Internet of Things monitoring method, device and equipment for garbage can and storage medium

Abstract

The invention relates to the technical field of the Internet of Things, and discloses an Internet of Things monitoring method, device and equipment for garbage cans and a storage medium. Garbage distribution characteristics of a target area are obtained by monitoring containing data of the garbage cans in the target area; and according to the garbage distribution characteristics, generating and testing a garbage can position adjusting scheme, finally obtaining each theoretical distribution scheme and rationality parameters thereof, and determining how to adjust the positions of the garbage cans through the rationality parameters of the theoretical distribution schemes so as to maximize the use efficiency of each garbage can. The problem that in the prior art, when the position of a garbage can is unreasonable, the use efficiency of the garbage can is low is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of Internet of Things, and in particular to an Internet of Things monitoring method, device, equipment and storage medium for a garbage can. Background Art

[0002] On the streets of modern towns, there are usually street trash cans for pedestrians to dispose of garbage. Due to the different flow of people on different streets, the amount of garbage placed on different streets is also different. Therefore, some trash cans are often full and need to be cleaned frequently, while other trash cans can be used for a longer time and do not need frequent cleaning. This causes inconvenience to the cleaning staff and it is inconvenient for pedestrians to use 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 a trash can, aiming to solve the problem in the prior art that when the location of the trash can is set unreasonably, the trash can utilization efficiency is low.

[0004] The present invention is implemented in this way. In a first aspect, the present invention provides an Internet of Things monitoring method for a garbage can, comprising: Acquire 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 can according to the acquired information; Continuously collecting data on the collection status of each garbage bin in the target area to obtain garbage collection data of each garbage bin, and assigning each garbage collection data to the corresponding unit simulation model to calculate the garbage distribution of the regional simulation model to obtain the garbage distribution map of the target area at each time; Extracting garbage distribution features from the garbage distribution map at each moment to obtain the garbage distribution features at each moment, and generating theoretical distribution schemes of each of the unit simulation models at each moment in the regional simulation model according to the garbage distribution features at each moment; Compare and analyze each of the theoretical distribution schemes with the existing distribution schemes of each of the unit simulation models to obtain rationality parameters of each of the theoretical distribution schemes; wherein the rationality parameters are used to describe the strength of the beneficial effects brought about by the theoretical distribution schemes.

[0005] Preferably, the step of continuously collecting data on the storage status of each trash can in the target area includes: Observing and processing the appearance of garbage accumulation inside the garbage can according to the sonic sensor and the infrared sensor pre-installed in the garbage can to obtain garbage accumulation data of the garbage can; Monitoring the garbage accumulation weight of the garbage bin according to a weight sensor pre-installed in the garbage bin to obtain garbage weight data of the garbage bin; The garbage accumulation data and the garbage weight data at each moment are used together as the garbage collection data of the garbage bin.

[0006] Preferably, the step of extracting garbage distribution features from the garbage distribution map at each moment to obtain the garbage distribution features at each moment includes: The garbage distribution map at each moment is subjected to a gap analysis process between the garbage collection data of each of the unit simulation models to obtain the degree of deviation between the garbage collection data of each of the unit simulation models at each moment, and the degree of deviation is used as the garbage distribution feature. Preferably, the step of performing a theoretical distribution scheme of each of the unit simulation models in the regional simulation model at each moment according to the garbage distribution characteristics at each moment comprises: Taking the existing position information of each of the unit simulation models on the regional simulation model as a reference, traversing and calculating the adjustment position information of each of the unit simulation models to obtain a number of adjustment position information of each of the unit simulation models; Combining the adjustment position information of each of the unit simulation models respectively to obtain a plurality of position adjustment schemes; Constructing a grid positioning coordinate system based on the regional simulation model to divide the regional simulation model into a plurality of positioning grids, and analyzing and processing 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; According to the garbage delivery pressure parameters of each positioning grid at each moment, the garbage distribution characteristics of each positioning adjustment scheme are predicted and calculated to obtain the garbage distribution characteristics under each positioning adjustment scheme; The garbage distribution characteristics of each of the position adjustment schemes are compared to obtain a comparison result, and the position adjustment scheme having the most average garbage distribution characteristic is determined as the theoretical distribution scheme according to the comparison result.

[0007] 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 rationality parameters of each of the theoretical distribution schemes includes: Performing feature average analysis on the existing garbage distribution features to obtain the feature average of the existing garbage distribution features; wherein the feature average is used to describe the average degree of distribution of the garbage distribution features; Performing feature average analysis on the garbage distribution features under each of the theoretical distribution schemes to obtain the distribution average degree of the garbage distribution features under each of the theoretical distribution schemes; Calculate the deviation between the characteristic average of the garbage distribution characteristics under each of the theoretical distribution schemes and the characteristic average of the existing garbage distribution characteristics to obtain the adjustment effect range of each position adjustment scheme; The characteristic analysis degree of each of the theoretical distribution schemes is taken as the first rationality parameter of each of the theoretical distribution schemes, and the adjustment effect amplitude of each of the theoretical distribution schemes is taken 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.

[0008] In a second aspect, the present invention provides an Internet of Things monitoring device for a trash can, comprising: A model building module, used to obtain road traffic information and trash can distribution information of a target area, and to build 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 collection module is used to continuously collect data on the collection status of each garbage bin in the target area to obtain garbage collection data of each garbage bin, and assign each garbage collection data to the corresponding unit simulation model to calculate the garbage distribution of the regional simulation model to obtain the garbage distribution map of the target area at each time; A data processing module is used to extract garbage distribution features from the garbage distribution map at each moment to obtain the garbage distribution features at each moment, and to calculate theoretical distribution schemes of each of the unit simulation models at each moment in the regional simulation model according to the garbage distribution features at each moment; The scheme analysis module is used to calculate and process the optimal distribution position of each of the unit simulation models based on the theoretical distribution scheme at each moment, so as to obtain the optimal distribution position of each of the unit simulation models.

[0009] In a third aspect, the present invention provides a computer device comprising a memory and a processor, wherein the memory stores a computer program executable on the processor, and when the processor executes the computer program, it implements an Internet of Things monitoring method for a trash can as described in any one of the first aspects.

[0010] In a fourth aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the processor executes an Internet of Things monitoring method for a trash can as described in any one of the first aspects.

[0011] The present invention provides an Internet of Things monitoring method for a garbage can, which has the following beneficial effects: The present invention monitors the storage data of garbage bins in a target area, thereby obtaining the garbage distribution characteristics of the target area, and generates and tests garbage bin position adjustment schemes according to the garbage distribution characteristics, and finally obtains various theoretical distribution schemes and their rationality parameters. The rationality parameters of the theoretical distribution schemes can be used to determine how to adjust the positions of the garbage bins to maximize the utilization efficiency of each garbage bin, thereby solving the problem in the prior art that the utilization efficiency of the garbage bins is low when the positions of the garbage bins are set unreasonably. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1 It is a schematic diagram of the steps of an Internet of Things monitoring method for a garbage bin provided by an embodiment of the present invention; Figure 2 It is a structural schematic diagram of an Internet of Things monitoring device for a garbage can provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0013] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with 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 intended to limit the present invention.

[0014] The implementation of the present invention is described in detail below in conjunction with specific embodiments.

[0015] Reference Figure 1 , Figure 2 As shown, a preferred embodiment of the present invention is provided.

[0016] In a first aspect, the present invention provides an Internet of Things monitoring method for a trash can, comprising: S1: Obtain 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 can according to the acquired information; S2: continuously collecting data on the collection status of each garbage bin in the target area to obtain garbage collection data of each garbage bin, and assigning each garbage collection data to the corresponding unit simulation model to calculate the garbage distribution of the regional simulation model to obtain the garbage distribution map of the target area at each time; S3: extracting garbage distribution features from the garbage distribution map at each moment to obtain the garbage distribution features at each moment, and respectively calculating theoretical distribution schemes of each of the unit simulation models at each moment in the regional simulation model according to the garbage distribution features at each moment; S4: Compare and analyze each of the theoretical distribution schemes with the existing distribution schemes of each of the unit simulation models to obtain rationality parameters of each of the theoretical distribution schemes; wherein the rationality parameters are used to describe the strength of the beneficial effects brought about by the theoretical distribution schemes.

[0017] Specifically, in S1 of the embodiment provided by the present invention, the road traffic information of the target area is first collected. Since the trash cans are set on the sidewalks, the road traffic information collected here mainly includes the information of the sidewalks, that is, the length, width and specific location of each sidewalk.

[0018] More specifically, the location information of each trash can in the target area is collected through on-site investigation, satellite image analysis or other feasible methods, and their latitude and longitude coordinates or relative position relationships are recorded to determine the specific location of each trash can on the road. The collected road traffic information is used to build a road network model of the target area. On the basis of the regional simulation model, trash can unit models are added at corresponding positions according to the collected trash can location information, and placed at corresponding positions in the regional simulation model.

[0019] It can be understood that by constructing a regional simulation model and adding a trash can unit model to the model, an accurate simulation of the trash can location can be achieved to facilitate related research and analysis such as garbage collection and trash can location optimization.

[0020] Specifically, in S2 of the embodiment provided by the present invention, a suitable garbage bin monitoring device is selected to detect the garbage collection situation of the garbage bin, and a corresponding monitoring device is installed on each garbage bin to ensure that the device can accurately obtain the garbage collection situation data of the garbage bin and can communicate with the data acquisition system.

[0021] More specifically, a data collection system is built to receive and process data transmitted from the garbage bin monitoring device. The system may include components such as data receiving equipment, database storage, data processing and analysis software, and the garbage collection data of the garbage bin is collected in real time through the data collection system. Depending on the device, information such as the weight, filling level, image recognition results, etc. of the garbage bin can be obtained regularly and the data can be stored in the database.

[0022] More specifically, the garbage collection data is assigned to the unit simulation model, and the collected garbage collection data is associated with the corresponding unit simulation model. The real-time garbage collection data can be assigned to the attributes or states of the corresponding garbage bins in the model through programming or data processing software.

[0023] It is understandable that by continuously collecting garbage collection data from the garbage bins and updating the simulation model, real-time monitoring and simulation of the garbage bin status can be achieved. This can be used to understand the actual filling situation of the garbage bins and take corresponding garbage collection measures in a timely manner. At the same time, combined with the regional simulation model, subsequent garbage distribution characteristics can be extracted and analyzed, so as to optimize the location of the garbage bins, improve the efficiency of garbage disposal and reduce resource waste.

[0024] More specifically, based on the recorded garbage collection data, a garbage distribution map is generated at each moment, and the garbage distribution conditions at different locations in the unit simulation model can be visualized using graphic processing software or drawing tools to form a garbage distribution map.

[0025] More specifically, the garbage distribution maps at each moment are arranged in order to form a distribution change map of the regional simulation model. The map can be automatically arranged through image processing software or programming to ensure the time sequence of the map.

[0026] It is understandable that by recording the garbage collection data of the unit simulation model and generating a garbage distribution map, the distribution of garbage in the region can be intuitively displayed. At the same time, by arranging the garbage distribution maps at various times, a distribution change map can be formed to reflect the dynamic changes in garbage distribution in the regional simulation model, so as to optimize the garbage collection route and garbage bin capacity planning in the subsequent steps, improve the efficiency of garbage disposal and reduce resource waste.

[0027] Specifically, in S3 provided by the present invention, the garbage distribution map at each moment is processed for extracting the garbage distribution characteristics to obtain the garbage distribution characteristics at each moment, and the theoretical distribution schemes of each unit simulation model at each moment in the regional simulation model are generated respectively according to the garbage distribution characteristics at each moment.

[0028] More specifically, the garbage distribution characteristics are used to describe the correlation between the garbage collection conditions of each unit simulation model in the regional simulation model at the same time, thereby providing feedback on the ability of each garbage bin in the target area to cope with the pressure of garbage disposal.

[0029] More specifically, several position adjustment schemes for trash cans are derived based on the trash distribution characteristics, and the various position adjustment schemes are analyzed and compared to determine the best adjustment scheme among the various position adjustment schemes, which is used as the theoretical distribution scheme.

[0030] 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 the rationality parameter of each theoretical distribution scheme is calculated based on the comparison and analysis results. 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.

[0031] It can be understood that by comparing and analyzing the garbage distribution characteristics of each position adjustment scheme and obtaining the rationality parameters, the advantages and 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 urban garbage collection routes and garbage bin placement, reduce urban garbage accumulation and pollution, and promote urban sustainable development.

[0032] The present invention provides an Internet of Things monitoring method for a garbage can, which has the following beneficial effects: The present invention monitors the storage data of garbage bins in a target area, thereby obtaining the garbage distribution characteristics of the target area, and generates and tests garbage bin position adjustment schemes according to the garbage distribution characteristics, and finally obtains various theoretical distribution schemes and their rationality parameters. The rationality parameters of the theoretical distribution schemes can be used to determine how to adjust the positions of the garbage bins to maximize the utilization efficiency of each garbage bin, thereby solving the problem in the prior art that the utilization efficiency of the garbage bins is low when the positions of the garbage bins are set unreasonably.

[0033] Preferably, the step of continuously collecting data on the storage status of each trash can in the target area includes: S21: observing and processing the appearance of garbage accumulation inside the garbage can according to the acoustic wave sensor and the infrared sensor pre-installed in the garbage can to obtain garbage accumulation data of the garbage can; S22: monitoring the garbage accumulation weight of the garbage bin according to a weight sensor pre-installed in the garbage bin to obtain garbage weight data of the garbage bin; S23: The garbage accumulation data and the garbage weight data at each moment are used together as the garbage collection data of the garbage bin.

[0034] Specifically, an acoustic sensor and an infrared sensor are pre-installed inside the trash can to observe and process the shape of the garbage pile. The sensor can detect the height, distribution and other information of the garbage and record the observed data; a weight sensor is pre-installed in the trash can to monitor the weight of the garbage pile. The sensor can sense the gravity changes in the trash can in real time, thereby obtaining the weight data of the garbage.

[0035] More specifically, the garbage accumulation data (obtained by the acoustic sensor and the infrared sensor) and the garbage weight data (obtained by the weight sensor) at each moment are integrated. The two data can be correlated so that both the volume and weight information of the garbage are considered at the same time.

[0036] It can be understood that through the above steps, the garbage collection data of the garbage bin can be obtained. The acoustic sensor and infrared sensor provide information on the shape of the garbage accumulation, and the weight sensor provides information on the weight of the garbage. By integrating these data, we can have a more comprehensive understanding of the garbage collection situation inside the garbage bin, providing a reference for subsequent garbage disposal and management.

[0037] Preferably, the step of extracting garbage distribution features from the garbage distribution map at each moment to obtain the garbage distribution features at each moment includes: S31: performing a gap analysis process on the garbage distribution map at each moment and the garbage collection data of each unit simulation model respectively, so as to obtain the degree of deviation between the garbage collection data of each unit simulation model at each moment, and taking the degree of deviation as the garbage distribution feature. Specifically, based on the garbage accumulation data obtained by the acoustic sensor and the infrared sensor, garbage distribution maps at various times can be obtained. These maps can show the distribution of garbage in the garbage bin, such as the distribution of garbage at different heights.

[0038] More specifically, for each garbage distribution map at a certain moment, it is compared with the corresponding unit simulation model. By comparing the differences between each unit simulation model and the actual garbage distribution map, the degree of deviation between the garbage collection data of each unit simulation model can be calculated. The obtained degree of deviation is used as the garbage distribution feature, which can reflect the degree of difference between the simulation model and the actual situation, thereby providing an evaluation and analysis of the garbage collection data.

[0039] It can be understood that, through the above steps, it is possible to analyze and process the degree of deviation between the garbage collection data of the unit simulation model at each moment.

[0040] Preferably, the step of generating theoretical distribution schemes of each of the unit simulation models at each moment in the regional simulation model according to the garbage distribution characteristics at each moment comprises: S32: taking the existing position information of each of the unit simulation models on the regional simulation model as a reference, performing traversal calculation processing on the adjustment position information of each of the unit simulation models to obtain a number of adjustment position information of each of the unit simulation models; S33: combining the adjustment position information of the unit simulation models respectively to obtain a plurality of position adjustment schemes; S34: constructing a grid positioning coordinate system based on the regional simulation model to divide the regional simulation model into a plurality of positioning grids, and analyzing and processing 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; S35: performing prediction and calculation processing of garbage distribution characteristics for each of the position adjustment schemes according to the garbage delivery pressure parameters of each of the positioning grids at each time, so as to obtain the garbage distribution characteristics under each of the position adjustment schemes; S36: performing a comparison process on the garbage distribution characteristics of each of the position adjustment schemes to obtain a comparison process result, and determining the position adjustment scheme having the most average garbage distribution characteristic as the theoretical distribution scheme according to the comparison process result.

[0041] Specifically, first, the position information of each unit simulation model on the regional simulation model is used as a reference to calculate the position information of each unit simulation model that needs to be adjusted. Then, the adjusted position information of each unit simulation model is traversed and calculated to obtain a number of adjusted position information of each unit simulation model. By traversing and calculating the position information of each unit simulation model, the position adjustment scheme of each unit simulation model can be obtained to provide data support for the next step.

[0042] More specifically, several adjustment position information of each unit simulation model are combined 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 options for the next step.

[0043] More specifically, a grid positioning coordinate system is constructed based on the regional simulation model, the regional simulation model is divided into a number of positioning grids, and the garbage disposal pressure of each positioning grid is analyzed and processed according to the garbage distribution characteristics of each unit simulation model at each moment, so as to obtain the garbage disposal pressure parameters of each positioning grid at each moment. The regional simulation model can be gridded, and the garbage disposal pressure is analyzed and processed according to the garbage distribution characteristics of the unit simulation model at each moment, so as to obtain the garbage disposal pressure parameters of each positioning grid at each moment, thereby providing data support for the next step.

[0044] More specifically, the garbage distribution characteristics of each position adjustment scheme are predicted and calculated based on the garbage disposal pressure parameters of each positioning grid at each moment, so as to obtain the garbage distribution characteristics under each position adjustment scheme, and provide data support for the next step.

[0045] More specifically, the garbage distribution characteristics of each position adjustment scheme are compared and processed to obtain a comparison result, and the position adjustment scheme with the most average garbage distribution characteristics is determined as the theoretical distribution scheme according to the comparison result. The garbage distribution characteristics of each position adjustment scheme are compared and processed to obtain a position adjustment scheme with the most average garbage distribution characteristics. This scheme can be used as a theoretical distribution scheme to provide a reference for optimizing the garbage collection scheme.

[0046] 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 rationality parameters of each of the theoretical distribution schemes includes: S41: Analyzing and processing the feature average of the existing garbage distribution feature to obtain the feature average of the existing garbage distribution feature; wherein the feature average is used to describe the distribution average degree of the garbage distribution feature; S42: performing feature average analysis on the garbage distribution features under each of the theoretical distribution schemes to obtain the distribution average degree of the garbage distribution features under each of the theoretical distribution schemes; S43: calculating the deviation between the characteristic average degree of the garbage distribution characteristics under each of the theoretical distribution schemes and the characteristic average degree of the existing garbage distribution characteristics, so as to obtain the adjustment effect range of each position adjustment scheme; S44: Taking the characteristic 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, the first rationality parameter and the second rationality parameter together constitute the rationality parameter.

[0047] Specifically, the average degree of distribution is calculated for the existing garbage distribution characteristics. The average degree can provide feedback on whether the garbage bins in the target area are used evenly. That is to say, the higher the characteristic average degree, the more evenly and fully the garbage bins are used.

[0048] More specifically, for the theoretical distribution scheme at each moment, the average degree of distribution of its garbage distribution characteristics is also calculated, and the steps are consistent with the above.

[0049] More specifically, the distribution average degree and the deviation degree obtained above are used as rationality parameters for comprehensive evaluation, wherein the distribution average degree can be used as the first rationality parameter, and the deviation degree can be used as the second rationality parameter.

[0050] 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 the size of the gap is used to provide feedback on whether the position adjustment scheme itself is reasonable.

[0051] Reference Figure 2 As shown, in a second aspect, the present invention provides an Internet of Things monitoring device for a trash can, comprising: A model building module, used to obtain road traffic information and trash can distribution information of a target area, and to build 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 collection module is used to continuously collect data on the collection status of each garbage bin in the target area to obtain garbage collection data of each garbage bin, and assign each garbage collection data to the corresponding unit simulation model to calculate the garbage distribution of the regional simulation model to obtain the garbage distribution map of the target area at each time; A data processing module is used to extract garbage distribution features from the garbage distribution map at each moment to obtain the garbage distribution features at each moment, and to calculate theoretical distribution schemes of each of the unit simulation models at each moment in the regional simulation model according to the garbage distribution features at each moment; The scheme analysis module is used to calculate and process the optimal distribution position of each of the unit simulation models based on the theoretical distribution scheme at each moment, so as to obtain the optimal distribution position of each of the unit simulation models.

[0052] In this embodiment, for the specific implementation of each module in the above-mentioned device embodiment, please refer to the above-mentioned method embodiment, which will not be repeated here.

[0053] In a third aspect, the present invention provides a computer device comprising a memory and a processor, wherein the memory stores a computer program executable on the processor, and when the processor executes the computer program, it implements an Internet of Things monitoring method for a trash can as described in any one of the first aspects.

[0054] In a fourth aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the processor executes an Internet of Things monitoring method for a trash can as described in any one of the first aspects.

[0055] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should 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: include: Acquire 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 can according to the acquired information; Continuously collecting data on the collection status of each garbage bin in the target area to obtain garbage collection data of each garbage bin, and assigning each garbage collection data to the corresponding unit simulation model to calculate the garbage distribution of the regional simulation model to obtain the garbage distribution map of the target area at each time; Extracting garbage distribution features from the garbage distribution map at each moment to obtain the garbage distribution features at each moment, and generating theoretical distribution schemes of each of the unit simulation models at each moment in the regional simulation model according to the garbage distribution features at each moment; Compare and analyze each of the theoretical distribution schemes with the existing distribution schemes of each of the unit simulation models to obtain rationality parameters of each of the theoretical distribution schemes; wherein the rationality parameters are used to describe the strength of the beneficial effects brought about by the theoretical distribution schemes.

2. The Internet of Things monitoring method for a garbage can according to claim 1, characterized in that: The step of continuously collecting data on the storage status of each trash can in the target area includes: Observing and processing the appearance of garbage accumulation inside the garbage can according to the sonic sensor and the infrared sensor pre-installed in the garbage can to obtain garbage accumulation data of the garbage can; Monitoring the garbage accumulation weight of the garbage bin according to a weight sensor pre-installed in the garbage bin to obtain garbage weight data of the garbage bin; The garbage accumulation data and the garbage weight data at each moment are used together as the garbage collection data of the garbage bin.

3. The Internet of Things monitoring method for a garbage can according to claim 1, characterized in that: The step of extracting garbage distribution features from the garbage distribution map at each moment to obtain the garbage distribution features at each moment includes: The garbage distribution map at each moment is subjected to a gap analysis process between the garbage collection data of each of the unit simulation models to obtain the degree of deviation between the garbage collection data of each of the unit simulation models at each moment, and the degree of deviation is used as the garbage distribution feature.

4. The Internet of Things monitoring method for a garbage can according to claim 1, characterized in that: The steps of respectively performing theoretical distribution schemes of each of the unit simulation models in the regional simulation model at each moment according to the garbage distribution characteristics at each moment include: Taking the existing position information of each of the unit simulation models on the regional simulation model as a reference, traversing and calculating the adjustment position information of each of the unit simulation models to obtain a number of adjustment position information of each of the unit simulation models; Combining the adjustment position information of each of the unit simulation models respectively to obtain a plurality of position adjustment schemes; Constructing a grid positioning coordinate system based on the regional simulation model to divide the regional simulation model into a plurality of positioning grids, and analyzing and processing 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; According to the garbage delivery pressure parameters of each positioning grid at each moment, the garbage distribution characteristics of each positioning adjustment scheme are predicted and calculated to obtain the garbage distribution characteristics under each positioning adjustment scheme; The garbage distribution characteristics of each of the position adjustment schemes are compared to obtain a comparison result, and the position adjustment scheme having the most average garbage distribution characteristic is determined as the theoretical distribution scheme according to the comparison result.

5. The Internet of Things monitoring method for a garbage can according to claim 4, characterized in that: 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 rationality parameters of each of the theoretical distribution schemes includes: Performing feature average analysis on the existing garbage distribution features to obtain the feature average of the existing garbage distribution features; wherein the feature average is used to describe the average degree of distribution of the garbage distribution features; Performing feature average analysis on the garbage distribution features under each of the theoretical distribution schemes to obtain the distribution average degree of the garbage distribution features under each of the theoretical distribution schemes; Calculate the deviation between the characteristic average of the garbage distribution characteristics under each of the theoretical distribution schemes and the characteristic average of the existing garbage distribution characteristics to obtain the adjustment effect range of each position adjustment scheme; The characteristic analysis degree of each of the theoretical distribution schemes is taken as the first rationality parameter of each of the theoretical distribution schemes, and the adjustment effect amplitude of each of the theoretical distribution schemes is taken 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.

6. An Internet of Things monitoring device for a trash can, characterized in that: include: A model building module, used to obtain road traffic information and trash can distribution information of a target area, and to build 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 collection module is used to continuously collect data on the collection status of each garbage bin in the target area to obtain garbage collection data of each garbage bin, and assign each garbage collection data to the corresponding unit simulation model to calculate the garbage distribution of the regional simulation model to obtain the garbage distribution map of the target area at each time; A data processing module is used to extract garbage distribution features from the garbage distribution map at each moment to obtain the garbage distribution features at each moment, and to calculate theoretical distribution schemes of each of the unit simulation models at each moment in the regional simulation model according to the garbage distribution features at each moment; The scheme analysis module is used to calculate and process the optimal distribution position of each of the unit simulation models based on the theoretical distribution scheme at each moment, so as to obtain the optimal distribution position of each of the unit simulation models.

7. A computer device comprising a memory and a processor, wherein the memory stores a computer program that can be run on the processor, characterized in that: When the processor executes the computer program, the Internet of Things monitoring method for a garbage can is implemented as described in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and when the computer program is executed by a processor, the processor executes an Internet of Things monitoring method for a garbage bin as described in any one of claims 1-5.

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