio of the sum of the total amount of the garbage in the intelligent garbage can 1 and the determined amount of the garbage to be dumped (namely the amount of the garbage per dump analyzed by historical data) to the capacity of the intelligent garbage can 1 is larger than or equal to a third ratio threshold value or not before the dumping time; the follow-up surplus capacity that can have sufficient intelligent garbage bin 1 of assurance trade company emptys rubbish.
In one embodiment, the intelligent trash can 1 includes:
the barrel body is used for storing kitchen garbage;
a barrel cover;
the RFID electronic tag is arranged on the outer side of the barrel body; the RFID electronic tag is used for storing the model of the barrel and attributing merchant information;
the RFID reader is arranged in the barrel cover;
the volume detection module is arranged on the lower end face of the barrel cover and used for detecting the total amount of kitchen garbage stored in the barrel body;
and the management all-in-one machine is in communication connection with the capacity detection module, the RFID reader and the Internet of things platform 3.
The working principle and the beneficial effects of the technical scheme are as follows:
the information such as the code and the loading capacity of the intelligent garbage can 1 is read in real time through the RFID reading module and the capacity detection module, and the capacity detection module monitors the total amount of kitchen garbage in real time. The barrel body can be made of plastics, and the barrel cover is made of corrosion-resistant materials such as stainless steel; the barrel body and the barrel cover can be detached, the barrel body can be directly replaced after the barrel body is damaged, and when the barrel body is recovered, the barrel cover is taken away by a worker, and garbage in the barrel body is dumped and recovered.
In one embodiment, the capacity detection module includes: an acoustic wave probe. The sound wave detector can adopt a double-head sound wave detector, the depth of the barrel is detected once in 10 minutes, and data are transmitted to the management all-in-one machine through a data transmission terminal in a 485 bus mode and are sent to the Internet of things platform 3; the sound wave detector transmits detection waves to be reflected when the detection waves meet the liquid level in the barrel body, so that the height of the liquid level from the barrel cover is determined, the depth of kitchen garbage is determined according to the depth of the barrel body and the height of the liquid level from the barrel cover, and the total amount is determined.
In one embodiment, a management kiosk includes: the cloud box, the camera and the power supply device;
the cloud box includes: the system comprises a processor and a first communication module;
the power supply device is electrically connected with the processor, the first communication module and the camera respectively; the processor is respectively and electrically connected with the camera, the capacity detection module, the RFID reader and the communication module; the processor is in communication connection with the Internet of things platform 3 through the first communication module.
Wherein the processor performs the following operations:
reading information stored in an RFID label on the outer side of the barrel body through an RFID reader at a preset first time interval, and sending the obtained information to the Internet of things platform 3; the Internet of things platform 3 compares the acquired information with the information acquired last time, and when the acquired information is different from the information acquired last time, preset early warning information is sent to preset staff;
and/or the presence of a gas in the gas,
acquiring a first image of the barrel body and the barrel cover shot by the camera through the camera;
determining the joint state of the barrel cover and the barrel body based on the first image;
when the joint state meets the preset test condition, acquiring detection data detected by the capacity detection module through the capacity detection module;
determining a volume of kitchen waste within the bin based on the probe data and the engagement status;
and/or the presence of a gas in the gas,
identifying persons in the first image;
when it is recognized that a person passes, a first image containing the person is extracted and the extracted first image is stored.
The working principle and the beneficial effects of the technical scheme are as follows:
the cloud box is used for receiving data sent by the data terminals of the peripheral intelligent garbage cans 1 and uploading the data to the Internet of things platform 3, and one management all-in-one machine can be connected with a plurality of garbage cans. The camera supports human-shaped detection and infrared camera shooting functions, more than 200 million pixels are used, the camera monitors the position of the garbage can in daily life, if a system monitors abnormal behaviors such as abnormal opening of an intelligent can cover, undetected data terminals or entering of a person into an area, automatic photographing and video recording are carried out for 1min and are sent to the Internet of things platform 3, the daily video storage capacity is prefabricated into 15-day video, and remote video recording checking or live broadcast video checking can be supported; the prefabricated multiunit power supply unit can be a plurality of intelligent garbage bin 1 power supplies simultaneously to be provided with the work pilot lamp. The processor acquires a first image of the barrel body and the barrel cover shot by the camera through the camera; determining the joint state of the barrel cover and the barrel body based on the first image; when the joint state meets a preset test condition, acquiring detection data detected by a capacity detection module through the capacity detection module; based on the detection data and the engagement state, a volume of kitchen waste within the bin is determined. When the volume of kitchen garbage is determined through detection data of the volume detection module, the determination of the joint state is introduced, and the measurement accuracy is directly influenced by whether the joint of the barrel cover and the barrel body is normal or not because the volume detection module is arranged on the barrel cover;
wherein the processor determines the joint state of the barrel cover and the barrel body based on the first image, and comprises: and comparing the first image with a preset image comparison library, and determining that the joint state meets the preset test condition when a comparison coincidence item exists. Furthermore, a data processing model stored correspondingly to the comparison coincidence item is called, the detection data is processed, and the volume of the kitchen waste is determined. Mainly when the barrel cover is positioned above the barrel body in parallel, the detected distance is the distance from the liquid level to the barrel cover; when the barrel cover and the barrel body form a certain angle, the influence of the angle needs to be considered; the angle is determined mainly by determining the correlation of the comparison coincidence items in the image comparison library; the data processing model is mainly constructed according to different angles between the barrel cover and the barrel body, so that the distance between the liquid level and the upper end face of the barrel body is determined at different angles, and the accuracy of determining kitchen waste is improved.
In one embodiment, the intelligent trash can 1 further includes:
and the biological enzyme spraying device is arranged on the lower end face of the barrel cover. Biological enzyme sprinkler accomplishes regularly, the ration sprays the surplus rubbish in top layer kitchen in the bucket, realizes biological harmless going to smell, avoids the smell to pollute, avoids breeding the bacterium. For example: automatic spraying is realized by regularly controlling the opening of a spraying pump of the biological enzyme spraying device.
In one embodiment, the garbage collection vehicle 2 includes:
the positioning module is used for acquiring positioning information; the positioning module comprises a Beidou positioning module, a GPS positioning module and the like;
the vehicle state monitoring module is used for acquiring the running state information of the vehicle; the vehicle state detection module includes: the data reading device is connected to the vehicle-mounted computer and used for reading the driving data of the vehicle-mounted computer, such as: oil mass, mileage, etc.;
the personnel monitoring module is used for acquiring a monitoring image of a driver; the personnel monitoring module includes: the camera is arranged in the cab, and monitoring and face recognition are realized through the camera;
the control module is electrically connected with the positioning module, the vehicle state detection module and the personnel monitoring module respectively;
and the second communication module is electrically connected with the control module and is used for being in communication connection with the Internet of things platform 3.
The working principle and the beneficial effects of the technical scheme are as follows:
the garbage collection vehicle 2 is connected to the Internet of things platform 3, so that the position, the driving mileage, the running track, the driver, the driving time, the oil consumption, the illegal driving behaviors of the personnel and the like of the vehicle can be monitored in the whole process. The vehicle state monitoring module further comprises a weighing device, and is used for weighing the total amount of garbage in the vehicle, recording the garbage recycling amount of a merchant when the garbage is recycled, and providing a data basis for subsequent settlement.
In one embodiment, the internet of things platform 3 further performs the following operations when the garbage collection vehicle 2 completes each garbage collection task in the first garbage collection route:
acquiring the garbage recycling condition in the garbage recycling vehicle 2;
analyzing the garbage recycling situation and determining the residual capacity of the garbage recycling truck 2;
when the residual capacity is larger than a preset capacity threshold value, acquiring the current position of the garbage collection vehicle 2;
determining the setting position of the intelligent garbage can 1 which can be carried along based on the current position and the residual capacity;
generating a second garbage clearing route based on the setting position of the intelligent garbage can 1 which can be carried along;
the second waste collection route is sent to the waste collection vehicle 2.
The working principle and the beneficial effects of the technical scheme are as follows:
when actually carrying out first rubbish clearance route, because reasons such as the error of evaporation and upload data, exist when rubbish recovery car 2 retrieves and plays the rubbish of each rubbish recovery point on the first rubbish clearance route, still have great residual capacity, consequently when rubbish recovery car 2 has executed each rubbish recovery task in the first rubbish clearance route, to the analysis of the residual capacity of rubbish recovery car 2 and the rubbish volume of intelligent garbage bin 1 of management and control, confirm whether can take the way to retrieve, when having the way to retrieve, carry out the generation of second rubbish clearance route, improved the utilization efficiency of rubbish recovery car 2.
In one embodiment, the internet of things platform 3 determines the setting position of the handy intelligent trash can 1 based on the current position and the remaining capacity, and performs the following operations:
constructing a virtual map of the garbage storage of the intelligent garbage can 1; each intelligent garbage can 1 corresponds to each garbage recycling point in the virtual map; the garbage storage of the intelligent garbage can 1 can be monitored by adopting a virtual map at ordinary times;
deleting the garbage collection points corresponding to the garbage collection tasks in the distributed first garbage collection routes from the virtual map to form a reference map; the influence of the garbage recycling points on the dispatched first garbage clearing route on the generation of the second garbage clearing route is avoided;
determining a first coordinate point corresponding to the current position of the garbage collection vehicle 2 in a reference map;
determining a second coordinate point of the garbage collection station corresponding to the first garbage clearing route in the reference map;
taking the second coordinate point as a center, taking the distance from the first coordinate point to the second coordinate point as a radius, and taking a semicircular area close to the first coordinate point as an analysis area; the analysis area is symmetrical by a connecting line of the first coordinate point and the second coordinate point; through the determination of the analysis area, the waste of the recovery time and resources of the garbage recovery vehicle 2 caused by the fact that the garbage recovery point corresponding to the second garbage cleaning route falls at the reverse position of the garbage recovery point is avoided;
acquiring the garbage storage of each garbage recycling point in the analysis area;
determining a plurality of pliable waste recovery points based on the remaining capacity and the waste inventory; when the garbage storage is less than or equal to the residual capacity, determining that the garbage storage can be carried smoothly;
and determining the setting position of the intelligent garbage can 1 which can be carried along based on the garbage recycling point.
Wherein, based on can be along with the position that sets up of intelligent garbage bin 1 of taking, generate the route of clearing away of second rubbish, include:
determining the garbage storage of the garbage recycling points corresponding to the setting positions of the intelligent garbage cans 1 which can be carried along;
arranging and combining the garbage stocks to construct a plurality of sets; the collection can comprise one garbage collection point or a plurality of garbage collection points;
calculating the total amount of garbage of each set;
extracting a set with the total garbage amount less than or equal to the residual capacity as a reference group;
constructing a reference route corresponding to each reference group based on the position of each garbage recycling point in each reference group;
acquiring historical monitoring data of each garbage recovery point in each reference group;
determining the time for the garbage collection vehicle 2 to move to each garbage collection point in each reference group;
extracting historical monitoring data based on time to obtain prediction data;
inputting the predicted data into a preset first neural network model to obtain fluctuation probability; the first neural network model is subjected to a large amount of data training convergence in advance and is used for predicting the change probability (namely fluctuation probability) of the total garbage amount in the intelligent garbage can 1 in the time period of the arrival time of the garbage collection vehicle 2 through historical data, and the larger the change probability is, the larger the probability of the increase of the total garbage amount is when the garbage collection vehicle 2 arrives;
constructing evaluation data of each reference group based on the fluctuation probability of each garbage recovery point in each reference group, the reference route corresponding to each reference group, and the garbage stock and the residual capacity of each garbage recovery point in each reference group;
performing feature extraction on the evaluation data based on a preset feature extraction template to obtain a plurality of feature values; the characteristic values include: the difference value between the total quantity of the garbage stock and the residual capacity, the number of the garbage collection points in the reference set, the fluctuation probability of each garbage collection point, the total length of the reference route and the like.
Inputting the characteristic values into a preset second neural network model, and acquiring evaluation values corresponding to all reference groups; the second neural network model is subjected to a large amount of data training convergence in advance and is used for evaluating the reference group through evaluation data to obtain an evaluation value; overall, the fewer the number of points of garbage collection within the reference group, the higher the evaluation value; the closer the total amount of the garbage stock and the residual capacity are, the higher the evaluation value is; the shorter the total length of the reference route is, the higher the evaluation value is; the lower the fluctuation probability, the higher the evaluation value;
and taking the reference route corresponding to the reference group with the largest evaluation value and larger than the preset evaluation threshold value as a second garbage cleaning route. And screening each reference route through the evaluation value to ensure the stability and high efficiency of the recovery of each recovery task point of the second garbage clearing route.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (10)
1. The utility model provides an intelligence kitchen garbage recovery thing networking systems which characterized in that includes:
the intelligent garbage can is arranged at each signed merchant and used for storing kitchen garbage by each signed merchant;
the garbage recycling vehicle is used for recycling kitchen garbage stored in each intelligent garbage can;
the Internet of things platform is in communication connection with the intelligent garbage can and the garbage recycling vehicle respectively;
the Internet of things platform executes the following operations:
acquiring the storage condition of kitchen waste in the intelligent garbage can in real time;
determining an intelligent garbage can to be cleared based on the kitchen waste storage condition;
determining a first garbage clearing route based on the setting position of the intelligent garbage can to be cleared;
and sending the first garbage clearing route to the garbage recycling vehicle.
2. The intelligent kitchen waste recycling internet of things system of claim 1, wherein the intelligent garbage can comprises:
the barrel body is used for storing kitchen garbage;
a barrel cover;
the RFID electronic tag is arranged on the outer side of the barrel body; the RFID electronic tag is used for storing the type of the bucket and attributing merchant information;
an RFID reader disposed within the drum lid;
the volume detection module is arranged on the lower end face of the barrel cover and used for detecting the total amount of kitchen garbage stored in the barrel body;
and the management all-in-one machine is in communication connection with the capacity detection module, the RFID reader and the Internet of things platform.
3. The intelligent kitchen waste recycling internet of things system of claim 2, wherein the capacity detection module comprises: an acoustic wave probe.
4. The intelligent kitchen waste recycling internet of things system of claim 2, wherein the all-in-one management machine comprises: the cloud box, the camera and the power supply device;
the cloud box includes: the system comprises a processor and a first communication module;
the power supply device is electrically connected with the processor, the first communication module and the camera respectively; the processor is respectively and electrically connected with the camera, the capacity detection module, the RFID reader and the communication module; the processor is in communication connection with the Internet of things platform through the first communication module.
5. The intelligent kitchen waste recycling internet of things system of claim 4, wherein the processor performs the following operations:
reading information stored in the RFID tag on the outer side of the barrel body by the RFID reader at a preset first time interval, and sending the obtained information to an Internet of things platform; the Internet of things platform compares the acquired information with the information acquired last time, and when the acquired information is different from the information acquired last time, preset early warning information is sent to preset workers;
and/or the presence of a gas in the gas,
acquiring a first image of the barrel body and the barrel cover shot by the camera through the camera;
determining a coupling state of the tub cover and the tub body based on the first image;
when the joint state meets a preset test condition, acquiring detection data detected by the capacity detection module through the capacity detection module;
determining a volume of kitchen waste within the bin based on the probe data and the engagement status;
and/or the presence of a gas in the atmosphere,
identifying a person in the first image;
when it is recognized that a person passes, a first image containing the person is extracted and the extracted first image is stored.
6. The intelligent kitchen waste recycling internet of things system of claim 2, wherein said intelligent garbage can further comprises:
and the biological enzyme spraying device is arranged on the lower end surface of the barrel cover.
7. The intelligent kitchen waste recycling internet of things system of claim 1, wherein the waste recycling cart comprises:
the positioning module is used for acquiring positioning information;
the vehicle state monitoring module is used for acquiring the running state information of the vehicle;
the personnel monitoring module is used for acquiring a monitoring image of a driver;
the control module is electrically connected with the positioning module, the vehicle state detection module and the personnel monitoring module respectively;
and the second communication module is electrically connected with the control module and is used for being in communication connection with the Internet of things platform.
8. The intelligent kitchen waste recycling internet of things system of claim 1, wherein the internet of things platform further performs the following operations when the waste recycling vehicle completes each waste recycling task in the first waste disposal route:
acquiring the garbage recycling condition in the garbage recycling vehicle;
analyzing the garbage recycling situation, and determining the residual capacity of the garbage recycling vehicle;
when the residual capacity is larger than a preset capacity threshold value, acquiring the current position of the garbage collection vehicle;
determining a setting position of the intelligent garbage can which can be carried along based on the current position and the residual capacity;
generating a second garbage clearing route based on the setting position of the intelligent garbage can which can be carried along;
and sending the second garbage clearing route to the garbage recycling vehicle.
9. The intelligent kitchen waste recycling internet of things system of claim 8, wherein the internet of things platform determines a setting position of the portable intelligent garbage can based on the current position and the remaining capacity, and performs the following operations:
constructing a virtual map of the garbage storage of the intelligent garbage can; each intelligent garbage can corresponds to each garbage recycling point in the virtual map;
deleting the garbage collection points corresponding to the garbage collection tasks in the assigned first garbage collection routes from the virtual map to form a reference map;
determining a first coordinate point in the reference map corresponding to the current position of the garbage collection vehicle;
determining a second coordinate point of the garbage collection station corresponding to the first garbage clearing route in the reference map;
taking the second coordinate point as a center, taking the distance from the first coordinate point to the second coordinate point as a radius, and taking a semicircular area close to the first coordinate point as an analysis area; the analysis area is symmetrical with a connecting line of the first coordinate point and the second coordinate point;
acquiring the garbage stock of each garbage recycling point in the analysis area;
determining a plurality of pliable waste recovery points based on the remaining capacity and the inventory of waste;
and determining the setting position of the intelligent garbage can which can be carried along based on the garbage recycling point.
10. The intelligent kitchen waste recycling internet of things system of claim 9, wherein generating a second waste disposal route based on a location of a streamable intelligent waste bin comprises:
determining the garbage stock of a garbage recycling point corresponding to the setting position of each portable intelligent garbage can;
arranging and combining the garbage stocks to construct a plurality of sets;
calculating the total amount of garbage of each set;
extracting a set of which the total garbage amount is less than or equal to the residual capacity to serve as a reference group;
constructing a reference route corresponding to each reference group based on the position of each garbage recycling point in each reference group;
acquiring historical monitoring data of each garbage recovery point in each reference group;
determining the time for the garbage collection vehicle to move to each garbage collection point in each reference group;
extracting the historical monitoring data based on the time to obtain predicted data;
inputting the prediction data into a preset first neural network model to obtain fluctuation probability;
constructing evaluation data of each reference group based on the fluctuation probability of each garbage collection point in each reference group, the reference route corresponding to each reference group, the garbage stock and the residual capacity of each garbage collection point in each reference group;
extracting the features of the evaluation data based on a preset feature extraction template to obtain a plurality of feature values;
inputting the characteristic values into a preset second neural network model, and acquiring evaluation values corresponding to all reference groups;
and taking the reference route corresponding to the reference group with the maximum evaluation value and larger than a preset evaluation threshold value as the second garbage cleaning route.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115545574A (en) * | 2022-11-30 | 2022-12-30 | 北京梅凯尼克环保科技有限公司 | Intelligent garbage receiving and transporting processing method and system based on Internet of things |
| CN116862088A (en) * | 2023-07-06 | 2023-10-10 | 浙江宏远智能科技有限公司 | Intelligent community service system based on information acquisition |
| CN117284663A (en) * | 2023-11-04 | 2023-12-26 | 北京安岭生态建设有限公司 | Garden garbage treatment system and method |
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2022
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115545574A (en) * | 2022-11-30 | 2022-12-30 | 北京梅凯尼克环保科技有限公司 | Intelligent garbage receiving and transporting processing method and system based on Internet of things |
| CN116862088A (en) * | 2023-07-06 | 2023-10-10 | 浙江宏远智能科技有限公司 | Intelligent community service system based on information acquisition |
| CN116862088B (en) * | 2023-07-06 | 2024-05-24 | 上海海阳大健康产业集团股份有限公司 | Intelligent community service system based on information acquisition |
| CN117284663A (en) * | 2023-11-04 | 2023-12-26 | 北京安岭生态建设有限公司 | Garden garbage treatment system and method |
| CN117284663B (en) * | 2023-11-04 | 2024-05-24 | 北京安岭生态建设有限公司 | Garden garbage treatment system and method |
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