Traceability Method for Kitchen Waste Collection and Transportation Information in Smart Property Management Platform

Abstract

The present invention relates to the technical field of data processing, and specifically relates to a method for traceability of kitchen waste collection and transportation information in a smart property management platform, including: obtaining kitchen waste collection and transportation information corresponding to multiple kitchen waste collection and transportation links; analyzing the path structure trends of multiple position nodes in each kitchen waste collection and transportation link according to the kitchen waste collection and transportation information to determine the traceability requirements of the kitchen waste collection and transportation information corresponding to each kitchen waste collection and transportation link; based on the pre-installed smart property management platform, scheduling and processing the kitchen waste collection and transportation resources of the position nodes in the kitchen waste collection and transportation link according to the traceability requirements of the kitchen waste collection and transportation information corresponding to each kitchen waste collection and transportation link. In this application, by performing data processing on the kitchen waste collection and transportation information corresponding to multiple kitchen waste collection and transportation links, the traceability requirements of the kitchen waste collection and transportation information corresponding to each of the kitchen waste collection and transportation links are determined, so as to efficiently trace the kitchen waste collection and transportation information.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and specifically relates to a method for traceability of food waste collection and transportation information in an intelligent property management platform. Background Art

[0002] An intelligent property management platform is an integrated management service platform that combines new-generation information technologies such as the Internet of Things, cloud computing, big data, and mobile Internet.

[0003] The intelligent property management platform can achieve traceability of food waste collection and transportation information through various methods. For example: using Internet of Things devices, such as sensors on smart trash cans, to collect data, and real-time record information such as the food waste disposal time and weight and upload it to the platform; installing positioning devices on collection and transportation vehicles to display the driving trajectory in real time to ensure collection and transportation along the specified route; assigning QR codes or tags to trash cans or collection and transportation containers, and scanning the codes during collection and transportation to record and associate information; recording the identity information and operation records of collection and transportation personnel to ensure traceability of responsibilities; taking photos during the collection and transportation process with in-vehicle or handheld devices to record the garbage status and collection and transportation site conditions, etc., and at the same time, associating information on links such as garbage disposal, collection and transportation, and treatment to form a complete information chain. When there are abnormal conditions in the actual property management operation process of garbage collection and transportation, it can quickly and accurately locate the abnormal collection and transportation path nodes, and perform dispatching and processing of resources such as garbage collection and transportation vehicles subsequently.

[0004] In the operation process of food waste collection and transportation information in the intelligent property management platform, information collection is usually realized by multiple waste classification storage location information in different communities and different time nodes of different collection and transportation operations of waste collection and transportation vehicles. The food waste collection and transportation information will show relatively obvious path structure information at the data level, that is, the actual geographical location structure of the route of the waste collection and transportation vehicle passing through the waste classification storage locations in the community during the collection and transportation process. For the waste collection and transportation process with abnormal conditions, the dispatching and processing of resources such as waste collection and transportation vehicles in property management should be an efficient processing realized in the information traceability process, and it is necessary to adjust the traceability information for the food waste collection and transportation situation with multiple collection and transportation path information.

[0005] Therefore, how to efficiently trace the food waste collection and transportation information in the intelligent property management platform is an urgent problem to be solved at present. Summary of the Invention

[0006] In order to solve the technical problem of how to efficiently trace the food waste collection and transportation information in the intelligent property management platform, the purpose of the present invention is to provide a method for traceability of food waste collection and transportation information in an intelligent property management platform, and the specific technical solution adopted is as follows:

[0007] An embodiment of the present application provides a method for tracing the collection and transportation information of kitchen waste in a smart property management platform. The method includes:

[0008] Obtain the kitchen waste collection and transportation information corresponding to multiple kitchen waste collection and transportation links;

[0009] According to the kitchen waste collection and transportation information, analyze the path structure trends of multiple location nodes in each kitchen waste collection and transportation link to determine the traceability requirements for the kitchen waste collection and transportation information corresponding to each kitchen waste collection and transportation link;

[0010] Based on the pre-installed smart property management platform, according to the traceability requirements for the kitchen waste collection and transportation information corresponding to each kitchen waste collection and transportation link, schedule the kitchen waste collection and transportation resources of the location nodes in the kitchen waste collection and transportation link.

[0011] In some embodiments, the multiple kitchen waste collection and transportation links include a kitchen waste storage link, a kitchen waste transportation link, a kitchen waste cleaning link, and a kitchen waste storage equipment cleaning link. The obtaining of the kitchen waste collection and transportation information corresponding to multiple kitchen waste collection and transportation links includes:

[0012] Through pre-installed sensors, obtain the location information and status information of the kitchen waste storage equipment in the kitchen waste storage link;

[0013] Through pre-installed positioning equipment, obtain the driving route, stop points, and collection and transportation time of the kitchen waste transportation vehicle in the kitchen waste transportation link;

[0014] Through pre-configured scanning equipment, obtain the cleaning operation information corresponding to the kitchen waste cleaning operator in the kitchen waste cleaning link;

[0015] Obtain the cleaning operation information of the kitchen waste storage equipment in the kitchen waste storage equipment cleaning link.

[0016] In some embodiments, the analyzing of the path structure trends of multiple location nodes in each kitchen waste collection and transportation link according to the kitchen waste collection and transportation information to determine the traceability requirements for the kitchen waste collection and transportation information corresponding to each kitchen waste collection and transportation link includes:

[0017] According to the kitchen waste collection and transportation information, obtain the degree of path structure trend corresponding to each kitchen waste collection and transportation link;

[0018] According to the degree of path structure trend corresponding to each kitchen waste collection and transportation link, determine the traceability requirements for the kitchen waste collection and transportation information corresponding to each kitchen waste collection and transportation link.

[0019] In some embodiments, obtaining the degree of path structure tendency corresponding to each food waste collection and transportation link according to the food waste collection and transportation information includes:

[0020] Dividing the food waste collection and transportation information into multiple information parts according to a preset food waste collection and transportation area range;

[0021] For any one of the information parts, determining the timing correlation characteristics of each position node;

[0022] Taking the position nodes with the same category and the timing correlation characteristics greater than the preset timing correlation characteristic threshold in each food waste collection and transportation link as a path structure tendency change range, and determining the degree of path structure tendency corresponding to each food waste collection and transportation link within the path structure tendency change range.

[0023] In some embodiments, after dividing the food waste collection and transportation information into multiple information parts, it further includes:

[0024] Arranging the element items of each information in each information part in the arrival order of the position nodes of a single batch, where the element value of the element item includes the information corresponding to each food waste collection and transportation link, and the element value is used to determine the timing correlation characteristics of each position node.

[0025] In some embodiments, determining the timing correlation characteristics of each position node includes:

[0026] Obtaining the information change rate of all position nodes in each food waste collection and transportation link, and the number of all the position nodes;

[0027] Determining the timing correlation characteristics of each position node according to the information change rate of all the position nodes and the number of all the position nodes.

[0028] In some embodiments, determining the degree of path structure tendency corresponding to each food waste collection and transportation link within the path structure tendency change range includes:

[0029] Taking the position nodes within the path structure tendency change range as a path subsequence;

[0030] Determining the path subsequence difference corresponding to each food waste collection and transportation link according to the length of the path subsequence;

[0031] Determining the degree of path structure tendency corresponding to each food waste collection and transportation link according to the path subsequence difference corresponding to each food waste collection and transportation link and the timing correlation characteristics of each position node in each path subsequence.

[0032] In some embodiments, determining the traceability requirements for the food waste collection and transportation information corresponding to each food waste collection and transportation link includes:

[0033] Determining the degree of path structure tendency corresponding to the same type of collection and transportation operations at each position node according to the degree of path structure tendency corresponding to each food waste collection and transportation link;

[0034] Based on the degree of path structure tendency corresponding to the same type of collection and transportation operations at each position node and the path subsequences corresponding to the same type of collection and transportation operations within the range of path structure tendency changes, determining the traceability requirements for the food waste collection and transportation information corresponding to each position node in each food waste collection and transportation link.

[0035] In some embodiments, scheduling the food waste collection and transportation resources at the position nodes in the food waste collection and transportation link according to the traceability requirements for the food waste collection and transportation information corresponding to each food waste collection and transportation link includes:

[0036] Performing density clustering on the traceability requirements for the food waste collection and transportation information corresponding to each position node in each food waste collection and transportation link to obtain multiple clustering clusters;

[0037] Regarding the position nodes in the same clustering cluster as the scheduling and traceability scope at the same level to obtain a multi-level scheduling and traceability scope;

[0038] Based on the multi-level scheduling and traceability scope, scheduling the food waste collection and transportation resources at the position nodes in the food waste collection and transportation link.

[0039] In some embodiments, scheduling the food waste collection and transportation resources at the position nodes in the food waste collection and transportation link based on the multi-level scheduling and traceability scope includes:

[0040] For the highest-level scheduling and traceability scope in the multi-level scheduling and traceability scope, scheduling food waste transportation vehicles and food waste cleaning and transporting operators to the position nodes for anomaly investigation and handling.

[0041] The present invention has the following beneficial effects:

[0042] First, the food waste collection and transportation information corresponding to multiple food waste collection and transportation links is obtained; then, based on the food waste collection and transportation information, the path structure trend of multiple position nodes in each of the food waste collection and transportation links is analyzed to determine the food waste collection and transportation information tracing requirements corresponding to each of the food waste collection and transportation links; finally, based on the pre-installed smart property management platform, the food waste collection and transportation resources of the position nodes in the food waste collection and transportation links are scheduled and processed according to the food waste collection and transportation information tracing requirements corresponding to each of the food waste collection and transportation links. In this application, the information acquisition of multiple food waste collection and transportation links is covered to ensure that every step from waste generation to final treatment is recorded and monitored. Comprehensive information collection provides a solid foundation for subsequent analysis and tracing. By analyzing the path structure trends of multiple location nodes in each food waste collection and transportation link, not only the geographical location relationship (i.e., the spatial distribution of the path) is considered, but also the time dimension (such as collection and transportation time, residence time, etc.) is combined. This time-space combined analysis method can more accurately reflect the actual process of food waste collection and transportation. The path structure trend analysis can identify normal and abnormal collection and transportation operations. Based on the analysis results of the path structure trend, future collection and transportation needs can be predicted, and the optimal collection and transportation routes and schedules can be planned in advance, thereby improving the overall efficiency. At the same time, through long-term monitoring of the path structure trend, the collection and transportation process can be continuously optimized to reduce unnecessary waste of resources. According to the results of the path structure trend analysis, the food waste collection and transportation information traceability needs corresponding to each food waste collection and transportation link can be determined, and then the food waste collection and transportation resources can be accurately dispatched according to the actual situation to ensure that each link can be processed in a timely and effective manner. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0044] Figure 1 A schematic diagram of an implementation environment of a method for tracing kitchen waste collection and transportation information of a smart property management platform provided by an embodiment of the present invention;

[0045] Figure 2 A schematic diagram of a process for tracing kitchen waste collection and transportation information of a smart property management platform provided by an embodiment of the present invention;

[0046] Figure 3 A schematic diagram of location nodes in a food waste transportation link provided by an embodiment of the present invention;

[0047] Figure 4 The structural schematic diagram of a device for tracing the collection and transportation information of kitchen waste in a smart property management platform provided by an embodiment of the present invention;

[0048] Figure 5 The structural schematic diagram of a computer system suitable for an electronic device provided by an embodiment of the present invention. Detailed implementation manners

[0049] In order to further elaborate on the technical means and effects adopted by the present invention to achieve the intended invention purpose, the following, in combination with the accompanying drawings and preferred embodiments, details a method for tracing the collection and transportation information of kitchen waste in a smart property management platform proposed according to the present invention, including its specific implementation manners, structures, features, and effects. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0050] It should be noted that the terms "first", "second", etc. in the specification of this application and the above-mentioned drawings are used to distinguish similar objects and do not necessarily need to describe a specific order or sequence. It should be understood that such used data can be interchanged under appropriate circumstances so that the embodiments of this application described here can be implemented in an order other than those illustrated or described here. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, device, product, or equipment that includes a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products, or equipment.

[0051] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which the present invention belongs.

[0052] The following specifically describes the specific solution of a method for tracing the collection and transportation information of kitchen waste in a smart property management platform provided by the present invention with reference to the accompanying drawings.

[0053] Please refer to Figure 1 , Figure 1 which is the schematic diagram of the implementation environment of a method for tracing the collection and transportation information of kitchen waste in a smart property management platform provided by an embodiment of the present invention. As Figure 1As shown in the figure, the implementation environment includes the kitchen waste collection and transportation link 101, the intelligent property management terminal 102, and the server 103. The intelligent property management terminal 102 can be a terminal device installed with an intelligent property management platform, including but not limited to mobile devices with local computing capabilities, laptops, tablets, personal digital assistants, PADs, desktop computers, etc.; the intelligent property management platform can be implemented in the form of a target client, and the target client can be a video client, an instant messaging client, a browser client, etc. that support tracing kitchen waste collection and transportation information; the intelligent property management terminal 102 can communicate with the server 103 through a network, which can include but not limited to: wired networks, wireless networks, where the wired network includes: local area networks, metropolitan area networks, and wide area networks, and the wireless network includes: Bluetooth, WIFI, and other networks that implement wireless communication. The above intelligent property management terminal 102 can include but not limited to a human-computer interaction screen, a processor, and a memory. The above processor can be used to respond to human-computer interaction operations, execute corresponding operations, or generate corresponding instructions.

[0054] As an alternative, the intelligent property management terminal 102 can be a computer, through which the kitchen waste collection and transportation information corresponding to multiple kitchen waste collection and transportation links 101 can be obtained in real time; the server 103 can be a single server, a server cluster composed of multiple servers, or a cloud server. The above is only an example, and this embodiment does not make any limitations in this regard.

[0055] As an alternative, the following steps of the kitchen waste collection and transportation information traceability method of the intelligent property management platform can be executed on the intelligent property management terminal 102:

[0056] Obtain the kitchen waste collection and transportation information corresponding to multiple kitchen waste collection and transportation links;

[0057] According to the kitchen waste collection and transportation information, analyze the path structure trends of multiple position nodes in each kitchen waste collection and transportation link to determine the kitchen waste collection and transportation information traceability requirements corresponding to each kitchen waste collection and transportation link;

[0058] Based on the pre-installed intelligent property management platform, according to the kitchen waste collection and transportation information traceability requirements corresponding to each kitchen waste collection and transportation link, schedule the kitchen waste collection and transportation resources of the position nodes in the kitchen waste collection and transportation link.

[0059] The above method covers the information acquisition of multiple food waste collection and transportation links, ensuring that every step from waste generation to final treatment is recorded and monitored. Comprehensive information collection provides a solid foundation for subsequent analysis and tracing. By analyzing the path structure trends of multiple location nodes in each food waste collection and transportation link, not only the geographical location relationship (i.e., the spatial distribution of the path) is considered, but also the time dimension (such as collection and transportation time, residence time, etc.) is combined. This time-space combined analysis method can more accurately reflect the actual process of food waste collection and transportation. The path structure trend analysis can identify normal and abnormal collection and transportation operations. Based on the analysis results of the path structure trend, future collection and transportation needs can be predicted, and the optimal collection and transportation routes and schedules can be planned in advance, thereby improving overall efficiency. At the same time, through long-term monitoring of the path structure trend, the collection and transportation process can be continuously optimized to reduce unnecessary waste of resources. According to the results of the path structure trend analysis, the food waste collection and transportation information traceability needs corresponding to each food waste collection and transportation link can be determined, and then the food waste collection and transportation resources can be accurately dispatched according to the actual situation to ensure that each link can be processed in a timely and effective manner.

[0060] As an optional example, this embodiment does not limit the execution subject of the method for tracing food waste collection and transportation information of the above-mentioned smart property management platform. The method for tracing food waste collection and transportation information of the above-mentioned smart property management platform can be executed on the smart property management terminal 102. For example, when the smart property management terminal 102 is a computer, some or all steps of the method for tracing food waste collection and transportation information of the above-mentioned smart property management platform can be executed on the computer.

[0061] The above section introduces the contents of an exemplary implementation environment for applying the technical solution of the present application. Next, we will continue to introduce the method for tracing food waste collection and transportation information of the smart property management platform of the present application.

[0062] In order to solve the problem of how to efficiently trace the food waste collection and transportation information of the smart property management platform in the prior art, the embodiments of the present application respectively propose a method for tracing the food waste collection and transportation information of the smart property management platform, a device for tracing the food waste collection and transportation information of the smart property management platform, an electronic device, a computer-readable storage medium and a computer program product. These embodiments will be described in detail below.

[0063] See also Figure 2 , Figure 2 A schematic diagram of a method for tracing kitchen waste collection and transportation information of a smart property management platform provided by an embodiment of the present invention. The method can be applied to Figure 1It should be understood that the method can also be applied to other exemplary implementation environments and specifically executed by devices in other implementation environments, and this embodiment does not limit the implementation environment to which the method is applicable.

[0064] like Figure 2 As shown, in an exemplary embodiment, the method for tracing kitchen waste collection and transportation information of the smart property management platform includes at least steps S210 to S230, which are described in detail as follows:

[0065] In step S210, the food waste collection and transportation information corresponding to the multiple food waste collection and transportation links is obtained.

[0066] Among them, the food waste collection and transportation links are different stages or operation steps in the process of food waste collection and transportation, and each link is responsible for specific tasks. Common food waste collection and transportation links include: storage link, food waste is temporarily stored in trash cans or garbage stations at homes, restaurants, canteens and other places where it is generated; transportation link, dedicated food waste transportation vehicles transport the garbage from various storage points to transfer stations or treatment facilities; cleaning link, collection and transportation personnel load the garbage from the garbage cans or garbage stations onto the transportation vehicles and carry out necessary cleaning and maintenance; cleaning link, cleaning the food waste storage equipment (such as trash cans) to ensure that the sanitary conditions meet the standards.

[0067] Among them, the food waste collection and transportation information refers to various data and information related to the food waste collection and transportation process, including but not limited to: location information, the specific geographical location (longitude, latitude) of the food waste storage equipment; status information, the status of the garbage can (such as whether it is full, whether it is damaged, etc.); driving route, the driving path, stop points and driving time of the transport vehicle; operation information, the operation records of the collection and transportation personnel (such as scanning code records, taking photos to leave traces, etc.); cleaning information, the cleaning time and cleaning results of the storage equipment.

[0068] In step S220, based on the food waste collection and transportation information, the path structure trends of multiple location nodes in each of the food waste collection and transportation links are analyzed to determine the food waste collection and transportation information traceability requirements corresponding to each of the food waste collection and transportation links.

[0069] Among them, the location node is the specific geographical location point involved in the collection and transportation of food waste, usually referring to the location of the food waste storage equipment. Each location node has clear geographical coordinates and may be accompanied by other attribute information (such as garbage bin type, capacity, etc.). For example: the garbage drop point in the community is the location of the garbage bin near the residents' homes; the garbage station in the commercial area is the garbage collection point of restaurants, shopping malls and other places; the transfer station is the station for transferring food waste; the treatment facility is the place where food waste is finally treated, such as a composting plant, anaerobic fermentation plant, etc.

[0070] Among them, analyzing the path structure trends of multiple location nodes in each of the food waste collection and transportation links can be achieved by analyzing the spatial and temporal relationships of multiple location nodes in each link during the food waste collection and transportation process to identify stable patterns or trends.

[0071] Among them, when there is a need for traceability of food waste collection and transportation information, the content and scope of information to be traced in each food waste collection and transportation link can be determined based on the results of the path structure trend analysis. The traceability requirements include: responsibility traceability to determine the responsible person for each link to ensure standard operations and prevent human errors or improper behaviors; exception handling to quickly locate the problem node and take corresponding measures when an abnormal situation is detected; resource optimization to reasonably arrange collection and transportation vehicles and personnel according to traceability requirements to ensure the most effective use of resources.

[0072] In step S230, based on the pre-installed intelligent property management platform, the food waste collection and transportation resources at the location nodes in the food waste collection and transportation links are scheduled according to the food waste collection and transportation information traceability requirements corresponding to each of the food waste collection and transportation links.

[0073] Among them, when scheduling the food waste collection and transportation resources at the location nodes in the food waste collection and transportation links, the food waste collection and transportation resources (such as vehicles, personnel, etc.) can be dynamically adjusted and scheduled according to the food waste collection and transportation information traceability requirements to ensure that each link can complete tasks efficiently and in a timely manner. Specifically, it includes: resource allocation to reasonably arrange collection and transportation vehicles and personnel according to the garbage volume and collection and transportation requirements of each location node; exception response to quickly schedule spare vehicles or personnel for handling when an abnormal situation occurs to ensure that the problem is solved in a timely manner; optimized scheduling to continuously optimize the collection and transportation routes and schedules through analyzing historical data and real-time monitoring to improve the overall efficiency.

[0074] For example, the whole process of food waste collection and transportation is a complex and closely connected system, which specifically includes the property management of multiple communities. The dispatch of food waste collection and transportation can be efficiently coordinated through the smart property management platform. Sensors are installed at the food waste collection and transportation nodes in each community to collect real-time data, and these real-time data are analyzed to optimize the collection and transportation routes and the configuration of food waste collection and transportation vehicles, so as to achieve dynamic resource allocation. The smart property management platform can adjust the food waste collection and transportation vehicles and personnel according to actual needs, set the collection and transportation priorities of different areas, and ensure that the food waste is processed on time. Residents can feedback food waste disposal problems through the application, and the property can respond quickly and improve the cooperation of residents through the smart property management platform. In addition, the smart property management platform supports the classification management of food waste, generates compliance reports, and helps the property fulfill regulatory requirements. Through continuous technical maintenance and personnel training, the stable operation and effective use of the smart property management platform are ensured. The above method can improve the efficiency of food waste management and residents' satisfaction, which is of great significance to optimizing urban environmental management.

[0075] It can be seen from the above steps S210 to S230 that the scheme proposed in this embodiment covers the information acquisition of multiple food waste collection and transportation links, ensuring that each step from waste generation to final treatment is recorded and monitored, and comprehensive information collection provides a solid foundation for subsequent analysis and tracing; by analyzing the path structure trend of multiple location nodes in each food waste collection and transportation link, not only the geographical location relationship (i.e., the spatial distribution of the path) is considered, but also the time dimension (such as collection and transportation time, residence time, etc.) is combined. This time-space combined analysis method can more accurately reflect the actual situation of food waste collection and transportation. During the collection and transportation process, path structure trend analysis can identify normal and abnormal collection and transportation operations. Based on the analysis results of path structure trends, future collection and transportation needs can be predicted, and the optimal collection and transportation routes and schedules can be planned in advance, thereby improving overall efficiency. At the same time, through long-term monitoring of path structure trends, the collection and transportation process can be continuously optimized to reduce unnecessary waste of resources. According to the results of path structure trend analysis, the traceability needs of food waste collection and transportation information corresponding to each food waste collection and transportation link can be determined, and then the food waste collection and transportation resources can be accurately dispatched according to actual conditions to ensure that each link can be handled in a timely and effective manner.

[0076] In one embodiment of the present application, the multiple food waste collection and transportation links include a food waste storage link, a food waste transportation link, a food waste removal link, and a food waste storage equipment cleaning link. The obtaining of food waste collection and transportation information corresponding to the multiple food waste collection and transportation links includes:

[0077] Acquiring location information and status information of the food waste storage device in the food waste storage link through a pre-installed sensor;

[0078] Obtain the driving route, stop points, and collection time of the food waste transportation vehicle during the food waste transportation process through a pre-installed positioning device.

[0079] Obtain the corresponding waste removal operation information of the food waste removal operator during the food waste removal process through a pre-configured scanning device.

[0080] Obtain the cleaning operation information of the food waste storage equipment during the cleaning process of the food waste storage equipment.

[0081] Among them, during the food waste storage process, through sensors installed on food waste storage equipment (such as smart trash cans, garbage stations, etc.), the position information and status information of the equipment are collected in real time. Specifically include: The sensor can obtain the geographical location coordinates (longitude, latitude) of the trash can or garbage station to ensure accurate positioning of each storage point; Status information: The sensor can monitor the status of the trash can, such as whether it is full, whether there is damage, whether there is an odor, etc. This information can help determine whether immediate collection or maintenance is required. Common sensor types include: GPS (Global Positioning System) module, used to obtain geographical location information; Weight sensor, used to monitor the weight of the garbage in the trash can to determine whether it is full; Infrared sensor, used to detect the capacity of the trash can to determine whether it is close to overflowing; Temperature and humidity sensor, used to monitor the environmental conditions inside the trash can to prevent the garbage from spoiling and generating odors.

[0082] Among them, during the food waste transportation process, through positioning devices installed on the transportation vehicle (such as GPS, Beidou, etc.), the driving route, stop points, and collection time of the vehicle are recorded in real time. Specifically include: Driving route, recording the driving path of the vehicle from one storage point to another to ensure that the vehicle travels according to the predetermined route; Stop points, recording the specific location of each stop of the vehicle to ensure that the vehicle conducts collection operations at the designated storage points; Collection time, recording the arrival time and departure time of the vehicle at each storage point to ensure that the collection task is completed on time. Common positioning devices include: GPS / Beidou positioning module, used to track the driving route and position of the vehicle in real time; On-vehicle camera, used to take pictures of the collection site to ensure standard operations; RFID (Radio Frequency Identification) tag, used to identify the unique identifier of the storage point to ensure that the vehicle stops at the correct location.

[0083] Among them, in the process of collecting and transporting kitchen waste, the operation information of the collectors is recorded through scanning devices (such as QR code scanners, RFID readers, etc.) installed on handheld devices or vehicles. Specifically, it includes: QR code scanning records. When collecting waste each time, the collector uses the handheld device to scan the QR code or RFID tag on the trash can to record the source information of the waste; operation information, recording the operation time and content of the collector (such as loading, unloading, etc.) to ensure that every operation is traceable; taking pictures for record. The collector can take pictures through the handheld device to record the waste status and the situation at the collection site to ensure standard operations. Commonly used scanning devices include: QR code scanners, used to scan the QR codes on the trash cans to record the source information of the waste; RFID readers, used to read the RFID tags on the trash cans to ensure that each trash can can be accurately identified; handheld terminals, handheld devices equipped with cameras and scanning functions, which are convenient for collectors to record operation information.

[0084] Among them, in the process of cleaning kitchen waste storage equipment, the specific information of the cleaning operation is recorded through sensors installed on the cleaning equipment or manual input. Specifically, it includes: cleaning time, recording the start time and end time of each cleaning to ensure that the cleaning work is completed on time; cleaning result, recording the status of the equipment after cleaning, such as whether it is clean, whether there is damage, etc., to ensure that the equipment meets the hygiene standards; operator information, recording the information of the operator responsible for cleaning to ensure traceability of responsibilities. Commonly used cleaning equipment includes: sensors, used to monitor parameters such as water temperature, water pressure, and detergent dosage during the cleaning process to ensure cleaning quality; manual input, manually inputting the specific information of the cleaning operation through a handheld terminal or computer to ensure that every operation is traceable; cameras, used to take pictures of the equipment status after cleaning to ensure that the cleaning effect meets the standards.

[0085] In this embodiment, through sensors and positioning devices, the status of the food waste storage equipment and the driving conditions of the transport vehicles can be grasped in real time, the collection and transportation tasks can be reasonably arranged, and unnecessary waiting time and empty driving rate can be reduced. When the amount of waste at a certain storage point suddenly increases, the collection and transportation route can be dynamically adjusted, and the collection and transportation tasks of this storage point can be prioritized to ensure the timely removal of waste. Through sensors and positioning devices, the whole process of food waste collection and transportation can be monitored in real time. When an abnormal situation is detected, the problem node can be quickly located and corresponding treatment measures can be taken. By detailed recording of the removal operation and cleaning operation, the responsible person for each link can be identified, the operation can be ensured to be standardized, and human errors or improper behaviors can be prevented. Through sensors, positioning devices and scanning devices, a large amount of historical data has been accumulated, and more accurate analysis and prediction can be carried out. For example, the amount of waste generated at a certain storage point can be predicted based on historical data, and the collection and transportation tasks can be arranged in advance. Through long-term monitoring and analysis of historical data, the food waste collection and transportation process can be continuously optimized, and the overall management level can be improved. For example, if it is found that some storage points often overflow, the number of trash cans in this area can be considered to be increased or the collection and transportation time can be adjusted.

[0086] In an embodiment of the present application, the analyzing the path structure tendency of multiple position nodes in each of the food waste collection and transportation links according to the food waste collection and transportation information to determine the food waste collection and transportation information traceability requirements corresponding to each of the food waste collection and transportation links includes:

[0087] Obtaining the degree of path structure tendency corresponding to each of the food waste collection and transportation links according to the food waste collection and transportation information;

[0088] Determining the food waste collection and transportation information traceability requirements corresponding to each of the food waste collection and transportation links according to the degree of path structure tendency corresponding to each of the food waste collection and transportation links.

[0089] Among them, in the process of the circulation of food waste collection and transportation information, since the change characteristics of food waste collection and transportation information are mainly restricted by the food waste removal, the collection and transportation routes of food waste collection and transportation vehicles, and the fixation of the food waste storage locations in multiple communities, it will show obvious path structure tendency in data. The path structure tendency will affect the traceability requirements in the property management process. Therefore, the information abnormality in the collection and transportation process will affect the position location analysis of the path structure tendency of the node, and adjustment should be made.

[0090] Among them, the degree of path structure tendency refers to the stability and regularity shown by the spatial and temporal relationships of multiple position nodes in each link of the kitchen waste collection and transportation process. Specifically, the degree of path structure tendency reflects the following characteristics: node distribution, the geographical distribution of each position node, including the distance between them, relative positions, etc.; topological relationship, the connection method and sequence between nodes, that is, the driving path of the vehicle from one node to another; temporal correlation, the time series relationship between nodes, such as the time interval between each collection and transportation, residence time, etc.; anomaly detection, the degree of path structure tendency can also be used to identify behaviors that deviate from the normal mode, such as the vehicle deviating from the predetermined route, or the abnormal increase in the amount of waste at a certain node.

[0091] In this embodiment, through the analysis of the degree of path structure tendency, the collection and transportation route can be better planned, the empty driving rate of the vehicle can be reduced, and fuel consumption and carbon emissions can be lowered. For example, according to the path similarity, the collection and transportation route can be optimized to ensure that the vehicle travels along the shortest path. When the amount of waste at a certain storage point suddenly increases, the collection and transportation route can be dynamically adjusted according to the degree of path structure tendency, and the collection and transportation task of this storage point can be preferentially arranged to ensure that the waste will not be stranded. Through the analysis of the degree of path structure tendency, the whole process of kitchen waste collection and transportation can be monitored in real time. When an abnormal situation is detected, the problem node can be quickly located and corresponding treatment measures can be taken. For example, if it is found that a vehicle deviates from the predetermined route, or the amount of waste in a certain trash can increases abnormally, an alarm will be immediately issued to notify the relevant personnel for inspection. Through the analysis of the degree of path structure tendency, the responsible person for each link can be clarified to ensure standardized operation and prevent human errors or improper behaviors. For example, by scanning the code for recording and taking pictures for traceability, the person responsible for a certain cleaning operation can be quickly found. Through the analysis of the degree of path structure tendency, a large amount of historical data has been accumulated, and more accurate prediction and optimization can be carried out. For example, the amount of waste generated at a certain storage point can be predicted according to historical data, and the collection and transportation task can be arranged in advance. Through the long-term monitoring and analysis of the degree of path structure tendency, the kitchen waste collection and transportation process can be continuously optimized, and the overall management level can be improved. For example, if it is found that some storage points often overflow, the number of trash cans in this area can be considered to be increased or the collection and transportation time can be adjusted.

[0092] In an embodiment of the present application, obtaining the degree of path structure tendency corresponding to each of the kitchen waste collection and transportation links according to the kitchen waste collection and transportation information includes:

[0093] Dividing the kitchen waste collection and transportation information into multiple information parts according to a preset kitchen waste collection and transportation area range;

[0094] For any one of the information parts, determining the temporal correlation characteristics of each position node;

[0095] Regarding each position node in the same category during the collection and transportation process of the kitchen waste, where the time series correlation feature is greater than the preset time series correlation feature threshold, it is regarded as a range of path structure trend changes, and the degree of path structure trend corresponding to each collection and transportation link of the kitchen waste within the range of path structure trend changes is determined.

[0096] Among them, the preset collection and transportation area range of kitchen waste refers to the collection and transportation service area of kitchen waste delimited in advance according to geographical and management requirements. Each area usually includes multiple communities or specific geographical ranges, which are used for centralized management and analysis of the collection and transportation information of kitchen waste. By dividing the area, the collection and transportation tasks can be better organized and optimized to ensure the efficient progress of the collection and transportation work in each area. The preset collection and transportation area range of kitchen waste can be determined in the following ways: Geographic Information System (GIS), using GIS technology, different collection and transportation areas are divided according to geographical boundaries such as communities, streets, and administrative divisions; management requirements, according to the operation strategy of the property management company, the entire service area is divided into several sub-areas, and each sub-area is responsible for by a specific collection and transportation team; historical data, based on historical collection and transportation data, identify the areas with a large amount of waste generation and use them as key collection and transportation areas.

[0097] Among them, multiple information parts refer to dividing the entire collection and transportation information of kitchen waste according to the preset collection and transportation area range of kitchen waste to form multiple independent information units. Each information part contains the relevant data of all collection and transportation links of kitchen waste within this area, such as the location information of storage equipment, the driving routes of transport vehicles, the operation records of cleaning and transportation operators, etc. The information parts can be divided in the following ways: divided by area, according to the preset collection and transportation area range of kitchen waste, the entire information set is divided into multiple area information parts. For example, a large community can be divided into multiple information parts such as the east area, west area, south area, and north area; divided by time, according to the collection and transportation time period, the information is divided into different information parts. For example, it can be divided by time periods such as days, weeks, and months to facilitate the analysis of collection and transportation patterns in different time periods; divided by collection and transportation type, according to the types of kitchen waste (such as household kitchen waste, commercial kitchen waste, etc.), the information is divided into different information parts to facilitate the targeted analysis of the collection and transportation conditions of different types of waste.

[0098] Among them, the temporal correlation feature of each location node refers to the time series relationship between various location nodes during the collection and transportation of food waste. Specifically, the temporal correlation feature reflects the temporal regularities such as the collection and transportation order, residence time, and interval time between nodes. By analyzing these features, common collection and transportation patterns and abnormal situations can be identified. The extraction and analysis of the temporal correlation feature can be carried out in the following ways: Using time series analysis methods to identify the collection and transportation order and time interval between each location node. For example, the timestamps of each collection and transportation can be analyzed to calculate the average residence time and interval time between adjacent nodes; Using statistical methods (such as Pearson correlation coefficient, mutual information, etc.) to measure the time series correlation between different nodes. For example, it can be calculated whether the collection and transportation times of two nodes are strongly correlated to determine whether they belong to the same collection and transportation path; By comparing the normal temporal correlation features, behaviors deviating from the conventional pattern can be identified. For example, if the collection and transportation time of a certain node suddenly prolongs, or the driving route of a certain vehicle changes, an alarm will be issued to indicate that there may be an abnormal situation.

[0099] Among them, being of the same category means that during the collection and transportation of food waste, the food waste collection and transportation links or location nodes with similar features. These links or nodes may belong to the same type of collection and transportation task, or have similar geographical locations, collection and transportation frequencies, etc. By grouping the nodes of the same category, common collection and transportation patterns and abnormal situations can be better identified.

[0100] Among them, the path structure trend change range refers to a specific area composed of location nodes with similar temporal correlation features and belonging to the same category during the collection and transportation of food waste. These nodes show a consistent collection and transportation pattern in space and time, forming a stable path structure. Identifying the path structure trend change range helps to discover common collection and transportation paths and abnormal situations. The determination of the path structure trend change range can be carried out in the following ways: According to the preset threshold of the temporal correlation feature, filter out the nodes whose temporal correlation feature is greater than this threshold. For example, a minimum correlation coefficient threshold can be set, and only when the collection and transportation time correlation between two nodes exceeds this threshold will they be classified into the same path structure trend change range; As new data is continuously added, the path structure trend change range can be dynamically adjusted. For example, when the collection and transportation pattern of a certain node changes, its belonging path structure trend change range can be re-evaluated and corresponding adjustments can be made; Intuitively display the node distribution and collection and transportation paths within the path structure trend change range in the form of a map or chart. For example, the nodes within each path structure trend change range can be marked on the map, and different collection and transportation paths can be represented by different colors.

[0101] Exemplarily, since the collected kitchen waste collection and transportation information mainly consists of time-series data of multiple links in the kitchen waste collection and transportation process, that is, the placement positions of kitchen waste bins in different communities correspond to an information set of multiple links such as kitchen waste collection vehicles, sanitation cleaning, and the placement of kitchen waste collection equipment. In fact, when there is an abnormality in the kitchen waste collection and transportation and there is a need for information traceability, it is necessary to locate the path structure trend of the node. The traceability requirements at different links in the collection and transportation process are closely related to the position in the collection and transportation process, that is, the time-series correlation relationship in the records at different positions in the kitchen waste collection and transportation process. The determination of the path structure trend of the node is realized by screening based on the change difference of the kitchen waste collection and transportation information on the node. Therefore, it is necessary to determine the traceability requirements of the node according to the change characteristics of the correlation relationship of the kitchen waste collection and transportation information. The change characteristics of the correlation relationship of the kitchen waste collection and transportation information are mainly manifested as the path structure trend of information change, that is, affected by the placement position of the kitchen waste bin and the kitchen waste collection route in the community, there will be a time-series correlation relationship before and after in the collection information records of the kitchen waste transportation vehicle between different positions.

[0102] Exemplarily, refer to Figure 3 , Figure 3 , which is a schematic diagram of the position nodes in the kitchen waste transportation link provided by an embodiment of the present invention. As Figure 3 can be seen, the kitchen waste transportation vehicle often enters the community from Gate 1 of Community A to carry out the kitchen waste collection work. For all the placement positions of the kitchen waste bins in Community A (i.e., the circles in Figure 3 ), at least one shortest kitchen waste collection route will be planned with Gate 1 at the starting point of the kitchen waste transportation vehicle. For any placement position of the kitchen waste bin, there will be a time-series correlation relationship of sequential cleaning in the kitchen waste transportation vehicle cleaning records with the nearby other placement positions of the kitchen waste bins, which is manifested as a path structure trend.

[0103] In this embodiment, through the analysis of the range of change in the path structure, the collection and transportation routes can be better planned, the empty driving rate of vehicles can be reduced, and fuel consumption and carbon emissions can be lowered. When the amount of garbage at a certain storage point suddenly increases, the collection and transportation routes can be dynamically adjusted according to the range of change in the path structure, and the collection and transportation tasks of this storage point can be preferentially arranged to ensure that the garbage will not be detained. Through the analysis of the range of change in the path structure, the whole process of kitchen waste collection and transportation can be monitored in real time. When an abnormal situation is detected, the problem node can be quickly located and corresponding treatment measures can be taken. For example, if it is found that a vehicle deviates from the predetermined route or the amount of garbage in a certain trash can increases abnormally, an alarm will be immediately issued to notify the relevant personnel to conduct an inspection. Through the analysis of the range of change in the path structure, the responsible person for each link can be clarified to ensure standard operation and prevent human errors or improper behaviors. For example, the personnel responsible for a certain cleaning operation can be quickly found through code scanning records and photo evidence. Through the analysis of the range of change in the path structure, a large amount of historical data has been accumulated, and more accurate prediction and optimization can be carried out. For example, the amount of garbage generated at a certain storage point can be predicted based on historical data, and the collection and transportation tasks can be arranged in advance. Through the long-term monitoring and analysis of the range of change in the path structure, the kitchen waste collection and transportation process can be continuously optimized, and the overall management level can be improved. For example, if it is found that some storage points often overflow, the number of trash cans in this area can be considered increased or the collection and transportation time can be adjusted.

[0104] In one embodiment of the present application, after dividing the kitchen waste collection and transportation information into multiple information parts, the following is further included:

[0105] Arrange the element items of each information in each of the information parts in the order of arrival of the position nodes of a single batch, where the element values of the element items include the information corresponding to each kitchen waste collection and transportation link, and the element values are used to determine the timing correlation characteristics of each of the position nodes.

[0106] Among them, an element item refers to each specific data item in the kitchen waste collection and transportation information, and each element item represents a specific attribute or feature. These element items contain various information related to the kitchen waste collection and transportation process, such as location, status, time, operating personnel, etc. By analyzing these element items, the specific situation of each link can be comprehensively understood. Common element items include: location information: the geographical location (longitude, latitude) of the kitchen waste storage equipment; status information: the status of the trash can (such as whether it is full, whether there is damage, etc.); driving route: the driving path, stopping points and driving time of the transport vehicle; operation information: the operation records of the cleaning personnel (such as code scanning records, photo evidence, etc.); cleaning information: the cleaning time and cleaning result of the storage equipment; garbage type: the specific type of kitchen waste (such as household kitchen waste, commercial kitchen waste, etc.); collection and transportation frequency: the collection and transportation frequency of a certain node (such as once a day, twice a week, etc.).

[0107] Among them, the arrival order of the location nodes of a single batch refers to the time order in which the transport vehicle arrives at each location node in sequence according to the predetermined route during a complete collection and transportation process of food waste. By recording the arrival order of each collection and transportation, the collection and transportation time and order of each node can be accurately grasped to ensure the timely completion of the collection and transportation task.

[0108] Among them, the element value refers to the specific numerical value or state of each element item, which is used to describe the specific situation in the food waste collection and transportation process. By analyzing the element values, the temporal correlation characteristics of each location node can be determined, and common collection and transportation patterns and abnormal situations can be identified. Common element values include: geographical location coordinates: specific longitude and latitude values, which are used to identify the precise location of each location node; garbage weight: the weight of the garbage in the trash can, which is used to judge whether it is full; travel time: the travel time of the vehicle from one node to another, which is used to optimize the route planning; stay time: the stay time of the vehicle at each node, which is used to evaluate the collection and transportation efficiency; operator information: information such as the name and job number of the operator responsible for the cleaning, which is used for responsibility tracing; cleaning result: the cleaning result of the storage equipment (such as whether it is clean, whether there is damage, etc.), which is used to ensure the hygiene standard.

[0109] Exemplarily, it is selected to divide the food waste collection and transportation information into multiple parts according to different regional scopes of the food waste collection and transportation. For the data of the food waste collection and transportation process of a single batch, the element items of each data are arranged according to the arrival order of the location nodes of the food waste collection and transportation of a single batch, and the element value is the information related to the detection of food waste collection and transportation in each category. Then, the data information contained in each element value is mainly the specific information of different collection and transportation links. For example, data such as the collection and transportation information of the food waste transport vehicle and the cleaning process information of the cleaning personnel can be regarded as multi-type data of the nodes in different collection and transportation links, which are used to analyze the temporal correlation characteristics of the subsequent path structure trend.

[0110] In this embodiment, by arranging the element items according to the arrival order of the location nodes of a single batch, the collection and transportation route can be better planned, the empty driving rate of the vehicle can be reduced, and the fuel consumption and carbon emissions can be reduced. For example, according to the arrival order, the collection and transportation route can be optimized to ensure that the vehicle travels along the shortest path. When the garbage volume at a certain storage point suddenly increases, the collection and transportation route can be dynamically adjusted according to the arrival order, and the collection and transportation task of this storage point can be preferentially arranged to ensure that the garbage will not be detained. By arranging the element items according to the arrival order of the location nodes of a single batch, the whole process of kitchen waste collection and transportation can be monitored in real time. When an abnormal situation is detected, the problem node can be quickly located and corresponding treatment measures can be taken. For example, if it is found that a vehicle deviates from the predetermined route or the garbage volume of a certain trash can increases abnormally, an alarm will be immediately issued to notify the relevant personnel to conduct an inspection. By recording the arrival order, the responsible person for each link can be clarified to ensure standard operation and prevent human errors or improper behaviors. For example, through barcode scanning records and photo evidence, the personnel responsible for a certain cleaning operation can be quickly found.

[0111] In an embodiment of the present application, the determining the temporal correlation characteristics of each location node includes:

[0112] Obtaining the information change rate of all location nodes in each kitchen waste collection and transportation link, and the number of all location nodes;

[0113] Determining the temporal correlation characteristics of each location node according to the information change rate of all location nodes and the number of all location nodes.

[0114] Among them, the information change rate refers to the change rate of the relevant information (such as garbage volume, vehicle arrival time, residence time, etc.) of each location node over time during the kitchen waste collection and transportation process. The information change rate reflects the dynamic change situation of each location node in different time periods, and helps to identify common collection and transportation patterns and abnormal situations.

[0115] Among them, the temporal correlation characteristic refers to the time series relationship between each location node, which reflects their relative order and time interval during the collection and transportation process. By comprehensively analyzing the information change rate and the number of location nodes, the temporal correlation characteristics of each location node can be determined, and common collection and transportation patterns and abnormal situations can be identified.

[0116] Exemplarily, the change in the amount of garbage in each trash can is monitored in real time through a weight sensor installed on the trash can. For example, it is recorded that the weight of the trash can before a certain garbage collection is 50 kg, and the weight after the collection is 10 kg. It is calculated that the amount of garbage has decreased by 40 kg. By further analyzing the data of multiple garbage collections, the average change rate of the amount of garbage in each trash can is calculated. Through the GPS positioning device on the transport vehicle, the time of arrival at a certain location node is recorded each time. For example, it is recorded that the times of a certain vehicle arriving at three nodes A, B, and C in a week are 8:00, 8:15, and 8:30 respectively. The change rate of the arrival time each time is calculated. If the arrival time of the vehicle at node A is delayed to 8:10 one day, the change rate of the arrival time is calculated as +10 minutes. Through sensors or manual input, the start time and end time of each garbage collection operation are recorded. For example, it is recorded that the residence time of a certain garbage collection operation at node A is 15 minutes, and the residence time of the next garbage collection operation is 20 minutes. It is calculated that the residence time has increased by 5 minutes. By further analyzing the data of multiple garbage collections, the average change rate of the residence time at each node is calculated. Through barcode scanning records or manual input, the operation frequency of each location node is counted. For example, it is recorded that the number of garbage collection times at node A in a certain week is 7 times, and the number of garbage collection times in the next week is 8 times. It is calculated that the operation frequency has increased by 1 time / week. By further analyzing the data of multiple weeks, the change rate of the operation frequency at each node is calculated. The number of all location nodes participating in the collection and transportation is counted to ensure the integrity and representativeness of the data. For example, it is recorded that in a certain collection and transportation task, there are a total of 10 location nodes (A, B, C, D, E, F, G, H, I, J). By further analyzing the data of multiple collection and transportation operations, it is ensured that each collection and transportation task covers all necessary location nodes. The time series correlation between different location nodes is measured. For example, it is found that the arrival times of nodes A and B are strongly correlated, indicating that they may belong to the same collection and transportation route. By further analyzing the arrival times of other nodes, more relevant nodes are identified to form a stable collection and transportation pattern. Using a clustering algorithm, nodes with similar information change rates are grouped into one category. For example, according to characteristics such as the change rate of the amount of garbage, the change rate of the arrival time, and the change rate of the residence time, certain nodes are clustered together to form a stable collection and transportation route. By further analyzing the data of multiple collection and transportation operations, common collection and transportation patterns and abnormal situations are identified. By comparing the normal time series correlation features, behaviors deviating from the conventional pattern are identified. For example, if the arrival time of a certain node is suddenly delayed, or the driving route of a certain vehicle changes, an alarm is issued to indicate that there may be an abnormal situation.

[0117] Exemplarily, within their respective links, the information change rates of the nodes are extracted. Taking the filling rate of the kitchen waste trash cans in the kitchen waste collection and transportation as an example, the filling rates of the kitchen waste trash cans of all nodes within this collection and transportation process link are extracted. Then, the th node's th type of information change rate It is represented by the ratio of the difference between the position node data and the average data. By obtaining the information change rate of the corresponding nodes in all links, the influence of the corresponding node information change rate on the path structure trend should be realized based on the sequential correlation characteristics before and after. That is, only when adjacent nodes have sequential performances in the kitchen waste collection and transportation link for many times, can they have the structural trend characteristics. Then, the correlation characteristics of each node in this link are analyzed. The representation method of the sequential correlation characteristics can be:

[0118]

[0119] Among them, represents the sequential correlation characteristic of the th position node, represents the average value of the information change rates of all types of the th position node, represents the average value of the information change rates of all types of the next node of the node in the th data record, represents the number of all position nodes.

[0120] Among them, represents the sequential performance of the th position node and its adjacent node in the kitchen waste collection and transportation link. When this value is larger, it means that the sequential correlation characteristic is larger and has the structural trend characteristic.

[0121] In this embodiment, through the analysis of the information change rate and the sequential correlation characteristics, the collection and transportation route can be better planned, the empty driving rate of the vehicle can be reduced, and the fuel consumption and carbon emissions can be reduced. For example, according to the garbage volume change rate, the collection and transportation frequency can be optimized to ensure that the garbage can be effectively cleared each time; or according to the arrival time change rate, the collection and transportation route can be adjusted to ensure that the vehicle travels along the shortest path. When the garbage volume at a certain storage point suddenly increases, the collection and transportation frequency can be dynamically adjusted according to the information change rate, and the collection and transportation task of this storage point can be preferentially arranged to ensure that the garbage will not be detained. Through the analysis of the information change rate and the sequential correlation characteristics, the whole process of kitchen waste collection and transportation can be monitored in real time. When an abnormal situation is detected, the problem node can be quickly located and corresponding treatment measures can be taken. For example, if it is found that the arrival time of a certain vehicle is suddenly delayed, or the garbage volume of a certain trash can is abnormally increased, an alarm will be immediately issued to notify the relevant personnel to conduct an inspection. Through the analysis of the information change rate and the sequential correlation characteristics, the responsible person of each link can be clarified to ensure the operation specification and prevent human errors or improper behaviors. For example, through scanning the code record and taking pictures for record, the person responsible for a certain cleaning operation can be quickly found.

[0122] In an embodiment of the present application, determining the degree of path structure tendency corresponding to each of the food waste collection and transportation links within the range of path structure tendency change includes:

[0123] Regarding the position nodes within the range of path structure tendency change as path subsequences;

[0124] Determining the differences in path subsequences corresponding to each of the food waste collection and transportation links according to the length of the path subsequences;

[0125] Determining the degree of path structure tendency corresponding to each of the food waste collection and transportation links according to the differences in path subsequences corresponding to each of the food waste collection and transportation links and the temporal correlation characteristics of each position node in each of the path subsequences.

[0126] Among them, a path subsequence refers to a sequence formed by arranging multiple position nodes within the same range of path structure tendency change in the order of arrival during the food waste collection and transportation process. Each path subsequence represents a part of a complete collection and transportation task, reflecting the driving path and time sequence of the vehicle from one node to another. According to a preset temporal correlation characteristic threshold, position nodes with temporal correlation characteristics greater than this threshold are screened out, and these nodes are classified within the same range of path structure tendency change. According to the time sequence of the vehicle arriving at each node in each collection and transportation task, these nodes are arranged into an ordered path subsequence. For example, if in a certain collection and transportation task, the vehicle arrives at four nodes A, B, C, and D in sequence, then these four nodes will form a path subsequence. For a larger collection and transportation area, the entire collection and transportation process can be divided into multiple path subsequences, and each path subsequence corresponds to a specific collection and transportation path or time period. This can more meticulously analyze the degree of path structure tendency of each path subsequence.

[0127] Among them, the length of a path subsequence refers to the number of position nodes included in the path subsequence. The length of the path subsequence reflects the complexity and coverage of this path subsequence, and is usually related to the scale and difficulty of the collection and transportation task.

[0128] Among them, the difference in path subsequences refers to the similarity and difference between different path subsequences. By comparing the length, node distribution, temporal correlation characteristics, etc. of the path subsequences, the differences between each path subsequence can be identified, which helps to optimize the collection and transportation route and resource scheduling.

[0129] Exemplarily, a certain intelligent property management platform manages a large community, which has multiple residential areas, and each residential area has multiple food waste disposal points. According to the preset time-series correlation feature threshold, position nodes with time-series correlation features greater than the threshold are screened out, and these nodes are grouped within the same range of path structure trend changes. For example, it is found that the collection and transportation times of nodes A, B, and C have strong correlations, so they are grouped within the same range of path structure trend changes. According to the time sequence of the vehicle arriving at each node in each collection and transportation task, these nodes are arranged into an ordered path subsequence. For example, in a certain collection and transportation task, the vehicle arrives at nodes A, B, and C in sequence, so these three nodes form a path subsequence. For a larger collection and transportation area, the entire collection and transportation process can be divided into multiple path subsequences. For example, the collection and transportation task in the eastern area can be divided into two path subsequences: one is the path subsequence of nodes A, B, and C, and the other is the path subsequence of nodes D, E, and F. The number of position nodes included in each path subsequence is counted as the length of the path subsequence. For example, the length of the path subsequence of nodes A, B, and C is 3, and the length of the path subsequence of nodes D, E, and F is also 3. As new data is continuously added, the length of the path subsequence can be dynamically adjusted. For example, if the collection and transportation mode of a certain node changes, its belonging path subsequence can be re-evaluated and corresponding adjustments can be made. The length of the path subsequence can help optimize the collection and transportation route. For example, if the length of a certain path subsequence is too long, it can be considered to increase the collection and transportation vehicles or adjust the collection and transportation frequency to improve efficiency.

[0130] Exemplarily, for the traceability requirement of the food waste collection and transportation process, the more obvious the time-series correlation feature is, the more obvious the impact of the information anomaly situation at this node on the nearby nodes is. Therefore, it is necessary to further analyze from the impact of the specific path structure. Since there are multiple path information with time-series correlations of nodes in the same type of collection and transportation operation process in the same link, it is regarded as a path subsequence. The structure trend feature is mainly related to the manifestation of the time-series correlation features of the nodes within the path subsequence. The smaller the difference between the length of each path subsequence and the average length of all path subsequences, the higher the degree of path structure trend of the abnormal information represented by its path subsequence. The representation method of the degree of path structure trend can be:

[0131]

[0132] Among them, represents the degree of path structure trend corresponding to the th food waste collection and transportation link; represents the average length of all path subsequences of the same type of collection and transportation operation in the th food waste collection and transportation link; Indicates the length of the path subsequence within the range of the tendency change of the path structure; Indicates the average value of the temporal correlation features of all nodes in the th food waste collection and transportation link;

[0133] Wherein, Indicates the difference between the length of the path subsequence within the range of the tendency change of the path structure and the average length of all path subsequences. The smaller the difference, the greater the degree of path structure tendency.

[0134] In this embodiment, by taking the position nodes within the range of the tendency change of the path structure as path subsequences and analyzing according to the length and difference of the path subsequences, the collection and transportation route can be better planned, the empty driving rate of the vehicle can be reduced, and the fuel consumption and carbon emissions can be reduced. For example, according to the length of the path subsequence, the collection and transportation route can be optimized to ensure that the vehicle travels along the shortest path; or according to the difference of the path subsequence, the collection and transportation frequency can be adjusted to ensure that the garbage can be effectively cleared each time. When the garbage volume at a certain storage point suddenly increases, the collection and transportation route can be dynamically adjusted according to the length and difference of the path subsequence, and the collection and transportation task of this storage point can be preferentially arranged to ensure that the garbage will not stay. Through the analysis of the length and difference of the path subsequence, the whole process of food waste collection and transportation can be monitored in real time. When an abnormal situation is detected, the problem node can be quickly located and corresponding treatment measures can be taken. For example, if it is found that the length of a certain path subsequence suddenly increases, or the collection and transportation time of a certain node has changed significantly, an alarm will be immediately issued to notify the relevant personnel for inspection. Through the analysis of the temporal correlation features of the path subsequence, the responsible person for each link can be clarified to ensure standard operation and prevent human errors or improper behaviors. For example, through scanning the code record and taking pictures for traceability, the personnel responsible for a certain cleaning operation can be quickly found.

[0135] In an embodiment of the present application, the determining the food waste collection and transportation information traceability requirements corresponding to each of the food waste collection and transportation links according to the degree of path structure tendency corresponding to each of the food waste collection and transportation links includes:

[0136] Determining the degree of path structure tendency corresponding to the same category of collection and transportation operations on each of the position nodes according to the degree of path structure tendency corresponding to each of the food waste collection and transportation links;

[0137] Based on the degree of path structure tendency corresponding to the same category of collection and transportation operations on each of the position nodes and the path subsequences corresponding to the same category of collection and transportation operations within the range of the tendency change of the path structure, determining the food waste collection and transportation information traceability requirements corresponding to each of the position nodes in each of the food waste collection and transportation links.

[0138] Among them, according to the path structure trend degree corresponding to each of the food waste collection and transportation links, the path structure trend degree corresponding to the same type of collection and transportation operations at each of the location nodes is determined. The purpose is to further refine the analysis on the basis of the calculated path structure trend degree of each food waste collection and transportation link, and determine the path structure trend degree of the same type of collection and transportation operations (such as household food waste, commercial food waste, etc.) at each location node. Through this refined analysis, the characteristics and laws of different types of collection and transportation operations can be more accurately identified, thereby providing more accurate support for subsequent traceability needs.

[0139] Among them, based on the degree of path structure tendency corresponding to the same category of collection and transportation operations at each of the said location nodes, and the path subsequence corresponding to the same category of collection and transportation operations within the range of the said path structure tendency change, the traceability requirements of the food waste collection and transportation information corresponding to each of the said location nodes in each of the said food waste collection and transportation links are determined. Through the comprehensive analysis of these information, the key information that needs to be traced can be more accurately identified to ensure that the responsibilities of each link are clear and the operation is standardized. Since the changing characteristics of food waste collection and transportation information are mainly limited by the fixed influence of the collection and transportation routes of food waste collection and transportation vehicles and the storage locations of food waste in multiple communities, it will show obvious path structure trends in the data. Then the path structure trend will affect the scope of traceability requirements in the property management process, that is, the allocation problem of different weights on the path, which is specifically manifested in the path structure trend in the obtained food waste collection and transportation information tends to change abnormally in terms of location, time, path, etc. When a node detects an abnormality, it is actually an analysis of multiple types of common concept relationships, that is, an analysis of multi-link correlation relationships. Therefore The path structure trend should be that there is a stronger correlation between one or more types of location, time, that is, the path structure trend is more obvious, then it will show stronger specificity for traceability needs, that is, the analysis of the path subsequence of the above-mentioned node structure trend is more of a stable expression of the difference characteristics at the data level, then for the actual management work on the smart property management platform, it should be more about the allocation of food waste collection and transportation resources. The main implementation process is to reasonably allocate surplus collection and transportation resources, that is, to achieve the best adjustment without affecting the food waste collection and transportation work in the communities in the entire area as much as possible.

[0140] For example, The demand for food waste collection and transportation information traceability corresponding to each location node can be expressed as:

[0141]

[0142] in, Indicates The demand for food waste collection and transportation information traceability corresponding to each location node; Indicates The degree of path structure tendency corresponding to the same category of collection and transportation operations at the th position node within a food waste collection and transportation link; Indicates the length of the path subsequence corresponding to the same category of collection and transportation operations at the th position node within the range of path structure tendency change; Indicates positive correlation normalization; Indicates the total number of food waste collection and transportation links.

[0143] Among them, , indicating the obvious situation of the path structure tendency at the position node. The larger this value is, the more obvious the path structure tendency is, and the greater the demand for tracing the source of food waste collection and transportation information corresponding to this position node.

[0144] In this embodiment, by analyzing the degree of path structure tendency of different categories of collection and transportation operations, the collection and transportation routes can be better planned, the empty driving rate of vehicles can be reduced, and fuel consumption and carbon emissions can be reduced. For example, according to the collection and transportation path characteristics of household food waste and commercial food waste, the collection and transportation routes can be optimized to ensure that the vehicles drive along the shortest path; or according to the collection and transportation frequencies of different categories, the collection and transportation schedule can be adjusted to ensure that each collection can effectively clean up the garbage. When the garbage volume at a certain storage point suddenly increases, the collection and transportation route can be dynamically adjusted according to the degree of path structure tendency of different categories of collection and transportation operations, and the collection task of this storage point can be preferentially arranged to ensure that the garbage will not be detained.

[0145] In an embodiment of the present application, the scheduling and processing of the food waste collection and transportation resources at the position nodes in the food waste collection and transportation link according to the tracing source requirements of the food waste collection and transportation information corresponding to each food waste collection and transportation link includes:

[0146] Performing density clustering on the tracing source requirements of the food waste collection and transportation information corresponding to each position node in each food waste collection and transportation link to obtain multiple clustering clusters;

[0147] Taking the position nodes in the same clustering cluster as the scheduling and tracing source range at the same level to obtain a multi-level scheduling and tracing source range;

[0148] Based on the multi-level scheduling and tracing source range, performing scheduling and processing on the food waste collection and transportation resources at the position nodes in the food waste collection and transportation link.

[0149] Among them, density-based spatial clustering of applications with noise (DBSCAN) is a clustering algorithm based on the density of data points. It identifies data points in high-density regions and groups these data points into the same class. Different from traditional clustering algorithms, DBSCAN does not require the number of clusters to be specified in advance, can automatically discover clusters of arbitrary shapes, and has good robustness to noise points. In the analysis of the tracing requirements of food waste collection and transportation information, DBSCAN can help identify location nodes with similar characteristics and form multiple clusters. First, obtain the tracing requirements of food waste collection and transportation information for each location node in each link of food waste collection and transportation, including the degree of path structure tendency, time series correlation characteristics, information change rate, etc. According to the characteristics of the data, set the parameters of DBSCAN, such as the minimum number of samples and the radius, which determine which points are considered core points and the size of the clusters. Use the DBSCAN algorithm to cluster all location nodes and identify multiple clusters. Each cluster represents a group of location nodes with similar characteristics, usually having similar collection and transportation patterns or abnormal conditions.

[0150] Among them, a cluster refers to a group of location nodes with similar characteristics identified by the DBSCAN algorithm. The nodes within each cluster show consistent regularity in terms of geographical location, collection and transportation frequency, time series, etc., forming a stable collection and transportation pattern. Through the analysis of clusters, the relationship between different location nodes can be better understood, and the scheduling of collection and transportation resources can be optimized.

[0151] Among them, the location nodes in the same cluster are used as the tracing scope of the same level of scheduling, and a multi-level tracing scope of scheduling is obtained. By managing the tracing scope of different levels of scheduling, the allocation of collection and transportation resources can be controlled more precisely, ensuring that the responsibilities of each link are clear and the operations are standardized. According to the characteristics of the clusters, all location nodes are divided into multiple levels. Each level represents a specific tracing scope of scheduling, usually containing a group of location nodes with similar characteristics. For example, according to characteristics such as the degree of path structure tendency and collection and transportation frequency, the nodes can be divided into three levels: high priority, medium priority, and low priority. Based on the multi-level tracing scope of scheduling, the collection and transportation vehicles and personnel are reasonably arranged. For example, for high-priority nodes, the collection and transportation tasks can be arranged preferentially to ensure that the garbage is cleared in time; while for low-priority nodes, the collection and transportation frequency can be appropriately adjusted to reduce unnecessary resource waste. As new data is continuously added, the multi-level tracing scope of scheduling can be dynamically adjusted. For example, when the collection and transportation pattern of a certain node changes, its belonging tracing scope of scheduling can be re-evaluated and corresponding adjustments can be made.

[0152] Exemplarily, a smart property management platform manages a large community with multiple residential areas, and each residential area has multiple food waste disposal points. The food waste collection and transportation information traceability requirements at each location node in the food waste collection and transportation process are obtained, including the degree of path structure tendency, temporal correlation characteristics, information change rate, etc. For example, information such as the change rate of the garbage volume, the change rate of the arrival time, and the change rate of the residence time at each node is recorded. According to the characteristics of the data, the parameters of density clustering are set. For example, the minimum number of samples is set to 5, and the radius is 0.5 kilometers, indicating that at least 5 nodes within a range of 0.5 kilometers are required to form a clustering cluster. All location nodes are clustered to identify multiple clustering clusters. For example, it is found that nodes A, B, and C form a clustering cluster, nodes D, E, and F form another clustering cluster, and nodes G, H, and I form a third clustering cluster. According to the characteristics of the clustering clusters, all location nodes are divided into multiple levels. For example, it is found that the collection and transportation frequencies of nodes A, B, and C are relatively high, and the degree of path structure tendency is relatively high, so they are divided into high priority levels; the collection and transportation frequencies of nodes D, E, and F are moderate, and the degree of path structure tendency is average, so they are divided into medium priority levels; the collection and transportation frequencies of nodes G, H, and I are relatively low, and the degree of path structure tendency is relatively low, so they are divided into low priority levels. Based on the multi-level scheduling traceability range, the collection and transportation vehicles and personnel are reasonably arranged. For example, for the high-priority nodes A, B, and C, the collection and transportation tasks are preferentially arranged to ensure that the garbage is cleared in time; for the medium-priority nodes D, E, and F, the collection and transportation frequency is appropriately adjusted to ensure that the garbage can be effectively cleared each time; for the low-priority nodes G, H, and I, the collection and transportation frequency can be appropriately reduced to reduce unnecessary resource waste. As new data is continuously added, the multi-level scheduling traceability range can be dynamically adjusted. For example, when the collection and transportation mode of a certain node changes, its belonging scheduling traceability range can be re-evaluated and corresponding adjustments can be made. According to the multi-level scheduling traceability range, the responsible person for each location node is clarified to ensure standard operations. For example, through scanning codes for recording and taking photos for traceability, the personnel responsible for a certain cleaning operation can be quickly found. If the garbage volume at a certain node increases abnormally, the operator responsible for this node can be quickly located for responsibility tracing. By comparing with the normal clustering clusters, behaviors deviating from the conventional mode are identified. For example, if the collection and transportation time of the nodes within a certain clustering cluster suddenly prolongs, or the driving route of a certain vehicle changes, an alarm will be issued to indicate that there may be an abnormal situation. Spare vehicles or personnel can be immediately dispatched to handle it to ensure that the problem is solved in time. According to the multi-level scheduling traceability range, the collection and transportation vehicles and personnel are reasonably arranged to ensure that each link can complete the task efficiently and in a timely manner. For example, it can be recommended to increase the number of trash cans in a certain area, or adjust the collection and transportation frequency to improve the overall efficiency.

[0153] In an embodiment of the present application, the scheduling and processing of the kitchen waste collection and transportation resources of the location nodes in the kitchen waste collection and transportation link based on the multi-level scheduling traceability scope includes:

[0154] For the highest-level scheduling traceability scope in the multi-level scheduling traceability scope, schedule kitchen waste transport vehicles and kitchen waste cleaning operators to the location nodes for anomaly investigation and handling.

[0155] Among them, anomaly investigation refers to identifying behaviors or abnormal situations that deviate from the normal mode by analyzing kitchen waste collection and transportation information and determining their causes. Anomaly handling refers to taking corresponding measures after an anomaly is discovered to ensure that the problem is resolved in a timely manner and normal operation is restored. Anomaly investigation and handling are important means to ensure the smooth progress of the kitchen waste collection and transportation process and can effectively improve reliability and management level.

[0156] Among them, the purpose of scheduling and processing the highest-level scheduling traceability scope is to focus on scheduling and processing the highest-level (i.e., the highest priority) scheduling traceability scope in the multi-level scheduling traceability scope. Usually, the highest-level scheduling traceability scope contains the most urgent or important location nodes, and the abnormal situations of these nodes may have a greater impact on the entire collection and transportation process. Therefore, kitchen waste transport vehicles and cleaning operators will be preferentially scheduled to these nodes for anomaly investigation and handling to ensure that the problems are resolved in a timely manner.

[0157] Exemplarily, for the scheduling of kitchen waste collection and transportation resources towards the position of the node structure according to the adjusted traceability information, first, sensors are used to continuously monitor parameters such as the filling degree and temperature of the kitchen waste bins in real time, and an alarm is automatically generated when overflow or abnormal conditions are detected. After receiving the alarm, the scheduling center and relevant staff will be notified, and the urgency of the problem will be evaluated to determine whether it is necessary to immediately mobilize resources. Through dynamic resource allocation within the divided traceability scope, the scheduling of kitchen waste collection and transportation vehicles and personnel is optimized, and the nearest kitchen waste collection and transportation vehicles and an appropriate number of staff are preferentially dispatched to handle the situation. After the on-site staff arrive, the kitchen waste will be quickly cleaned up and the cause of the anomaly will be inspected, and necessary measures will be taken to solve the problem. If potential safety hazards are found, the safety emergency procedure will be initiated to ensure on-site safety. Through this process, the property management company can efficiently respond to abnormal situations and ensure the environmental hygiene and safety of the community.

[0158] In this embodiment, by scheduling and tracing the highest-level scheduling traceability scope, the most urgent or important location nodes can be processed preferentially to ensure that problems are solved in a timely manner. For example, according to the priority evaluation results, spare vehicles and waste collection personnel can be dispatched to the highest-level nodes to ensure that waste does not accumulate. When the amount of waste at a storage point suddenly increases or the collection route changes, the collection plan can be dynamically adjusted according to the results of anomaly detection and handling to ensure that waste can be effectively cleared during each collection. By scheduling and tracing the highest-level scheduling traceability scope, the whole process of food waste collection and transportation can be monitored in real time. When an abnormal situation is detected, the problem node can be quickly located and corresponding handling measures can be taken. For example, if it is found that the collection time of a certain node suddenly extends or the driving route of a vehicle changes, an alarm will be immediately issued to notify the relevant personnel to conduct an inspection. By recording the results of anomaly detection and handling, the responsible person for each link can be identified to ensure standard operation and prevent human errors or improper behaviors. For example, by scanning codes for recording and taking photos for traceability, the personnel responsible for a certain waste collection operation can be quickly found for responsibility tracing.

[0159] Figure 4 The structure diagram of a food waste collection and transportation information traceability device of a smart property management platform provided by an embodiment of the present invention. This device can be applied to Figure 1 the shown implementation environment. This device can also be applicable to other exemplary implementation environments and be specifically configured in other devices. This embodiment does not limit the implementation environment applicable to this device.

[0160] As Figure 4 shown, the exemplary food waste collection and transportation information traceability device of the smart property management platform includes:

[0161] An information acquisition module 401, configured to acquire food waste collection and transportation information corresponding to a plurality of food waste collection and transportation links;

[0162] A path structure trend analysis module 402, configured to analyze the path structure trends of a plurality of location nodes in each of the food waste collection and transportation links according to the food waste collection and transportation information, so as to determine the food waste collection and transportation information traceability requirements corresponding to each of the food waste collection and transportation links;

[0163] A scheduling processing module 403, configured to, based on a pre-installed smart property management platform, perform scheduling processing on the food waste collection and transportation resources of the location nodes in the food waste collection and transportation links according to the food waste collection and transportation information traceability requirements corresponding to each of the food waste collection and transportation links.

[0164] In the food waste collection and transportation information traceability device of the exemplary smart property management platform, information acquisition of multiple food waste collection and transportation links is covered, ensuring that every step from waste generation to final treatment is recorded and monitored. Comprehensive information collection provides a solid foundation for subsequent analysis and tracing; by analyzing the path structure trends of multiple location nodes in each food waste collection and transportation link, not only the geographical location relationship (i.e., the spatial distribution of the path) is considered, but also the time dimension (such as collection and transportation time, residence time, etc.) is combined. This time-space combined analysis method can more accurately reflect the actual situation of food waste collection and transportation. In the actual process, path structure trend analysis can identify normal and abnormal collection and transportation operations. Based on the analysis results of path structure trends, future collection and transportation needs can be predicted, and the optimal collection and transportation routes and schedules can be planned in advance, thereby improving overall efficiency. At the same time, through long-term monitoring of path structure trends, the collection and transportation process can be continuously optimized to reduce unnecessary waste of resources. According to the results of path structure trend analysis, the traceability needs of food waste collection and transportation information corresponding to each food waste collection and transportation link can be determined, and then the food waste collection and transportation resources can be accurately dispatched according to the actual situation to ensure that each link can be handled in a timely and effective manner.

[0165] It should be noted that the device for tracing the collection and transportation information of kitchen waste on the smart property management platform provided in the above embodiment and the method for tracing the collection and transportation information of kitchen waste on the smart property management platform provided in the above embodiment belong to the same concept, wherein the specific manner in which each module and unit performs the operation has been described in detail in the method embodiment, and will not be repeated here. In actual application, the device for tracing the collection and transportation information of kitchen waste on the smart property management platform provided in the above embodiment can allocate the above functions to different functional modules as needed, that is, divide the internal structure of the device into different functional modules to complete all or part of the functions described above, and this is not limited here.

[0166] An embodiment of the present application also provides an electronic device, comprising: one or more processors; a storage device for storing one or more programs, and when the one or more programs are executed by the one or more processors, the electronic device implements the method for tracing food waste collection and transportation information of the smart property management platform provided in the above-mentioned embodiments.

[0167] Figure 5 This is a schematic diagram of the structure of a computer system suitable for electronic equipment provided by one embodiment of the present invention. It should be noted that: Figure 5 The computer system 500 of the electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0168] like Figure 5As shown, computer system 500 includes a Central Processing Unit (CPU) 501, which can perform various appropriate actions and processes according to programs stored in a Read-Only Memory (ROM) 502 or programs loaded from a storage section 508 into a Random Access Memory (RAM) 503, such as executing the methods described in the above embodiments. In the RAM 503, various programs and data required for system operations are also stored. The CPU 501, ROM 502, and RAM 503 are connected to each other via a bus 504. An Input / Output (I / O) interface 505 is also connected to the bus 504.

[0169] The following components are connected to the I / O interface 505: an input section 506 including a keyboard, a mouse, etc.; an output section 507 including, for example, a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), etc., and a speaker, etc.; a storage section 508 including a hard disk, etc.; and a communication section 509 including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication section 509 performs communication processing via a network such as the Internet. A drive 510 is also connected to the I / O interface 505 as needed. A removable medium 511, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 510 as needed so that a computer program read from it can be installed into the storage section 508 as needed.

[0170] Specifically, according to an embodiment of the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present application includes a computer program product that includes a computer program carried on a computer-readable medium, and the computer program includes a computer program for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network via the communication section 509, and / or installed from the removable medium 511. When the computer program is executed by a Central Processing Unit (CPU) 501, various functions defined in the device of the present application are executed.

[0171] It should be noted that the computer-readable medium shown in the embodiments of the present application can be a computer-readable signal medium, a computer-readable storage medium, or any combination of the two. A computer-readable storage medium can be, for example, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples of the computer-readable storage medium may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, a computer-readable signal medium may include a data signal propagated in a baseband or as a part of a carrier wave, which carries a computer-readable computer program. Such a propagated data signal may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The computer program contained on the computer-readable medium can be transmitted by any appropriate medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0172] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of devices, methods, and computer program products according to various embodiments of the present application. Among them, each block in the flowchart or block diagram may represent a module, a program segment, or a part of code, and the above module, program segment, or part of code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than marked in the accompanying drawings. For example, two consecutive blocks shown may actually be executed substantially in parallel, and they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram or flowchart, and the combination of blocks in the block diagram or flowchart, can be implemented by a dedicated hardware-based system for performing the specified functions or operations, or can be implemented by a combination of dedicated hardware and computer instructions.

[0173] The units involved in the embodiments described in this application can be implemented in software or in hardware, and the described units can also be provided in a processor. Among them, the names of these units do not constitute a limitation to the units themselves in some cases.

[0174] Another aspect of this application also provides a computer-readable storage medium. The computer-readable storage medium stores multiple instructions, and these instructions are suitable for being loaded by a processor to execute the steps in any of the methods for tracing the information of kitchen waste collection and transportation in the intelligent property management platform provided by the embodiments of this application. This computer-readable storage medium can be included in the electronic device described in the above embodiments, or can exist alone without being assembled into the electronic device.

[0175] It should be noted that the above sequence of the embodiments of the present invention is only for description and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0176] Each embodiment in this specification is described in a progressive manner. For the same or similar parts among the embodiments, reference can be made to each other. Each embodiment focuses on the differences from other embodiments.

Claims

1. A method for tracing kitchen waste collection and transportation information on a smart property management platform, characterized in that: The method comprises: Obtaining the food waste collection and transportation information corresponding to multiple food waste collection and transportation links; According to the food waste collection and transportation information, the path structure trend of multiple location nodes in each food waste collection and transportation link is analyzed to determine the food waste collection and transportation information traceability requirements corresponding to each food waste collection and transportation link; Based on the pre-installed smart property management platform, according to the traceability requirements of the kitchen waste collection and transportation information corresponding to each kitchen waste collection and transportation link, the kitchen waste collection and transportation resources of the location nodes in the kitchen waste collection and transportation link are dispatched and processed; the process of obtaining the traceability requirements of the kitchen waste collection and transportation information includes: According to the food waste collection and transportation information, the path structure trend degree corresponding to each food waste collection and transportation link is obtained; According to the path structure trend degree corresponding to each of the food waste collection and transportation links, the food waste collection and transportation information traceability requirements corresponding to each of the food waste collection and transportation links are determined; The method of scheduling the food waste collection and transportation resources of the location nodes in the food waste collection and transportation links according to the food waste collection and transportation information tracing requirements corresponding to each food waste collection and transportation link includes: Density clustering is performed on the traceability requirements of the food waste collection and transportation information corresponding to each of the location nodes in each of the food waste collection and transportation links to obtain multiple clusters; The location nodes in the same cluster are used as the scheduling traceability scope of the same level to obtain a multi-level scheduling traceability scope; Based on the multi-level scheduling traceability range, the food waste collection and transportation resources of the location nodes in the food waste collection and transportation link are scheduled and processed.

2. The method for tracing kitchen waste collection and transportation information of a smart property management platform according to claim 1, characterized in that: The multiple food waste collection and transportation links include a food waste storage link, a food waste transportation link, a food waste removal link, and a food waste storage equipment cleaning link. The obtaining of food waste collection and transportation information corresponding to the multiple food waste collection and transportation links includes: Acquiring location information and status information of the food waste storage device in the food waste storage link through a pre-installed sensor; Obtaining the driving route, stop points and collection time of the food waste transport vehicle in the food waste transport link through the pre-installed positioning device; Acquiring the cleaning operation information corresponding to the kitchen waste cleaning operator in the kitchen waste cleaning link through a pre-configured scanning device; Acquire the cleaning operation information of the food waste storage equipment in the cleaning link of the food waste storage equipment.

3. The method for tracing kitchen waste collection and transportation information of a smart property management platform according to claim 1, characterized in that: The step of obtaining the path structure trend corresponding to each of the food waste collection and transportation links according to the food waste collection and transportation information includes: Dividing the food waste collection and transportation information into multiple information parts according to a preset food waste collection and transportation area; For any of the information parts, determining the time series correlation characteristics of each location node; The position nodes with the same category in each of the food waste collection and transportation links and whose timing correlation characteristics are greater than the preset timing correlation characteristic threshold are taken as a path structure trend change range, and the path structure trend degree corresponding to each of the food waste collection and transportation links within the path structure trend change range is determined.

4. The method for tracing kitchen waste collection and transportation information of a smart property management platform as claimed in claim 3, characterized in that: After dividing the food waste collection and transportation information into multiple information parts, the method further includes: The element items of each information in each of the information parts are arranged according to the arrival order of the location nodes of a single batch, wherein the element values ​​of the element items include the information corresponding to each of the food waste collection and transportation links, and the element values ​​are used to determine the time series correlation characteristics of each of the location nodes.

5. The method for tracing kitchen waste collection and transportation information of a smart property management platform as claimed in claim 3, characterized in that: The determining of the time series correlation characteristics of each location node includes: Obtaining the information change rate of all location nodes in each of the food waste collection and transportation links, and the number of all location nodes; The time series correlation feature of each location node is determined according to the information change rate of all the location nodes and the number of all the location nodes.

6. The method for tracing kitchen waste collection and transportation information of a smart property management platform as claimed in claim 3, characterized in that: Determining the path structure trend degree corresponding to each of the kitchen waste collection and transportation links within the path structure trend change range includes: The position nodes within the range of path structure trend change are regarded as path subsequences; Determining the path subsequence differences corresponding to each of the food waste collection and transportation links according to the length of the path subsequence; According to the differences in the path subsequences corresponding to the food waste collection and transportation links and the temporal correlation characteristics of each position node in each path subsequence, the degree of path structure tendency corresponding to each food waste collection and transportation link is determined.

7. The method for tracing kitchen waste collection and transportation information of a smart property management platform as claimed in claim 3, characterized in that: Determining the traceability requirements of the food waste collection and transportation information corresponding to each food waste collection and transportation link according to the path structure trend degree corresponding to each food waste collection and transportation link includes: According to the path structure trend degree corresponding to each of the food waste collection and transportation links, determine the path structure trend degree corresponding to the same type of collection and transportation operations at each of the location nodes; Based on the path structure trend degree corresponding to the same type of collection and transportation operations at each of the location nodes, and the path subsequence corresponding to the same type of collection and transportation operations within the range of change of the path structure trend, the traceability requirements of the food waste collection and transportation information corresponding to each of the location nodes in each of the food waste collection and transportation links are determined.

8. The method for tracing kitchen waste collection and transportation information of a smart property management platform according to claim 1, characterized in that: The step of scheduling and processing the kitchen waste collection and transportation resources of the location nodes in the kitchen waste collection and transportation link based on the multi-level scheduling traceability range includes: For the highest level of scheduling and tracing scope in the multi-level scheduling and tracing scope, dispatch food waste transport vehicles and food waste removal operators to the location node to conduct abnormality investigation and abnormality processing.

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