Urban management platform and method based on Internet of Things

Abstract

The invention relates to the technical field of city management, in particular to a city management platform and method based on the Internet of Things. The method comprises the following steps: acquiring an environment-friendly hand-held image, analyzing the environment-friendly hand-held image, and determining a garbage placement position and a garbage stacking condition; according to the garbage stacking condition, whether temporary clearing treatment is carried out or not is determined; if it is determined that temporary clearing and transporting treatment is carried out, a clearing and transporting place is determined according to the garbage placing position, and the garbage stacking condition and the clearing and transporting place are sent to clearing and transporting personnel to carry out timely clearing and transporting. The uploaded image is analyzed, whether temporary clearing is needed or not is judged more accurately, the number of unnecessary clearing times is reduced, and manpower and material resources are saved. The automatic clearing decision-making process reduces the on-site investigation and manual report work of environmental sanitation workers, and reduces the labor intensity. The problems of stink, pollution and the like caused by long-time stacking of the garbage can be effectively prevented by timely clearing and transporting the garbage, so that the urban environment quality is improved.

Description

Technical Field

[0001] The present application relates to the field of urban management technology, and in particular to an urban management platform and method based on the Internet of Things. Background Art

[0002] With the acceleration of urbanization, urban management is facing more and more challenges, especially the problem of urban garbage disposal. Traditional garbage collection methods often have problems such as low efficiency and untimely collection, which leads to environmental pollution and waste of resources. In order to solve these problems, the method of using Internet of Things technology for urban management has gradually received attention.

[0003] Among the existing urban management technologies, the application of environmental protection snapshots provides a new idea for urban garbage management. Through the environmental protection snapshots uploaded by users, the location and stacking of garbage can be obtained in real time, providing a basis for decision-making for the sanitation personnel. However, the existing technology still has some problems, such as the inability to dig out the root cause of the dirtiness of the garbage bins and solve the problem from the root, which will become an excessive workload burden for sanitation workers. Summary of the invention

[0004] The present application provides an Internet of Things-based city management platform and method to solve the above-mentioned problems.

[0005] In a first aspect, the present application provides an Internet of Things-based urban management method, the method comprising: Acquire environmental protection casually shot images, analyze the environmental protection casually shot images, and determine the location and stacking conditions of garbage; Determine whether to temporarily remove and transport the garbage based on the garbage dumping situation; If it is determined that temporary removal is to be carried out, the removal location is determined based on the location of the garbage, and the garbage stacking situation and the removal location are sent to the removal personnel for timely removal.

[0006] Through this solution, the location and stacking of garbage can be obtained in real time, so that the sanitation department can respond quickly and dispatch the removal resources in time. By analyzing the uploaded images, it is possible to more accurately determine whether temporary removal is needed, reduce unnecessary removal times, and save manpower and material resources. The automated removal decision process reduces the on-site investigation and manual reporting work of sanitation workers, reducing their labor intensity. Timely removal of garbage can effectively prevent the odor, pollution and other problems caused by long-term garbage stacking, thereby improving the quality of the urban environment. Analyzing the reasons for the messy garbage cans in the image, such as whether it is due to improper garbage classification, insufficient garbage can capacity or unreasonable removal frequency, can help solve the problem from the root. The collected data can be used to analyze the pattern of garbage generation and treatment, and provide support for the formulation of long-term urban garbage management strategies. The application of environmental protection snapshot images encourages citizens to participate in urban management and improves their environmental awareness and sense of participation. Through real-time monitoring and analysis of garbage stacking, removal resources can be allocated more reasonably to avoid resource waste.

[0007] Optionally, analyzing the environmental protection casual shot image to determine the garbage placement and garbage stacking situation includes: Analyze the environmental protection casual images to determine image interference factors; Analyze the interference factors of the image, determine the interference removal method, and standardize the environmental protection casual image according to the interference removal method to obtain a pure trash can image; Analyze the pure trash can image to determine the trash stacking situation; Obtain the upload source of the environmental protection casual shot image, and determine the garbage placement location based on the upload source.

[0008] Through this solution, the on-site investigation time of sanitation workers is reduced through automated image analysis, and the efficiency of garbage disposal is improved. The application of environmentally friendly snapshot images enables real-time monitoring of urban garbage problems, timely detection and treatment of garbage problems. Using image recognition technology, garbage types and quantities can be more accurately identified, providing more accurate data support for garbage disposal. By analyzing garbage bin images, garbage classification errors can be reduced and the accuracy of garbage classification can be improved. Real-time analysis of garbage stacking helps optimize the allocation of transportation resources and reduce unnecessary transportation operations. Provide data-based decision support for urban management decision makers to help them better formulate garbage management strategies.

[0009] Optionally, determining the garbage placement location according to the upload source includes: Determine the user's device information based on the upload source; Determining, according to the device information, whether the user allows obtaining the geographic location; If not allowed, the environmental protection casual image is analyzed to determine the angle of the trash can; Determine the shooting angle according to the trash can angle and the upload source; The garbage placement location is determined based on the shooting angle and the upload source.

[0010] Through this solution, by accurately determining the location of garbage, it is possible to reduce the time for garbage removal personnel to find garbage and improve the efficiency of garbage removal. After knowing the specific location of the garbage bin, more efficient removal routes can be planned to avoid unnecessary U-turns or detours of vehicles. Sanitation workers can respond to garbage problems more quickly, reduce workload and lighten their work burden. The determined garbage location can provide data support for urban management decision makers, helping them to better plan garbage collection and removal work. By reducing ineffective driving during the removal process, the use of removal resources can be optimized and urban management costs can be reduced.

[0011] Optionally, determining whether to perform temporary removal according to the garbage stacking situation includes: Based on the garbage placement location, obtaining a monitoring video of the garbage placement location; Analyze the surveillance video to determine the frequency of garbage placement; Determine the garbage removal time based on the garbage stacking situation and garbage delivery frequency; Obtaining an actual removal plan; analyzing the actual removal plan to determine whether the garbage removal time is within the removal plan for the garbage placement location; If so, clearing and transportation will be carried out according to the actual clearing and transportation plan; Determining the removal location according to the garbage placement location, and sending the garbage stacking situation and the removal location to the removal personnel for timely removal, including: If not, the removal location is determined based on the garbage placement location, and the garbage stacking situation and the removal location are sent to the removal personnel for timely removal.

[0012] Through this solution, the collection and transportation plan can be flexibly adjusted according to the garbage stacking situation, which can ensure that the garbage is cleaned up in time, avoid garbage accumulation, and improve the efficiency of collection and transportation. By analyzing the frequency of garbage delivery and the stacking situation, the collection and transportation resources can be allocated more reasonably to avoid resource waste. Timely response to garbage problems can reduce the workload of sanitation workers caused by garbage accumulation and improve job satisfaction. Ensuring that garbage is cleaned up in time can improve the level of urban environmental sanitation and improve the living environment of residents. According to the garbage stacking situation and the frequency of collection and transportation, data support is provided to urban management decision makers to help them better plan garbage collection and transportation. By analyzing the garbage stacking situation, problem-prone areas can be identified, providing clues for further root cause analysis of the problem. By collecting and analyzing data on garbage stacking, data-driven urban management can be achieved to improve the scientificity and accuracy of decision-making.

[0013] Optionally, determining the garbage removal time according to the garbage stacking situation and the garbage delivery frequency includes: Determine the peak period for garbage disposal based on the frequency of garbage disposal; Obtaining the upload time of the environmental protection casual image; Predicting changes in garbage stacking within a preset period of time based on the upload time, the peak period of garbage placement, and the frequency of garbage placement; Determine the type of trash can according to the environmental protection casual shot image; Determine the maximum capacity of the trash can according to the type of the trash can; The garbage removal time is determined according to the garbage stacking situation, the maximum capacity of the garbage bin and the garbage stacking changes.

[0014] Through this solution, by analyzing the frequency and peak period of garbage delivery, the collection time can be arranged more accurately, the empty driving and waiting time can be reduced, and the collection efficiency can be improved. According to the type and capacity of the garbage bin, as well as the garbage stacking situation, the collection vehicles and personnel can be reasonably allocated to optimize the use of resources. By predicting the changes in garbage stacking, garbage can be collected in time before it accumulates, reducing garbage accumulation and odor problems. By scientifically planning the collection time, the ineffective labor of sanitation workers can be reduced and their workload can be reduced. By obtaining the garbage stacking situation in real time, the collection plan can be adjusted in real time to improve the flexibility and response speed of urban management. Through accurate collection time scheduling, the quality of garbage collection services can be improved and residents' satisfaction can be increased. The collected data and analysis results can provide data support for urban management and help decision makers make more reasonable and effective decisions.

[0015] Optionally, determining the garbage removal time according to the garbage stacking situation, the maximum capacity of the garbage bin and the change in the garbage stacking includes: According to the garbage stacking situation, the maximum capacity of the garbage bin and the change in garbage stacking, the maximum time for the garbage capacity to reach the limit is determined and calculated according to the following formula: ; in, Indicates the limit duration; Indicates the change of said garbage dump; Indicates the maximum capacity of the trash can; Indicates the current garbage dumping amount included in the garbage dumping situation; represents the correction factor; The garbage removal time is determined according to the limit time and the upload time.

[0016] Through this solution, by real-time monitoring of garbage stacking, the demand for garbage removal can be predicted more accurately, unnecessary empty driving and waiting time can be reduced, and the removal efficiency can be improved. According to the capacity of the garbage bin and the change rate of garbage stacking, the removal resources, such as vehicles and personnel, can be reasonably allocated to avoid resource waste. Timely garbage removal can reduce garbage accumulation, reduce environmental pollution and public health risks. The formula provides a quantitative prediction tool to help managers predict the best time for garbage removal. By real-time monitoring of garbage stacking and change rate, managers can adjust the removal time according to actual conditions to ensure that garbage does not accumulate too much. The process and results of the formula derivation are based on data and analysis, which helps to promote urban management decision-making in the direction of data-driven. By considering the correction factor, the formula can more accurately reflect the variables and uncertainties that may exist in actual conditions.

[0017] Optionally, the sending of the garbage stacking situation and the removal location to the removal personnel includes: Retrieve the physical location of each cleaning personnel, and determine the appropriate personnel according to the cleaning location and the physical location; Assign each suitable person the task of cleaning and transportation; Analyze the removal task to determine whether there is any suitable person to remove the items along the route; If so, suitable personnel who are present in the garbage collection along the way will be selected as the best garbage collection personnel, and the garbage stacking situation and the garbage collection location will be sent to the best garbage collection personnel.

[0018] Through this solution, through GIS and real-time positioning technology, the garbage collectors can reach the garbage dumping site along the shortest path, reducing time and fuel consumption. Avoid multiple garbage collectors going to the same location to collect garbage and reduce unnecessary trips. The garbage collectors can quickly receive information about the garbage dumping and the collection location, and quickly respond to garbage collection needs. By avoiding repeated collection and optimizing resource allocation, the efficiency of resource use is improved. By reasonably allocating tasks, the labor intensity of garbage collectors is reduced.

[0019] Optionally, if the situation occurs, after the cleaning process is performed according to the actual cleaning plan, the method further includes: If it is determined that the garbage removal time is within the removal plan of the garbage placement location, obtaining the removal arrangement of the garbage placement location in the removal plan; Analyze the removal arrangement to determine the actual removal time of the garbage placement location; According to the upload time, the peak period of garbage placement and the frequency of garbage placement, predict the expected stacking situation of the garbage placement location when the actual removal time is reached; Determine whether to add additional trash cans based on the expected stacking situation and the maximum capacity of the trash cans.

[0020] Through this solution, by following the predetermined collection and transportation plan, it can ensure that garbage is cleared in time, reduce accumulation, and avoid environmental pollution. The collection and transportation personnel can know the collection and transportation time of the garbage placement location in advance, reducing the waiting and uncertainty time. According to the collection and transportation arrangements and garbage delivery conditions, the collection and transportation personnel and equipment can be allocated more accurately to avoid waste of resources. If the amount of garbage is predicted to increase, the collection and transportation plan can be adjusted in time to avoid overflowing the garbage bin. Record key information in the collection and transportation process, such as the amount of garbage, collection time, and garbage bin status, to provide data support for future decision-making. By analyzing the peak period of garbage delivery, you can prepare in advance, increase the frequency of collection or increase the number of garbage bins to ensure that the garbage is handled in time. By collecting and analyzing data, it can help identify the problem and provide a basis for long-term solutions.

[0021] Optionally, the suitable personnel who have the phenomenon of clearing and transporting along the way are selected as the best clearing and transporting personnel, including: Analyze the cleaning tasks of the suitable personnel who have the cleaning phenomenon along the way, and determine the cleaning and transportation capacity of each suitable personnel when they arrive at the garbage placement location; According to the garbage stacking situation, the garbage stacking changes and the transportation capacity, the suitable personnel are screened to obtain the best transportation personnel.

[0022] Through this solution, by analyzing the location data and routes of the cleaning personnel, the cleaning routes can be optimized, unnecessary driving distance and time can be reduced, and the cleaning efficiency can be improved. By selecting the cleaning personnel who have cleaning phenomena along the way as the best cleaning personnel, resources can be concentrated to improve the overall cleaning efficiency. By identifying and reducing the cleaning phenomena along the way, unnecessary waste of resources can be avoided. Selecting suitable personnel as the best cleaning personnel can help to reasonably allocate tasks and reduce the overload of individual personnel.

[0023] In a second aspect, the present application provides an Internet of Things-based city management platform, the platform comprising: An image analysis module is used to obtain environmental protection casual images, analyze the environmental protection casual images, and determine the location and stacking conditions of garbage; A processing and analysis module is used to determine whether to carry out temporary removal and transportation according to the garbage stacking situation; The removal analysis module is used to determine the removal location based on the garbage placement if it is determined that temporary removal is to be carried out, and to send the garbage stacking situation and the removal location to the removal personnel for timely removal.

[0024] Optionally, when the image analysis module analyzes the environmental protection casual shot image to determine the garbage placement location and garbage stacking situation, it is used to: Analyze the environmental protection casual images to determine image interference factors; Analyze the interference factors of the image, determine the interference removal method, and standardize the environmental protection casual image according to the interference removal method to obtain a pure trash can image; Analyze the pure trash can image to determine the trash stacking situation; Obtain the upload source of the environmental protection casual shot image, and determine the garbage placement location based on the upload source.

[0025] Optionally, when the image analysis module determines the location of the garbage according to the upload source, it is used to: Determine the user's device information based on the upload source; Determining, according to the device information, whether the user allows obtaining the geographic location; If not allowed, the environmental protection casual image is analyzed to determine the angle of the trash can; Determine the shooting angle according to the trash can angle and the upload source; The garbage placement location is determined based on the shooting angle and the upload source.

[0026] Optionally, when the processing and analysis module determines whether to perform temporary removal according to the garbage stacking situation, it is used to: Based on the garbage placement location, obtaining a monitoring video of the garbage placement location; Analyze the surveillance video to determine the frequency of garbage placement; Determine the garbage removal time based on the garbage stacking situation and garbage delivery frequency; Obtaining an actual removal plan; analyzing the actual removal plan to determine whether the garbage removal time is within the removal plan for the garbage placement location; If so, clearing and transportation will be carried out according to the actual clearing and transportation plan; When determining the removal location according to the garbage placement location, and sending the garbage stacking situation and the removal location to the removal personnel for timely removal, it is used to: If not, the removal location is determined based on the garbage placement location, and the garbage stacking situation and the removal location are sent to the removal personnel for timely removal.

[0027] Optionally, when the processing and analysis module determines the garbage removal time according to the garbage stacking situation and the garbage delivery frequency, it is used to: Determine the peak period for garbage disposal based on the frequency of garbage disposal; Obtaining the upload time of the environmental protection casual image; Predicting changes in garbage stacking within a preset period of time based on the upload time, the peak period of garbage placement, and the frequency of garbage placement; Determine the type of trash can according to the environmental protection casual shot image; Determine the maximum capacity of the trash can according to the type of the trash can; The garbage removal time is determined according to the garbage stacking situation, the maximum capacity of the garbage bin and the garbage stacking changes.

[0028] Optionally, when determining the garbage removal time according to the garbage stacking situation, the maximum capacity of the garbage bin and the garbage stacking change, the processing and analysis module is used to: According to the garbage stacking situation, the maximum capacity of the garbage bin and the change in garbage stacking, the maximum time for the garbage capacity to reach the limit is determined and calculated according to the following formula: ; in, Indicates the limit duration; Indicates the change of said garbage dump; Indicates the maximum capacity of the trash can; Indicates the current garbage dumping amount included in the garbage dumping situation; represents the correction factor; The garbage removal time is determined according to the limit time and the upload time.

[0029] Optionally, when the removal analysis module sends the garbage stacking situation and the removal location to the removal personnel, it is used to: Retrieve the physical location of each cleaning personnel, and determine the appropriate personnel according to the cleaning location and the physical location; Assign each suitable person the task of cleaning and transportation; Analyze the removal task to determine whether there is any suitable person to remove the items along the route; If so, suitable personnel who are present in the garbage collection along the way will be selected as the best garbage collection personnel, and the garbage stacking situation and the garbage collection location will be sent to the best garbage collection personnel.

[0030] Optionally, the city management platform further includes an additional analysis module for: If it is determined that the garbage removal time is within the removal plan of the garbage placement location, obtaining the removal arrangement of the garbage placement location in the removal plan; Analyze the removal arrangement to determine the actual removal time of the garbage placement location; According to the upload time, the peak period of garbage placement and the frequency of garbage placement, predict the expected stacking situation of the garbage placement location when the actual removal time is reached; Determine whether to add additional trash cans based on the expected stacking situation and the maximum capacity of the trash cans.

[0031] Optionally, when the cleaning and transportation analysis module uses suitable personnel with cleaning and transportation phenomena along the way as the best cleaning and transportation personnel, it is used to: Analyze the cleaning tasks of the suitable personnel who have the cleaning phenomenon along the way, and determine the cleaning and transportation capacity of each suitable personnel when they arrive at the garbage placement location; According to the garbage stacking situation, the garbage stacking changes and the transportation capacity, the suitable personnel are screened to obtain the best transportation personnel. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, a brief introduction will be given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0033] Figure 1 A schematic diagram of an application scenario provided for an embodiment of the present application; Figure 2 A flowchart of a city management method based on the Internet of Things provided in one embodiment of the present application; Figure 3 A schematic diagram of the structure of a city management platform based on the Internet of Things provided in one embodiment of the present application. DETAILED DESCRIPTION

[0034] In order to make the purpose, technical scheme and advantages of the embodiments of the present application clearer, the technical scheme in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0035] In addition, the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article, unless otherwise specified, generally means that the associated objects before and after are in an "or" relationship.

[0036] The embodiments of the present application are further described in detail below in conjunction with the drawings in the specification.

[0037] Among the existing urban management technologies, the application of environmental protection snapshots provides a new idea for urban garbage management. Through the environmental protection snapshots uploaded by users, the location and stacking of garbage can be obtained in real time, providing a basis for decision-making for the sanitation personnel. However, the existing technology still has some problems, such as the inability to dig out the root cause of the dirtiness of the garbage bins and solve the problem from the root, which will become an excessive workload burden for sanitation workers.

[0038] Based on this, the present application provides an urban management platform and method based on the Internet of Things, which obtains environmental protection casual images, analyzes environmental protection casual images, determines the location of garbage and the situation of garbage stacking; determines whether to carry out temporary removal according to the garbage stacking; if it is determined to carry out temporary removal, the removal location is determined according to the garbage placement location, and the garbage stacking situation and the removal location are sent to the removal personnel for timely removal. Real-time acquisition of garbage placement and stacking enables the sanitation department to respond quickly and dispatch removal resources in a timely manner. By analyzing the uploaded images, it is possible to more accurately determine whether temporary removal is required, reduce unnecessary removal times, and save manpower and material resources. The automated removal decision process reduces the on-site investigation and manual reporting work of sanitation workers and reduces their labor intensity. Timely removal of garbage can effectively prevent problems such as odor and pollution caused by long-term garbage stacking, thereby improving the quality of the urban environment. Analyzing the reasons for the mess in the garbage bin in the image, such as whether it is due to improper garbage classification, insufficient garbage bin capacity, or unreasonable removal frequency, helps to solve the problem from the root. The collected data can be used to analyze the patterns of garbage generation and disposal, and provide support for the formulation of long-term urban garbage management strategies. The application of environmental protection snapshot images encourages citizens to participate in urban management and improves their environmental awareness and sense of participation. Through real-time monitoring and analysis of garbage dumping, it is possible to more reasonably allocate transportation resources and avoid resource waste.

[0039] Figure 1 A schematic diagram of an application scenario provided by this application is provided. In the urban garbage management scenario, the method provided by this application is applied. Specifically, the method provided by this application is applied to any server, and the server and the equipment of the cleaning personnel interact with the urban management platform. By analyzing the images uploaded to the urban management platform, the garbage placement and stacking situation are determined, and sent to the equipment of the cleaning personnel, so that the sanitation department can respond quickly, dispatch cleaning resources in time, reduce unnecessary cleaning times, and save manpower and material resources. The automated cleaning decision process reduces the on-site investigation and manual reporting work of sanitation workers and reduces their labor intensity. Timely garbage removal can effectively prevent the stench and pollution caused by long-term garbage stacking, thereby improving the quality of the urban environment. Analyzing the reasons for the dirtiness of the garbage cans in the image, such as whether it is due to improper garbage classification, insufficient garbage can capacity or unreasonable cleaning frequency, etc., helps to solve the problem from the root. The collected data can be used to analyze the pattern of garbage generation and treatment, and provide support for the formulation of long-term urban garbage management strategies. The application of environmental protection casual images encourages citizens to participate in urban management and improve their environmental awareness and sense of participation. Through real-time monitoring and analysis of garbage dumping conditions, it is possible to allocate cleaning and transportation resources more reasonably and avoid waste of resources.

[0040] For specific implementation methods, please refer to the following embodiments.

[0041] Figure 2 This is a flowchart of a city management method based on the Internet of Things provided in an embodiment of the present application. The method of this embodiment can be applied to the server in the above scenario. Figure 2 As shown, the method includes: S201, obtaining environmental protection casually shot images, analyzing the environmental protection casually shot images, and determining the location and stacking conditions of garbage.

[0042] Environmental protection snapshot images can be images related to urban garbage taken by citizens or staff using mobile phones or other photographic equipment. They are usually used to record the placement and stacking of garbage, and are uploaded to the urban management platform through an application for subsequent analysis and processing.

[0043] The garbage placement location can be the specific geographical location of the garbage or garbage bin, including its specific coordinates in a street, park, residential area or other public place.

[0044] The garbage stacking situation may be the state of garbage stacking, including the type of garbage (such as recyclables, hazardous waste, wet garbage, etc.), quantity, volume, and whether it exceeds the capacity of the garbage bin.

[0045] Specifically, users use their smartphones to capture real-time images of garbage placement and upload them to the city management platform through an app. The platform records the time, location, and user information of the image upload, which are crucial for subsequent analysis. Image recognition technology is used to analyze the uploaded images to identify the location of the garbage cans, the type of garbage, and the stacking conditions. By comparing the standard garbage can images in the database, the degree of dirtiness and potential hygiene problems of the garbage cans can be identified. Combined with geographic location information (GPS) and image analysis results, the location of the garbage cans can be accurately determined. Analyze the stacking of garbage in the image, including the volume, type, and distribution of the garbage, to determine whether it has reached the level that requires removal.

[0046] S202: Determine whether to temporarily remove the garbage based on the garbage stacking situation.

[0047] Temporary removal and disposal can be an unplanned, immediate removal operation to quickly solve the garbage dumping problem caused by excessive garbage accumulation or improper placement.

[0048] Specifically, through algorithm analysis, combined with historical data and real-time monitoring, it is determined whether the current garbage situation requires temporary removal. If the garbage situation indicates that immediate disposal is required, the system will automatically mark the event and start the removal process.

[0049] S203: If it is determined that temporary removal is to be carried out, the removal location is determined based on the location of the garbage, and the garbage stacking situation and removal location are sent to the removal personnel for timely removal.

[0050] The collection point can be the destination of the garbage collection, which may be a garbage transfer station, garbage disposal site or other designated garbage collection point.

[0051] The haulage personnel may be sanitation workers or employees of a haulage company who are responsible for carrying out garbage collection work.

[0052] Removal can be the process of removing garbage from its placement location and transporting it to a designated location, including the collection, loading, transportation and unloading of garbage.

[0053] Specifically, if temporary removal is determined, the system will calculate the most suitable removal location and determine the best removal route based on the location of the garbage. The system will send information about the garbage stacking and removal location to the nearest removal personnel to ensure timely response. After receiving the notification, the removal personnel will promptly remove the garbage based on the provided location and garbage situation. After the removal is completed, the removal personnel can feedback the removal results through the application so that the system can update the data and optimize the subsequent removal plan.

[0054] Through this solution, the location and stacking of garbage can be obtained in real time, so that the sanitation department can respond quickly and dispatch the removal resources in time. By analyzing the uploaded images, it is possible to more accurately determine whether temporary removal is needed, reduce unnecessary removal times, and save manpower and material resources. The automated removal decision process reduces the on-site investigation and manual reporting work of sanitation workers, reducing their labor intensity. Timely removal of garbage can effectively prevent the odor, pollution and other problems caused by long-term garbage stacking, thereby improving the quality of the urban environment. Analyzing the reasons for the messy garbage cans in the image, such as whether it is due to improper garbage classification, insufficient garbage can capacity or unreasonable removal frequency, can help solve the problem from the root. The collected data can be used to analyze the pattern of garbage generation and treatment, and provide support for the formulation of long-term urban garbage management strategies. The application of environmental protection snapshot images encourages citizens to participate in urban management and improves their environmental awareness and sense of participation. Through real-time monitoring and analysis of garbage stacking, removal resources can be allocated more reasonably to avoid resource waste.

[0055] In some embodiments, the environmental protection casually-shot images are analyzed to determine image interference factors; the image interference factors are analyzed to determine the interference removal method, and based on the interference removal method, the environmental protection casually-shot images are standardized to obtain pure trash can images; the pure trash can images are analyzed to determine the garbage stacking situation; the upload source of the environmental protection casually-shot images is obtained, and the garbage placement location is determined based on the upload source.

[0056] Image interference factors can be elements that affect garbage identification and analysis in environmental protection casual photos, such as the sky, background buildings, reflections, shadows, passers-by, vehicles, animals, labels or text on garbage bags, etc.

[0057] The interference removal method may be a method for eliminating or reducing image interference factors, such as image filtering, edge detection, color segmentation, shape recognition, etc.

[0058] The pure trash can image may be an image after interference removal processing, in which interference factors have been effectively removed and only a clear image of the trash can and trash is included, which is convenient for subsequent trash identification and analysis.

[0059] The garbage stacking situation can be the distribution status of garbage in the garbage bin, including the type, quantity, volume of the garbage, whether it exceeds the capacity of the garbage bin, and whether it is correctly classified.

[0060] The upload source may be a device or application that uploads the environmental protection snapshot images, such as a smartphone, application, or a dedicated environmental protection snapshot platform used by the user.

[0061] The garbage placement location can be the specific location of the garbage or garbage bin in the real world, which is usually identified by geographic coordinates (such as longitude and latitude), and can also be combined with street names, buildings or other landmarks to further refine the location.

[0062] Specifically, the received environmental protection casual images are first preprocessed, including cropping, denoising, adjusting brightness and contrast, etc., to improve image quality for subsequent analysis. Image recognition technology is used to analyze images and identify possible interference factors, such as the sky, background buildings, reflections, shadows, etc. Machine learning algorithms are applied to train models to distinguish between garbage and interference factors. According to the identified interference factors, the corresponding removal method is determined, such as removing noise through image filtering, or removing unnecessary background elements through edge detection. According to the interference removal method, the image is processed to eliminate interference and obtain a pure trash can image. Ensure the consistency of the trash can image to facilitate subsequent garbage stacking analysis. Analyze the pure trash can image to identify the type, quantity and volume of garbage in the trash can. Use image recognition algorithms to identify the distribution and accumulation of garbage, such as whether the garbage exceeds the capacity of the trash can, whether there is any classification error, etc. Combine the geographic tags in the image (such as GPS coordinates) and image content analysis to determine the specific placement of the garbage. If the image contains street names, buildings or other landmarks, this information can be used to further pinpoint the location. Obtain the user information of the uploaded image, including the user's location, upload time, etc. This information helps to understand when and where the garbage problem occurred. Combine the above analysis results to form a complete garbage management report, including garbage type, stacking conditions, placement, upload time, etc. Feedback the analysis results to the removal personnel to guide their work.

[0063] Through this solution, the on-site investigation time of sanitation workers is reduced through automated image analysis, and the efficiency of garbage disposal is improved. The application of environmentally friendly snapshot images enables real-time monitoring of urban garbage problems, timely detection and treatment of garbage problems. Using image recognition technology, garbage types and quantities can be more accurately identified, providing more accurate data support for garbage disposal. By analyzing garbage bin images, garbage classification errors can be reduced and the accuracy of garbage classification can be improved. Real-time analysis of garbage stacking helps optimize the allocation of transportation resources and reduce unnecessary transportation operations. Provide data-based decision support for urban management decision makers to help them better formulate garbage management strategies.

[0064] In some embodiments, the user's device information is determined based on the upload source; based on the device information, it is determined whether the user allows the geographic location to be obtained; if not allowed, the environmental protection snapshot image is analyzed to determine the angle of the trash can; based on the trash can angle and the upload source, the shooting angle is determined; based on the shooting angle and the upload source, the garbage placement location is determined.

[0065] The trash can angle may be the relative position and direction of the trash can in the captured image.

[0066] The shooting angle can be the relative position and orientation of the camera with respect to the geographic location when the image was captured.

[0067] Specifically, the uploaded image is analyzed and image processing techniques are used to determine the angle of the trash can. This may include identifying features such as the edge, shape, and symmetry of the trash can. The tilt angle and direction of the trash can are calculated through image recognition algorithms, such as perspective transformation or Hough transformation. This helps to understand the relative position between the camera and the trash can when shooting. Obtain metadata for the uploaded image, including device information (such as mobile phone model, camera model), upload time, GPS coordinates, etc. This information helps to infer the type of device used when shooting, thereby providing clues for determining the shooting angle. Combining the angle of the trash can and the device information of the upload source, the angle of the user when shooting is inferred, including facing south, facing north, etc. Through this shooting angle, it can be determined where the trash can is located at the intersection or on which side of the lane, so as to facilitate the subsequent planning of the removal route without the need for the vehicle to turn around. Observe the background elements in the image, such as street names, building appearances, road signs, etc., which can all be used as auxiliary information for positioning. If the image contains GPS coordinates, these coordinate information can be directly used to determine the location of the trash. If there are no direct geographic coordinates, the location can be matched based on the trash can angle in the image and landmarks or street features combined with the map service API. The angle of the trash can, shooting angle, device information of the upload source, image background and geographic coordinate data are combined to determine the exact location of the garbage through algorithms or manual review.

[0068] Through this solution, by accurately determining the location of garbage, it is possible to reduce the time for garbage removal personnel to find garbage and improve the efficiency of garbage removal. After knowing the specific location of the garbage bin, more efficient removal routes can be planned to avoid unnecessary U-turns or detours of vehicles. Sanitation workers can respond to garbage problems more quickly, reduce workload and lighten their work burden. The determined garbage location can provide data support for urban management decision makers, helping them to better plan garbage collection and removal work. By reducing ineffective driving during the removal process, the use of removal resources can be optimized and urban management costs can be reduced.

[0069] In some embodiments, based on the garbage placement location, a surveillance video of the garbage placement location is obtained; the surveillance video is analyzed to determine the frequency of garbage disposal; the garbage removal time is determined based on the garbage stacking situation and the frequency of garbage disposal; the actual removal plan is obtained; the actual removal plan is analyzed to determine whether the garbage removal time is within the removal plan of the garbage placement location; if so, the garbage removal is carried out according to the actual removal plan; if not, the removal location is determined based on the garbage placement location, and the garbage stacking situation and the removal location are sent to the removal personnel for timely removal.

[0070] Garbage disposal frequency can be the frequency at which garbage is placed into a trash can within a certain period of time. It is an important indicator to measure the efficiency of garbage generation and collection.

[0071] The garbage removal time can be the time point for garbage collection and transportation set according to the frequency and stacking of garbage.

[0072] The actual collection plan may be a component of the garbage collection plan formulated by the urban management or sanitation department, which includes the collection time, route, frequency, etc.

[0073] Specifically, first, use environmental protection snapshots or surveillance videos to analyze the location and stacking of garbage. Analyze the frequency of garbage placement based on the surveillance video of the garbage placement location. Determine the time pattern and frequency of garbage placement through surveillance video analysis. Observe the garbage stacking situation, including the type, quantity, volume of garbage, and whether it exceeds the capacity of the garbage bin. Determine the best garbage collection time based on the frequency and stacking of garbage and the existing garbage collection plan. Obtain the actual garbage collection plan from the urban garbage management system, including the collection route, timetable, etc. Analyze the actual collection plan to determine whether the collection time of the garbage placement location is included. If the collection time of the garbage placement location is already included in the actual collection plan, it will be executed according to the plan. If not, decide whether temporary collection is needed based on the garbage stacking situation. If temporary collection is needed, determine the appropriate collection location based on the garbage placement location. Send the garbage stacking situation and the determined collection location to the collection personnel so that they can collect and transport it in time. The collection personnel will carry out temporary collection based on the information received to ensure that the garbage is cleared in time.

[0074] Through this solution, the collection and transportation plan can be flexibly adjusted according to the garbage stacking situation, which can ensure that the garbage is cleaned up in time, avoid garbage accumulation, and improve the efficiency of collection and transportation. By analyzing the frequency of garbage delivery and the stacking situation, the collection and transportation resources can be allocated more reasonably to avoid resource waste. Timely response to garbage problems can reduce the workload of sanitation workers caused by garbage accumulation and improve job satisfaction. Ensuring that garbage is cleaned up in time can improve the level of urban environmental sanitation and improve the living environment of residents. According to the garbage stacking situation and the frequency of collection and transportation, data support is provided to urban management decision makers to help them better plan garbage collection and transportation. By analyzing the garbage stacking situation, problem-prone areas can be identified, providing clues for further root cause analysis of the problem. By collecting and analyzing data on garbage stacking, data-driven urban management can be achieved to improve the scientificity and accuracy of decision-making.

[0075] In some embodiments, the peak period of garbage disposal is determined based on the frequency of garbage disposal; the upload time of the environmental protection snapshot image is obtained; the changes in garbage stacking within a preset time period are predicted based on the upload time, the peak period of garbage disposal and the frequency of garbage disposal; the type of garbage bin is determined based on the environmental protection snapshot image; the maximum capacity of the garbage bin is determined based on the type of garbage bin; the garbage removal time is determined based on the garbage stacking situation, the maximum capacity of the garbage bin and the changes in garbage stacking.

[0076] The peak period of garbage disposal can be the period when the amount of garbage disposal increases significantly within a certain period of time.

[0077] The upload time may be the time point when the user uploads the image through the environmental protection snap shooting platform.

[0078] The garbage stacking change within the preset time period may be an expected change trend of the garbage stacking amount within a predetermined time period, and the preset time period may be stored in a preset database.

[0079] The trash can types may be different kinds of trash cans for classifying and collecting different kinds of trash.

[0080] The maximum capacity of a trash can may be the maximum volume or weight of trash that the trash can can hold.

[0081] Specifically, collect historical data, analyze the frequency of garbage disposal, and determine the peak period of garbage disposal. Collect image data uploaded by users through the environmental protection snap platform. Extract the upload time from the collected images for subsequent analysis. Combine the frequency of garbage disposal and the upload time to further confirm the peak period of garbage disposal. Use time series analysis or machine learning algorithms to predict the changes in garbage stacking within a preset period based on the upload time and the peak period of disposal. Use image recognition technology to identify the type of garbage can from the environmental protection snap images. According to the identified type of garbage can, refer to relevant information or databases to determine the maximum capacity of the garbage can. Analyze the garbage stacking conditions shown in the environmental protection snap images, including the amount and distribution of garbage. Compare the actual garbage stacking conditions with the maximum capacity of the garbage can to evaluate whether the capacity of the garbage can is close to or full. Determine the best time for garbage removal based on the predicted changes in garbage stacking, the type and capacity of the garbage can, and the actual garbage stacking conditions. Integrate information such as predicted data, garbage stacking conditions, and garbage can capacity to form a comprehensive garbage removal time decision. According to the determined removal time, formulate a detailed removal plan, including removal routes, removal schedules, etc. Send the collection schedule to your haulers to make sure they know when and where the trash will be collected.

[0082] Through this solution, by analyzing the frequency and peak period of garbage delivery, the collection time can be arranged more accurately, the empty driving and waiting time can be reduced, and the collection efficiency can be improved. According to the type and capacity of the garbage bin, as well as the garbage stacking situation, the collection vehicles and personnel can be reasonably allocated to optimize the use of resources. By predicting the changes in garbage stacking, garbage can be collected in time before it accumulates, reducing garbage accumulation and odor problems. By scientifically planning the collection time, the ineffective labor of sanitation workers can be reduced and their workload can be reduced. By obtaining the garbage stacking situation in real time, the collection plan can be adjusted in real time to improve the flexibility and response speed of urban management. Through accurate collection time scheduling, the quality of garbage collection services can be improved and residents' satisfaction can be increased. The collected data and analysis results can provide data support for urban management and help decision makers make more reasonable and effective decisions.

[0083] In some embodiments, the maximum time for the garbage capacity to reach the limit is determined based on the garbage stacking situation, the maximum capacity of the garbage bin and the change in garbage stacking, and the garbage removal time is determined based on the maximum time and the upload time according to the following formula (1).

[0084] (1) in, Indicates the limit duration; Indicates changes in garbage dumping; Indicates the maximum capacity of the trash can; Indicates the current amount of garbage piled up as contained in the garbage pile situation; represents the correction factor; The maximum time limit can be the time required for the amount of garbage to increase to the maximum capacity of the garbage bin based on the current amount of garbage piled.

[0085] The correction factor can be a mathematical adjustment parameter introduced when predicting the time required for the garbage capacity to reach the limit (limit duration), taking into account various uncertainties that may exist in actual operations.

[0086] Specifically, the garbage dumping situation is collected through environmental protection snapshot images, including the current amount of garbage dumping. . Get the maximum capacity of the trash can The amount of garbage pile increases linearly with time, then ,in is the time interval when the trash bin is increased from its current capacity Increase to maximum capacity When . Analyze the recent trend of garbage dumping and obtain the garbage dumping change rate Since the amount of garbage pile increases linearly with time, we can calculate the time required It is expressed as: ; In actual situations, the rate of change of garbage deposits may not be constant, or there may be other factors that affect garbage deposits, so a correction factor needs to be introduced . Use formula (1) to calculate the maximum time for the garbage capacity to reach the limit. According to the calculated maximum time (T) and the upload time of the environmental protection casual photos, determine the best time for garbage removal. If the garbage pile change rate is low, the removal time can be appropriately postponed. Consider the correction factor factors, including weather changes, holidays, special events, etc., which may affect the generation and removal of garbage and can be corrected through work experience.

[0087] Through this solution, by real-time monitoring of garbage stacking, the demand for garbage removal can be predicted more accurately, unnecessary empty driving and waiting time can be reduced, and the removal efficiency can be improved. According to the capacity of the garbage bin and the change rate of garbage stacking, the removal resources, such as vehicles and personnel, can be reasonably allocated to avoid resource waste. Timely garbage removal can reduce garbage accumulation, reduce environmental pollution and public health risks. The formula provides a quantitative prediction tool to help managers predict the best time for garbage removal. By real-time monitoring of garbage stacking and change rate, managers can adjust the removal time according to actual conditions to ensure that garbage does not accumulate too much. The process and results of the formula derivation are based on data and analysis, which helps to promote urban management decision-making in the direction of data-driven. By considering the correction factor, the formula can more accurately reflect the variables and uncertainties that may exist in actual conditions.

[0088] In some embodiments, the physical location of each haulage personnel is retrieved, and suitable personnel are determined based on the haulage location and physical location; the haulage tasks of each suitable personnel are retrieved; the haulage tasks are analyzed to determine whether there is any suitable personnel available for haulage along the way; if so, the suitable personnel available for haulage along the way are selected as the best haulage personnel, and the garbage stacking situation and haulage location are sent to the best haulage personnel.

[0089] Physical positioning can be determined by GPS, Beidou navigation system, wireless signals or other positioning technologies to determine the specific location on the earth.

[0090] Suitable personnel may be those who are selected to perform a specific removal task based on specific criteria such as distance, skills, availability, etc.

[0091] Removal tasks can be a series of tasks that move waste from the point of generation to the treatment site, including collection, transportation and treatment.

[0092] The phenomenon of along-the-way removal may be that the removal personnel deal with other garbage dumping sites on the way to the target location.

[0093] The best hauler can be the one who is selected to perform a specific haulage task based on a series of evaluation criteria (such as distance, efficiency, experience, etc.).

[0094] Specifically, use GPS or other positioning technology to obtain the real-time physical location of each hauler. Based on the haulage location and the physical location of the hauler, use the Geographic Information System (GIS) to determine the hauler closest to the garbage dump location. Consider the distance, task volume, and personnel availability to assign corresponding haulage tasks to each suitable person, including cleaning of garbage dumps, garbage collection, etc. Analyze the tasks assigned to the haulers and check whether there are multiple people who need to go to the same location to haul garbage. If one or more people are hauling garbage along the same route, this indicates that there may be a waste of resources. If haulage is found along the way, select one of them as the best hauler to be responsible for cleaning all relevant garbage dumps. The selection of the best hauler may be based on factors such as distance, task volume, and work efficiency. Send information about garbage dumping and haulage locations to the best hauler's mobile device or work platform. The information may include the specific location of the garbage dump, the type of garbage, the required haulage tools, etc. The best hauler performs the haulage task based on the received information. During the haulage process, communication with other relevant personnel, such as the operator of the garbage treatment facility, may be required.

[0095] Through this solution, through GIS and real-time positioning technology, the garbage collectors can reach the garbage dumping site along the shortest path, reducing time and fuel consumption. Avoid multiple garbage collectors going to the same location to collect garbage and reduce unnecessary trips. The garbage collectors can quickly receive information about the garbage dumping and the collection location, and quickly respond to garbage collection needs. By avoiding repeated collection and optimizing resource allocation, the efficiency of resource use is improved. By reasonably allocating tasks, the labor intensity of garbage collectors is reduced.

[0096] In some embodiments, if it is determined that the garbage removal time is within the removal plan of the garbage placement location, the removal arrangement of the garbage placement location in the removal plan is obtained; the removal arrangement is analyzed to determine the actual removal time of the garbage placement location; based on the upload time, peak period of garbage placement and frequency of garbage placement, the expected stacking situation of the garbage placement location when the actual removal time is reached is predicted; based on the expected stacking situation and the maximum capacity of the garbage bin, it is determined whether to add a garbage bin.

[0097] The collection arrangement can be a series of plans for garbage collection formulated based on factors such as the amount of garbage generated, the capacity of the garbage bin, the service area, and environmental protection requirements, including the frequency of collection, collection routes, personnel allocation, etc.

[0098] The expected stacking situation can be a prediction of the stacking state that the garbage placement location may reach within a specific time based on the historical data and current trends of garbage disposal.

[0099] Specifically, determine whether the current time is in the collection and transportation plan of the garbage placement location. If the current time is in line with the collection and transportation plan, obtain the collection and transportation arrangement of the garbage placement location, including the collection and transportation frequency, collection and transportation route, etc. According to the collection and transportation arrangement, determine the actual collection and transportation time of the garbage placement location. Analyze the peak period of garbage disposal and predict the expected stacking situation of the garbage placement location when the actual collection and transportation time is reached. According to the frequency of garbage disposal, predict the expected stacking situation of the garbage placement location when the actual collection and transportation time is reached. Compare the predicted expected stacking situation with the maximum capacity of the garbage bin. If the expected stacking situation is close to or exceeds the maximum capacity of the garbage bin, consider adding garbage bins. If conditions permit, the number or capacity of garbage bins can be increased to accommodate the increase in garbage volume. According to the collection and transportation arrangement, perform the collection and transportation tasks, including collecting, transporting and processing garbage. Record key information in the collection and transportation process, such as garbage volume, collection and transportation time, garbage bin status, etc., for subsequent analysis and optimization. After the collection and transportation task is completed, collect feedback from the collection and transportation personnel, including task completion status, resource utilization efficiency, etc.

[0100] Through this solution, by following the predetermined collection and transportation plan, it can ensure that garbage is cleared in time, reduce accumulation, and avoid environmental pollution. The collection and transportation personnel can know the collection and transportation time of the garbage placement location in advance, reducing the waiting and uncertainty time. According to the collection and transportation arrangements and garbage delivery conditions, the collection and transportation personnel and equipment can be allocated more accurately to avoid waste of resources. If the amount of garbage is predicted to increase, the collection and transportation plan can be adjusted in time to avoid overflowing the garbage bin. Record key information in the collection and transportation process, such as the amount of garbage, collection time, and garbage bin status, to provide data support for future decision-making. By analyzing the peak period of garbage delivery, you can prepare in advance, increase the frequency of collection or increase the number of garbage bins to ensure that the garbage is handled in time. By collecting and analyzing data, it can help identify the problem and provide a basis for long-term solutions.

[0101] In some embodiments, the transportation tasks of suitable personnel who are involved in the transportation along the way are analyzed to determine the transportation capacity of each suitable personnel when they arrive at the garbage placement location; based on the garbage stacking situation, garbage stacking changes and transportation capacity, suitable personnel are screened to obtain the best transportation personnel.

[0102] Specifically, analyze the location data and routes of the removal personnel, and identify the removal points where there is removal along the way. Evaluate the removal efficiency of the removal personnel along the way, including the removal speed, garbage processing volume, etc. Analyze the task allocation of the removal personnel where there is removal along the way, including the removal frequency, route, task volume, etc. Determine the removal capacity of the removal personnel, that is, the amount of garbage they can handle in a specific time. Compare the removal capacity of each suitable person based on the removal capacity and garbage stacking situation. Consider factors such as the distance, efficiency, and capacity of the removal personnel to screen out the best removal personnel. Assign the garbage placement location and removal tasks to the best removal personnel. The best removal personnel perform the removal work according to the assigned tasks.

[0103] Through this solution, by analyzing the location data and routes of the cleaning personnel, the cleaning routes can be optimized, unnecessary driving distance and time can be reduced, and the cleaning efficiency can be improved. By selecting the cleaning personnel who have cleaning phenomena along the way as the best cleaning personnel, resources can be concentrated to improve the overall cleaning efficiency. By identifying and reducing the cleaning phenomena along the way, unnecessary waste of resources can be avoided. Selecting suitable personnel as the best cleaning personnel can help to reasonably allocate tasks and reduce the overload of individual personnel.

[0104] Figure 3 A schematic diagram of a city management platform based on the Internet of Things provided in one embodiment of the present application is shown in FIG. Figure 3 As shown, the city management platform 300 based on the Internet of Things of this embodiment includes: an image analysis module 301, a processing analysis module 302, and a removal analysis module 303.

[0105] The image analysis module 301 is used to obtain environmental protection casually shot images, analyze the environmental protection casually shot images, and determine the garbage placement location and garbage stacking situation; The processing and analysis module 302 is used to determine whether to perform temporary removal according to the garbage stacking situation; The removal analysis module 303 is used to determine the removal location according to the garbage placement position if it is determined to carry out temporary removal, and send the garbage stacking situation and the removal location to the removal personnel for timely removal.

[0106] Optionally, when the image analysis module 301 analyzes the environmental protection casual shot image to determine the garbage placement location and garbage stacking situation, it is used to: Analyze the environmental protection casual images to determine image interference factors; Analyze the interference factors of the image, determine the interference removal method, and standardize the environmental protection casual image according to the interference removal method to obtain a pure trash can image; Analyze the pure trash can image to determine the trash stacking situation; Obtain the upload source of the environmental protection casual shot image, and determine the garbage placement location based on the upload source.

[0107] Optionally, when the image analysis module 301 determines the location of the garbage according to the upload source, it is used to: Determine the user's device information based on the upload source; Determining, according to the device information, whether the user allows obtaining the geographic location; If not allowed, the environmental protection casual image is analyzed to determine the angle of the trash can; Determine the shooting angle according to the trash can angle and the upload source; The garbage placement location is determined based on the shooting angle and the upload source.

[0108] Optionally, when the processing and analysis module 302 determines whether to perform temporary removal according to the garbage stacking situation, it is used to: Based on the garbage placement location, obtaining a monitoring video of the garbage placement location; Analyze the surveillance video to determine the frequency of garbage placement; Determine the garbage removal time based on the garbage stacking situation and garbage delivery frequency; Obtaining an actual removal plan; analyzing the actual removal plan to determine whether the garbage removal time is within the removal plan for the garbage placement location; If so, clearing and transportation will be carried out according to the actual clearing and transportation plan; When determining the removal location according to the garbage placement location, and sending the garbage stacking situation and the removal location to the removal personnel for timely removal, it is used to: If not, the removal location is determined based on the garbage placement location, and the garbage stacking situation and the removal location are sent to the removal personnel for timely removal.

[0109] Optionally, when determining the garbage removal time according to the garbage stacking situation and the garbage delivery frequency, the processing and analysis module 302 is used to: Determine the peak period for garbage disposal based on the frequency of garbage disposal; Obtaining the upload time of the environmental protection casual image; Predicting changes in garbage stacking within a preset period of time based on the upload time, the peak period of garbage placement, and the frequency of garbage placement; Determine the type of trash can according to the environmental protection casual shot image; Determine the maximum capacity of the trash can according to the type of the trash can; The garbage removal time is determined according to the garbage stacking situation, the maximum capacity of the garbage bin and the garbage stacking changes.

[0110] Optionally, when determining the garbage removal time according to the garbage stacking situation, the maximum capacity of the garbage bin and the garbage stacking change, the processing and analysis module 302 is used to: According to the garbage stacking situation, the maximum capacity of the garbage bin and the change in garbage stacking, the maximum time for the garbage capacity to reach the limit is determined and calculated according to the following formula: ; in, Indicates the limit duration; Indicates the change of said garbage dump; Indicates the maximum capacity of the trash can; Indicates the current garbage dumping amount included in the garbage dumping situation; represents the correction factor; The garbage removal time is determined according to the limit time and the upload time.

[0111] Optionally, when the removal analysis module 303 sends the garbage stacking situation and the removal location to the removal personnel, it is used to: Retrieve the physical location of each cleaning personnel, and determine the appropriate personnel according to the cleaning location and the physical location; Assign each suitable person the task of cleaning and transportation; Analyze the removal task to determine whether there is any suitable person to remove the items along the route; If so, suitable personnel who are present in the garbage collection along the way will be selected as the best garbage collection personnel, and the garbage stacking situation and the garbage collection location will be sent to the best garbage collection personnel.

[0112] Optionally, the city management platform 300 further includes an additional analysis module 304, which is used to: If it is determined that the garbage removal time is within the removal plan of the garbage placement location, obtaining the removal arrangement of the garbage placement location in the removal plan; Analyze the removal arrangement to determine the actual removal time of the garbage placement location; According to the upload time, the peak period of garbage placement and the frequency of garbage placement, predict the expected stacking situation of the garbage placement location when the actual removal time is reached; Determine whether to add additional trash cans based on the expected stacking situation and the maximum capacity of the trash cans.

[0113] Optionally, when the cleaning and transportation analysis module 303 selects suitable personnel with cleaning and transportation phenomena along the way as the best cleaning and transportation personnel, it is used to: Analyze the cleaning tasks of the suitable personnel who have the cleaning phenomenon along the way, and determine the cleaning and transportation capacity of each suitable personnel when they arrive at the garbage placement location; According to the garbage stacking situation, the garbage stacking changes and the transportation capacity, the suitable personnel are screened to obtain the best transportation personnel.

[0114] The platform of this embodiment can be used to execute the method of any of the above embodiments, and its implementation principles and technical effects are similar and will not be repeated here.

Claims

1. A city management method based on the Internet of Things, characterized in that: include: Acquire environmental protection casually shot images, analyze the environmental protection casually shot images, and determine the location and stacking conditions of garbage; Determine whether to temporarily remove and transport the garbage based on the garbage dumping situation; If it is determined that temporary removal is to be carried out, the removal location is determined based on the location of the garbage, and the garbage stacking situation and the removal location are sent to the removal personnel for timely removal.

2. The method according to claim 1, characterized in that The analyzing of the environmental protection casually shot images to determine the location of garbage and the garbage stacking conditions includes: Analyze the environmental protection casual images to determine image interference factors; Analyze the interference factors of the image, determine the interference removal method, and standardize the environmental protection casual image according to the interference removal method to obtain a pure trash can image; Analyze the pure trash can image to determine the trash stacking situation; Obtain the upload source of the environmental protection casual shot image, and determine the garbage placement location based on the upload source.

3. The method according to claim 2, characterized in that Determining the garbage placement location according to the upload source includes: Determine the user's device information according to the upload source; Determining, according to the device information, whether the user allows obtaining the geographic location; If not allowed, the environmental protection casual image is analyzed to determine the angle of the trash can; Determine the shooting angle according to the trash can angle and the upload source; The garbage placement location is determined based on the shooting angle and the upload source.

4. The method according to claim 1, characterized in that: Determining whether to carry out temporary removal and transportation according to the garbage stacking situation includes: Based on the garbage placement location, obtaining a monitoring video of the garbage placement location; Analyze the surveillance video to determine the frequency of garbage placement; Determine the garbage removal time based on the garbage stacking situation and garbage delivery frequency; Obtaining an actual removal plan; analyzing the actual removal plan to determine whether the garbage removal time is within the removal plan for the garbage placement location; If so, clearing and transportation will be carried out according to the actual clearing and transportation plan; Determining the removal location according to the garbage placement location, and sending the garbage stacking situation and the removal location to the removal personnel for timely removal, including: If not, the removal location is determined based on the garbage placement location, and the garbage stacking situation and the removal location are sent to the removal personnel for timely removal.

5. The method according to claim 4, characterized in that Determining the garbage removal time according to the garbage stacking situation and garbage delivery frequency includes: Determine the peak period for garbage disposal based on the frequency of garbage disposal; Obtaining the upload time of the environmental protection casual image; Predicting changes in garbage stacking within a preset period of time according to the upload time, the peak period of garbage placement, and the frequency of garbage placement; Determine the type of trash can according to the environmental protection casual shot image; Determine the maximum capacity of the trash can according to the type of the trash can; The garbage removal time is determined according to the garbage stacking situation, the maximum capacity of the garbage bin and the garbage stacking changes.

6. The method according to claim 5, characterized in that The determining of the garbage removal time according to the garbage stacking situation, the maximum capacity of the garbage bin and the change of the garbage stacking includes: According to the garbage stacking situation, the maximum capacity of the garbage bin and the change in garbage stacking, the maximum time for the garbage capacity to reach the limit is determined and calculated according to the following formula: ； in, Indicates the limit duration; Indicates the change of said garbage dump; Indicates the maximum capacity of the trash can; Indicates the current garbage dumping amount included in the garbage dumping situation; represents the correction factor; The garbage removal time is determined according to the limit time and the upload time.

7. The method according to claim 5, characterized in that The sending of the garbage stacking situation and the removal location to the removal personnel includes: Retrieve the physical location of each cleaning personnel, and determine the appropriate personnel according to the cleaning location and the physical location; Assign each suitable person the task of cleaning and transportation; Analyze the removal task to determine whether there is any suitable person to remove the items along the route; If so, suitable personnel who are present in the garbage collection along the way will be selected as the best garbage collection personnel, and the garbage stacking situation and the garbage collection location will be sent to the best garbage collection personnel.

8. The method according to claim 5, characterized in that If so, after the cleaning and transportation is performed according to the actual cleaning and transportation plan, the method further includes: If it is determined that the garbage removal time is within the removal plan of the garbage placement location, obtaining the removal arrangement of the garbage placement location in the removal plan; Analyze the removal arrangement to determine the actual removal time of the garbage placement location; According to the upload time, the peak period of garbage placement and the frequency of garbage placement, predict the expected stacking situation of the garbage placement location when the actual removal time is reached; Determine whether to add additional trash cans based on the expected stacking situation and the maximum capacity of the trash cans.

9. The method according to claim 7, characterized in that: The best cleaning personnel include: Analyze the cleaning tasks of the suitable personnel who have the cleaning phenomenon along the way, and determine the cleaning and transportation capacity of each suitable personnel when they arrive at the garbage placement location; According to the garbage stacking situation, the garbage stacking changes and the transportation capacity, the suitable personnel are screened to obtain the best transportation personnel.

10. An urban management platform based on the Internet of Things, characterized in that: include: An image analysis module is used to obtain environmental protection casual images, analyze the environmental protection casual images, and determine the location and stacking conditions of garbage; A processing and analysis module is used to determine whether to carry out temporary removal and transportation according to the garbage stacking situation; The removal analysis module is used to determine the removal location based on the garbage placement if it is determined that temporary removal is to be carried out, and to send the garbage stacking situation and the removal location to the removal personnel for timely removal.

Images