Internet of Things Monitoring Method, Device, Equipment and Storage Medium for Trash Can

Abstract

The present invention relates to the technical field of the Internet of Things, and discloses an Internet of Things monitoring method, device, equipment and storage medium for trash cans. By monitoring the data collected by the trash cans in the target area, the present invention obtains the garbage distribution characteristics of the target area, and generates and tests the position adjustment plan of the trash cans according to the garbage distribution characteristics. Finally, various theoretical distribution plans and their rationality parameters are obtained. Through the rationality parameters of the theoretical distribution plan, it can be determined how to adjust the positions of the trash cans to maximize the usage efficiency of each trash can, solving the problem in the prior art that when the positions of the trash cans are set unreasonably, the usage efficiency of the trash cans is relatively low.

Description

Technical Field

[0001] The present invention relates to the technical field of the Internet of Things, and particularly to an Internet of Things monitoring method, device, equipment and storage medium for trash cans. Background Art

[0002] On the streets of modern towns, trash cans are usually set up by the roadside for pedestrians to dispose of garbage. Since the pedestrian flow of different streets is different, the amount of garbage disposed of on different streets is also different. Therefore, some trash cans are often full and need to be cleaned frequently, while others can be used for a longer time and do not need to be cleaned frequently. This causes inconvenience to the cleaning staff and pedestrians when using the trash cans. Summary of the Invention

[0003] The purpose of the present invention is to provide an Internet of Things monitoring method, device, equipment and storage medium for trash cans, aiming to solve the problem of low utilization efficiency of trash cans when the positions of trash cans are set unreasonably in the prior art.

[0004] The present invention is implemented as follows. In the first aspect, the present invention provides an Internet of Things monitoring method for trash cans, including:

[0005] Obtain the road traffic information and trash can distribution information of the target area, and construct a regional simulation model corresponding to the target area and a unit simulation model corresponding to the trash can according to the obtained information;

[0006] Continuously collect data on the containment status of each trash can in the target area to obtain the garbage containment data of each trash can, and assign each piece of garbage containment data to the corresponding unit simulation model to perform calculation processing on the garbage distribution of the regional simulation model, so as to obtain the garbage distribution map of the target area at each moment;

[0007] Extract the garbage distribution characteristics of the garbage distribution map at each moment to obtain the garbage distribution characteristics at each moment, and generate a theoretical distribution plan of each unit simulation model in the regional simulation model at each moment according to the garbage distribution characteristics at each moment;

[0008] Compare and analyze each theoretical distribution plan with the existing distribution plan of each unit simulation model to obtain the rationality parameter of each theoretical distribution plan; wherein, the rationality parameter is used to describe the strength of the beneficial effect brought by the theoretical distribution plan.

[0009] Preferably, the step of continuously collecting data on the containment status of each trash can in the target area includes:

[0010] Based on the sonic sensor and infrared sensor pre - set in the trash can, the interior of the trash can is observed for the shape of garbage accumulation to obtain the garbage accumulation data of the trash can;

[0011] Based on the weight sensor pre - set in the trash can, the trash can is monitored for the weight of garbage accumulation to obtain the garbage weight data of the trash can;

[0012] The garbage accumulation data and the garbage weight data at each moment are jointly used as the garbage reception data of the trash can.

[0013] Preferably, the steps of extracting the garbage distribution characteristics from the garbage distribution maps at each moment to obtain the garbage distribution characteristics at each moment include:

[0014] Analyze the gap between the garbage reception data of each unit simulation model for each garbage distribution map at each moment to obtain the deviation degree between the garbage reception data of each unit simulation model at each moment, and use the deviation degree as the garbage distribution characteristic.

[0015] Preferably, the steps of respectively obtaining the theoretical distribution schemes of each unit simulation model in the area simulation model according to the garbage distribution characteristics at each moment include:

[0016] Perform traversal calculation processing on the adjusted position information of each unit simulation model based on the position information of each existing unit simulation model on the area simulation model to obtain several adjusted position information of each unit simulation model;

[0017] Combine the adjusted position information of each unit simulation model respectively to obtain several position adjustment schemes;

[0018] Construct a grid positioning coordinate system based on the area simulation model to divide the area simulation model into several positioning grids. Analyze the garbage - throwing pressure of each positioning grid according to the garbage distribution characteristics of each unit simulation model at each moment to obtain the garbage - throwing pressure parameters of each positioning grid at each moment;

[0019] Perform predictive calculation processing on the garbage distribution characteristics of each position adjustment scheme according to the garbage - throwing pressure parameters of each positioning grid at each moment to obtain the garbage distribution characteristics under each position adjustment scheme;

[0020] Compare the garbage distribution characteristics of each of the position adjustment schemes to obtain a comparison result, and determine the position adjustment scheme with the most average garbage distribution characteristics as the theoretical distribution scheme according to the comparison result.

[0021] Preferably, the steps of comparing and analyzing each of the theoretical distribution schemes with the existing distribution schemes of each of the unit simulation models to obtain the rationality parameters of each of the theoretical distribution schemes include:

[0022] Analyze the feature average degree of the existing garbage distribution characteristics to obtain the feature average degree of the existing garbage distribution characteristics; wherein, the feature average degree is used to describe the distribution average degree of the garbage distribution characteristics;

[0023] Analyze the feature average degree of the garbage distribution characteristics under each of the theoretical distribution schemes to obtain the distribution average degree of the garbage distribution characteristics under each of the theoretical distribution schemes;

[0024] Calculate the deviation degree between the feature average degree of the garbage distribution characteristics under each of the theoretical distribution schemes and the feature average degree of the existing garbage distribution characteristics to obtain the adjustment effect amplitude of each position adjustment scheme;

[0025] Take the feature analysis degree of each of the theoretical distribution schemes as the first rationality parameter of each of the theoretical distribution schemes, and take the adjustment effect amplitude of each of the theoretical distribution schemes as the second rationality parameter of each of the theoretical distribution schemes. The first rationality parameter and the second rationality parameter together constitute the rationality parameter.

[0026] In a second aspect, the present invention provides an Internet of Things monitoring device for trash cans, including:

[0027] A model construction module, configured to obtain the road traffic information and trash can distribution information of a target area, and construct a regional simulation model corresponding to the target area and a unit simulation model corresponding to the trash cans according to the obtained information;

[0028] A data acquisition module, configured to continuously collect data on the containment status of each trash can in the target area to obtain the garbage containment data of each trash can, and assign each of the garbage containment data to the corresponding unit simulation model to perform a calculation process on the garbage distribution of the regional simulation model, so as to obtain a garbage distribution map of the target area at each moment;

[0029] A data processing module is used to extract and process the garbage distribution characteristics of the garbage distribution atlas at each moment, so as to obtain the garbage distribution characteristics at each moment, and respectively simulate the theoretical distribution schemes of each unit model in the area model according to the garbage distribution characteristics at each moment;

[0030] A scheme analysis module is used to calculate and process the optimal distribution positions of each unit simulation model based on the theoretical distribution schemes at each moment, so as to obtain the optimal distribution positions of each unit simulation model.

[0031] In a third aspect, the present invention provides a computer device, including a memory and a processor. The memory stores a computer program that can run on the processor. When the processor executes the computer program, it implements the Internet of Things monitoring method for trash cans described in any item of the first aspect.

[0032] In a fourth aspect, the present invention provides a computer-readable storage medium, on which a computer program is stored. When the computer program is run by a processor, the processor is caused to execute the Internet of Things monitoring method for trash cans described in any item of the first aspect.

[0033] The present invention provides an Internet of Things monitoring method for trash cans, which has the following beneficial effects:

[0034] By monitoring the containment data of trash cans in a target area, the present invention obtains the garbage distribution characteristics of the target area, generates and tests the position adjustment scheme of the trash cans according to the garbage distribution characteristics, and finally obtains each theoretical distribution scheme and its rationality parameters. Through the rationality parameters of the theoretical distribution scheme, it can be determined how to adjust the positions of the trash cans to maximize the usage efficiency of each trash can, solving the problem in the prior art that when the positions of the trash cans are set unreasonably, the usage efficiency of the trash cans is relatively low. Description of the Drawings

[0035] Figure 1 is a schematic diagram of the steps of an Internet of Things monitoring method for trash cans provided by an embodiment of the present invention;

[0036] Figure 2 is a schematic diagram of the structure of an Internet of Things monitoring device for trash cans provided by an embodiment of the present invention. Detailed Embodiments

[0037] In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0038] The implementation of the present invention will be described in detail below in conjunction with specific embodiments.

[0039] Refer to Figure 1 、 Figure 2 As shown, a preferred embodiment is provided by the present invention.

[0040] In a first aspect, the present invention provides an Internet of Things monitoring method for trash cans, including:

[0041] S1: Obtain the road traffic information and trash can distribution information of the target area, and construct a regional simulation model corresponding to the target area and a unit simulation model corresponding to the trash cans according to the obtained information;

[0042] S2: Continuously collect data on the containment status of each trash can in the target area to obtain the trash containment data of each trash can, and assign each piece of trash containment data to the corresponding unit simulation model to perform calculation processing on the trash distribution of the regional simulation model, and obtain the trash distribution map of the target area at each moment;

[0043] S3: Extract the trash distribution characteristics of the trash distribution map at each moment to obtain the trash distribution characteristics at each moment, and respectively obtain the theoretical distribution schemes of each unit simulation model in the regional simulation model at each moment according to the trash distribution characteristics at each moment;

[0044] S4: Compare and analyze each theoretical distribution scheme with the existing distribution scheme of each unit simulation model to obtain the rationality parameters of each theoretical distribution scheme; wherein, the rationality parameters are used to describe the strength of the beneficial effects brought by the theoretical distribution scheme.

[0045] Specifically, in S1 of the embodiment provided by the present invention, first collect the road traffic information of the target area. Since the trash cans are set on the sidewalks, the road traffic information collected here is mainly the information of the sidewalks, that is, the length, width and specific positions of each sidewalk, etc.

[0046] More specifically, collect the position information of each trash can in the target area through on-site investigation, satellite image analysis or other feasible means, and record its longitude and latitude coordinates or relative position relationship, so as to determine the specific position of each trash can on the road. Use the collected road traffic information to construct a road network model of the target area. On the basis of the regional simulation model, according to the collected trash can position information, add a trash can unit model at the corresponding position and place it at the corresponding position in the regional simulation model.

[0047] It is understandable that by constructing a regional simulation model and adding a trash can unit model to the model, the accurate simulation of the trash can location can be achieved, so as to conduct relevant research and analysis on garbage collection, trash can location optimization, etc.

[0048] Specifically, in S2 of the embodiment provided by the present invention, a suitable trash can monitoring device is selected to detect the garbage containment situation of the trash can, and the corresponding monitoring device is installed on each trash can to ensure that the device can accurately obtain the data of the garbage containment situation of the trash can and can communicate with the data acquisition system.

[0049] More specifically, a data acquisition system is built to receive and process the data transmitted from the trash can monitoring device. This system can include components such as data receiving devices, database storage, data processing and analysis software, etc., and the garbage containment data of the trash can is collected in real time through the data acquisition system. According to the different devices, information such as the weight, filling level, image recognition results of the trash can can be obtained regularly, and the data is stored in the database.

[0050] More specifically, the garbage containment data is assigned to the unit simulation model, and the collected garbage containment data is associated with the corresponding unit simulation model. Through programming or data processing software, the real-time garbage containment data can be assigned to the attributes or states of the corresponding trash cans in the model.

[0051] It is understandable that by continuously collecting the garbage containment data of the trash can and updating the simulation model, the real-time monitoring and simulation of the trash can state can be achieved. This can be used to understand the actual filling situation of the trash can and take corresponding garbage collection measures in a timely manner. At the same time, combined with the regional simulation model, the subsequent extraction and analysis of the garbage distribution characteristics can be carried out, so as to optimize the trash can location setting, improve the efficiency of garbage treatment and reduce resource waste.

[0052] More specifically, according to the recorded garbage containment data, a garbage distribution map of each moment is generated. The garbage distribution situation at different positions in the unit simulation model can be visually represented using graphics processing software or drawing tools to form a garbage distribution map.

[0053] More specifically, the garbage distribution maps of each moment are arranged in sequence to form a distribution change map of the regional simulation model. Automatic arrangement can be carried out through image processing software or programming to ensure the timeliness of the map.

[0054] It can be understood that by recording the garbage collection data of the unit simulation model and generating a garbage distribution map, the garbage distribution in the area can be intuitively displayed. At the same time, by arranging the garbage distribution maps at each moment, a distribution change map can be formed, reflecting the dynamic change of the garbage distribution in the area simulation model, so as to optimize the garbage collection route and the trash can capacity planning in the subsequent steps, improve the efficiency of garbage disposal and reduce resource waste.

[0055] Specifically, in S3 provided by the present invention, the garbage distribution characteristics of the garbage distribution maps at each moment are extracted to obtain the garbage distribution characteristics at each moment, and the theoretical distribution schemes of each unit simulation model in the area simulation model at each moment are generated respectively according to the garbage distribution characteristics at each moment.

[0056] More specifically, the garbage distribution characteristics are used to describe the correlation between the garbage collection statuses of each unit simulation model in the area simulation model at the same moment, so as to reflect the coping ability of each trash can in the target area to the garbage disposal pressure.

[0057] More specifically, several trash can position adjustment schemes are derived according to the garbage distribution characteristics, and each position adjustment scheme is analyzed and compared to determine the best adjustment scheme among each position adjustment scheme and use it as the theoretical distribution scheme.

[0058] Specifically, in S4 provided by the present invention, the garbage distribution characteristics of each theoretical distribution scheme are compared, the garbage distribution characteristics under each theoretical distribution scheme are compared and analyzed with the existing garbage distribution characteristics, the advantages and disadvantages of each scheme are evaluated, and according to the comparison and analysis results, the rationality parameter of each theoretical distribution scheme is calculated. This parameter is used to describe the strength of the beneficial effects brought by each scheme, such as garbage collection efficiency, cost, environmental impact, etc.

[0059] It can be understood that by comparing and analyzing the garbage distribution characteristics of each position adjustment scheme to obtain the rationality parameter, the advantages, disadvantages and feasibility of each scheme can be evaluated, providing a scientific basis for decision-making. This method can improve the accuracy and reliability of garbage analysis and prediction, optimize the urban garbage collection route and the placement position of trash cans, reduce urban garbage accumulation and pollution, and promote the sustainable development of the city.

[0060] The present invention provides an Internet of Things monitoring method for trash cans, which has the following beneficial effects:

[0061] The present invention monitors the data of waste bin receptions in a target area to obtain the waste distribution characteristics of the target area, generates and tests a waste bin position adjustment plan based on the waste distribution characteristics, and finally obtains various theoretical distribution plans and their rationality parameters. Through the rationality parameters of the theoretical distribution plans, it can be determined how to adjust the positions of the waste bins to maximize the usage efficiency of each waste bin, solving the problem in the prior art that when the positions of the waste bins are set unreasonably, the usage efficiency of the waste bins is relatively low.

[0062] Preferably, the step of continuously collecting data on the reception status of each waste bin in the target area includes:

[0063] S21: Observing and processing the internal waste accumulation shape of the waste bin according to the acoustic wave sensor and infrared sensor pre-set in the waste bin to obtain the waste accumulation data of the waste bin;

[0064] S22: Monitoring and processing the waste accumulation weight of the waste bin according to the weight sensor pre-set in the waste bin to obtain the waste weight data of the waste bin;

[0065] S23: Using the waste accumulation data and the waste weight data at each moment together as the waste reception data of the waste bin.

[0066] Specifically, an acoustic wave sensor and an infrared sensor are pre-set inside the waste bin, and they are used to observe and process the shape of the waste accumulation. The sensors can detect information such as the height and distribution of the waste and record the observed data; a weight sensor is pre-set in the waste bin to monitor the weight of the waste accumulation. The sensor can sense the gravity change inside the waste bin in real time to obtain the waste weight data.

[0067] More specifically, the waste accumulation data (obtained through the acoustic wave sensor and the infrared sensor) and the waste weight data (obtained through the weight sensor) at each moment are integrated. The data of the two can be correlated to consider the volume and weight information of the waste simultaneously.

[0068] It can be understood that through the above steps, the acquisition of the waste reception data of the waste bin can be achieved. The acoustic wave sensor and the infrared sensor provide the waste accumulation shape information, and the weight sensor provides the waste weight information. Integrating these data can more comprehensively understand the waste reception situation inside the waste bin and provide a reference basis for subsequent waste treatment and management.

[0069] Preferably, the step of extracting the waste distribution characteristics from the waste distribution maps at each moment to obtain the waste distribution characteristics at each moment includes:

[0070] S31: Analyze the differences between the waste containment data of each of the unit simulation models for each moment in the waste distribution maps respectively, to obtain the deviation degree between the waste containment data of each of the unit simulation models at each moment, and use the deviation degree as the waste distribution feature.

[0071] Specifically, based on the waste accumulation data obtained by the acoustic wave sensors and infrared sensors, waste distribution maps for each moment can be obtained. These maps can show the distribution of waste in the trash can, such as the waste distribution at different heights.

[0072] More specifically, for the waste distribution map of each moment, compare it with the corresponding unit simulation model. By comparing the differences between each unit simulation model and the actual waste distribution map, the deviation degree between the waste containment data of each unit simulation model can be calculated. Using the obtained deviation degree as the waste distribution feature can reflect the difference degree between the simulation model and the actual situation, thus providing an evaluation and analysis of the waste containment data.

[0073] It can be understood that through the above steps, the analysis and processing of the deviation degree between the waste containment data of the unit simulation models at each moment can be achieved.

[0074] Preferably, the steps of generating the theoretical distribution plan of each of the unit simulation models in the area simulation model at each moment according to the waste distribution features at each moment include:

[0075] S32: Perform traversal calculation processing on the adjusted position information of each of the unit simulation models based on the position information of each of the existing unit simulation models on the area simulation model as a reference, to obtain several adjusted position information of each of the unit simulation models;

[0076] S33: Combine the adjusted position information of each of the unit simulation models respectively, to obtain several position adjustment plans;

[0077] S34: Construct a grid positioning coordinate system based on the area simulation model, to divide the area simulation model into several positioning grids. Analyze the waste placement pressure of each of the positioning grids according to the waste distribution features of each of the unit simulation models at each moment, to obtain the waste placement pressure parameters of each of the positioning grids at each moment;

[0078] S35: Perform prediction calculation processing on the waste distribution features of each of the position adjustment plans according to the waste placement pressure parameters of each of the positioning grids at each moment, to obtain the waste distribution features under each of the position adjustment plans;

[0079] S36: Compare the garbage distribution characteristics of each of the position adjustment schemes to obtain a comparison result, and determine the position adjustment scheme with the most average garbage distribution characteristics as the theoretical distribution scheme according to the comparison result.

[0080] Specifically, first, based on the position information of each unit simulation model on the regional simulation model, calculate the position information that each unit simulation model needs to adjust. Then, traverse and calculate the adjusted position information of each unit simulation model to obtain several adjusted position information of each unit simulation model. The position adjustment scheme of each unit simulation model can be obtained by traversing and calculating the position information of each unit simulation model, providing data support for the next step.

[0081] More specifically, combine the several adjusted position information of each unit simulation model respectively to obtain several position adjustment schemes. The position adjustment schemes of each unit simulation model can be combined to obtain a variety of different position adjustment schemes, providing multiple choices for the next step.

[0082] More specifically, construct a grid positioning coordinate system based on the regional simulation model, divide the regional simulation model into several positioning grids, and analyze the garbage delivery pressure of each positioning grid according to the garbage distribution characteristics of each unit simulation model at each moment to obtain the garbage delivery pressure parameters of each positioning grid at each moment. The garbage delivery pressure parameters of each positioning grid at each moment can be obtained by dividing the regional simulation model into grids and analyzing the garbage delivery pressure according to the garbage distribution characteristics of the unit simulation model at each moment, providing data support for the next step.

[0083] More specifically, predict and calculate the garbage distribution characteristics of each position adjustment scheme according to the garbage delivery pressure parameters of each positioning grid at each moment to obtain the garbage distribution characteristics under each position adjustment scheme. Use the garbage delivery pressure parameters to predict and calculate the garbage distribution characteristics to obtain the garbage distribution characteristics under each position adjustment scheme, providing data support for the next step.

[0084] More specifically, compare the garbage distribution characteristics of each position adjustment scheme to obtain a comparison result, and determine the position adjustment scheme with the most average garbage distribution characteristics as the theoretical distribution scheme according to the comparison result. Compare the garbage distribution characteristics of each position adjustment scheme to obtain the position adjustment scheme with the most average garbage distribution characteristics. This scheme can be used as the theoretical distribution scheme to provide a reference basis for optimizing the garbage collection scheme.

[0085] Preferably, the step of comparing and analyzing each of the theoretical distribution schemes with the existing distribution schemes of each of the unit simulation models to obtain the rationality parameters of each of the theoretical distribution schemes includes:

[0086] S41: Analyze the feature average degree of the existing garbage distribution characteristics to obtain the feature average degree of the existing garbage distribution characteristics; wherein, the feature average degree is used to describe the average degree of distribution of the garbage distribution characteristics;

[0087] S42: Analyze the feature average degree of the garbage distribution characteristics under each of the theoretical distribution schemes to obtain the average degree of distribution of the garbage distribution characteristics under each of the theoretical distribution schemes;

[0088] S43: Calculate the deviation degree between the feature average degree of the garbage distribution characteristics under each of the theoretical distribution schemes and the feature average degree of the existing garbage distribution characteristics to obtain the adjustment effect amplitude of each position adjustment scheme;

[0089] S44: Take the feature analysis degree of each of the theoretical distribution schemes as the first rationality parameter of each of the theoretical distribution schemes, and take the adjustment effect amplitude of each of the theoretical distribution schemes as the second rationality parameter of each of the theoretical distribution schemes. The first rationality parameter and the second rationality parameter together constitute the rationality parameter.

[0090] Specifically, for the existing garbage distribution characteristics, calculate its average degree of distribution. The average degree can reflect whether each trash can is used evenly in the target area. That is to say, the higher the feature average degree, the more evenly each trash can is used and the more fully it is utilized.

[0091] More specifically, for the theoretical distribution scheme at each moment, similarly calculate the average degree of distribution of its garbage distribution characteristics, and the steps are the same as above.

[0092] More specifically, comprehensively evaluate the above-obtained average degree of distribution and deviation degree as rationality parameters. Among them, the average degree of distribution can be used as the first rationality parameter, and the deviation degree can be used as the second rationality parameter.

[0093] It can be understood that the first rationality parameter is used to describe whether the effect of the position adjustment scheme is reasonable, and the second rationality parameter is used to describe the gap between the position adjustment scheme and the existing scheme, and to reflect whether the position adjustment scheme itself is reasonable according to the size of the gap.

[0094] Refer to Figure 2 As shown in the figure, on the second aspect, the present invention provides an Internet of Things monitoring device for trash cans, including:

[0095] A model construction module, configured to obtain the road traffic information and the trash can distribution information of the target area, and construct a regional simulation model corresponding to the target area and a unit simulation model corresponding to each trash can according to the obtained information;

[0096] A data collection module, configured to continuously collect the data of the containment status of each trash can in the target area to obtain the trash containment data of each trash can, and assign each piece of the trash containment data to the corresponding unit simulation model respectively to perform calculation processing on the trash distribution of the regional simulation model, so as to obtain the trash distribution map of the target area at each moment;

[0097] A data processing module, configured to perform extraction processing on the trash distribution characteristics of the trash distribution map at each moment to obtain the trash distribution characteristics at each moment, and respectively obtain the theoretical distribution schemes of each unit simulation model in the regional simulation model at each moment according to the trash distribution characteristics at each moment;

[0098] A scheme analysis module, configured to perform calculation processing on the optimal distribution positions of each unit simulation model based on the theoretical distribution schemes at each moment to obtain the optimal distribution positions of each unit simulation model.

[0099] In this embodiment, for the specific implementation of each module in the above device embodiment, please refer to that described in the above method embodiment, and details will not be described herein again.

[0100] In a third aspect, the present invention provides a computer device, including a memory and a processor, where the memory stores a computer program that can be run on the processor, and when the processor executes the computer program, it implements any one of the methods for Internet of Things monitoring of trash cans described in the first aspect.

[0101] In a fourth aspect, the present invention provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is run by a processor, the processor is caused to execute any one of the methods for Internet of Things monitoring of trash cans described in the first aspect.

[0102] The above are only the preferred embodiments of the present invention, and are not intended to limit the present invention. Any modifications, equivalent replacements, and improvements made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. An Internet of Things monitoring method for a trash can, characterized in that, Including: Obtain the road traffic information and trash can distribution information of the target area, and construct a regional simulation model corresponding to the target area and a unit simulation model corresponding to each trash can according to the obtained information; Continuously collect data on the containment status of each trash can in the target area to obtain the trash containment data of each trash can, and assign each piece of trash containment data to the corresponding unit simulation model respectively to perform calculation processing on the trash distribution of the regional simulation model, so as to obtain the trash distribution map of the target area at each moment; Extract the trash distribution characteristics of the trash distribution map at each moment to obtain the trash distribution characteristics at each moment, and generate theoretical distribution plans of each unit simulation model in the regional simulation model at each moment according to the trash distribution characteristics at each moment; Compare and analyze each theoretical distribution plan with the existing distribution plan of each unit simulation model to obtain the rationality parameter of each theoretical distribution plan; wherein, the rationality parameter is used to describe the strength of the beneficial effect brought by the theoretical distribution plan; The steps of generating the theoretical distribution plan of each unit simulation model in the regional simulation model at each moment according to the trash distribution characteristics at each moment include: Perform traversal calculation processing on the adjusted position information of each unit simulation model with the position information of each existing unit simulation model on the regional simulation model as a reference to obtain several adjusted position information of each unit simulation model; Combine the adjusted position information of each unit simulation model respectively to obtain several position adjustment plans; Construct a grid positioning coordinate system based on the regional simulation model to divide the regional simulation model into several positioning grids, and analyze the trash dumping pressure of each positioning grid according to the trash distribution characteristics of each unit simulation model at each moment to obtain the trash dumping pressure parameters of each positioning grid at each moment; Perform prediction calculation processing on the trash distribution characteristics of each position adjustment plan according to the trash dumping pressure parameters of each positioning grid at each moment to obtain the trash distribution characteristics under each position adjustment plan; Compare the trash distribution characteristics of each position adjustment plan to obtain the comparison result, and determine the position adjustment plan with the most average trash distribution characteristics as the theoretical distribution plan according to the comparison result.

2. The Internet of Things monitoring method for a trash can according to claim 1, characterized in that, The steps of continuously collecting data on the containment status of each trash can in the target area include: Observe the trash accumulation shape inside the trash can according to the acoustic wave sensor and infrared sensor pre-set in the trash can to obtain the trash accumulation data of the trash can; Monitor the trash accumulation weight of the trash can according to the weight sensor pre-set in the trash can to obtain the trash weight data of the trash can; The garbage accumulation data and the garbage weight data at each moment are jointly used as the garbage containment data of the trash can.

3. The Internet of Things monitoring method for a trash can according to claim 1, characterized in that, The steps of extracting the garbage distribution characteristics from the garbage distribution maps at each moment to obtain the garbage distribution characteristics at each moment include: Performing gap analysis processing on the garbage containment data of each of the unit simulation models for the garbage distribution maps at each moment to obtain the deviation degree between the garbage containment data of each of the unit simulation models at each moment, and using the deviation degree as the garbage distribution characteristic.

4. The Internet of Things monitoring method for a trash can according to claim 1, wherein, The steps of comparing and analyzing each of the theoretical distribution schemes with the existing distribution schemes of each of the unit simulation models to obtain the rationality parameters of each of the theoretical distribution schemes include: Performing analysis processing on the feature average degree of the existing garbage distribution characteristics to obtain the feature average degree of the existing garbage distribution characteristics; wherein, the feature average degree is used to describe the average degree of distribution of the garbage distribution characteristics. Performing analysis processing on the feature average degree of the garbage distribution characteristics under each of the theoretical distribution schemes to obtain the average degree of distribution of the garbage distribution characteristics under each of the theoretical distribution schemes. Performing calculation processing on the deviation degree between the feature average degree of the garbage distribution characteristics under each of the theoretical distribution schemes and the feature average degree of the existing garbage distribution characteristics to obtain the adjustment effect amplitude of each position adjustment scheme. Taking the feature analysis degree of each of the theoretical distribution schemes as the first rationality parameter of each of the theoretical distribution schemes, taking the adjustment effect amplitude of each of the theoretical distribution schemes as the second rationality parameter of each of the theoretical distribution schemes, and the first rationality parameter and the second rationality parameter jointly constitute the rationality parameter.

5. An Internet of Things monitoring device for a trash can, characterized in that, A method for Internet of Things monitoring for a trash can, which is used to implement any one of claims 1 to 4, includes: A model construction module, configured to obtain the road traffic information and the trash can distribution information of the target area, and construct a regional simulation model corresponding to the target area and a unit simulation model corresponding to the trash can according to the obtained information. A data acquisition module, configured to continuously collect data on the containment status of each trash can in the target area to obtain the garbage containment data of each trash can, and assign each of the garbage containment data to the corresponding unit simulation model to perform calculation processing on the garbage distribution of the regional simulation model to obtain the garbage distribution map of the target area at each moment. A data processing module, configured to perform extraction processing on the garbage distribution characteristics of the garbage distribution maps at each moment to obtain the garbage distribution characteristics at each moment, and respectively determine the theoretical distribution schemes of each of the unit simulation models in the regional simulation model according to the garbage distribution characteristics at each moment. A scheme analysis module, configured to perform calculation processing on the optimal distribution positions of each of the unit simulation models based on the theoretical distribution schemes at each moment to obtain the optimal distribution positions of each of the unit simulation models.

6. A computer device, comprising a memory and a processor, the memory storing a computer program that can run on the processor, characterized in that, When the processor executes the computer program, it implements the Internet of Things monitoring method for a trash can according to any one of claims 1 to 4.

7. A computer-readable storage medium, characterized in that, A computer program is stored thereon, and when the computer program is run by a processor, the processor is caused to execute an Internet of Things monitoring method for a trash can according to any one of claims 1-4.

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