Kitchen waste collection and transportation information traceability method of intelligent property management platform

Abstract

The invention relates to the technical field of data processing, in particular to a kitchen waste collection and transportation information traceability method of an intelligent property management platform, which comprises the following steps: obtaining kitchen waste collection and transportation information corresponding to a plurality of kitchen waste collection and transportation links; according to the kitchen waste collection and transportation information, analyzing path structure trends of a plurality of position nodes in each kitchen waste collection and transportation link so as to determine kitchen waste collection and transportation information tracing requirements corresponding to each kitchen waste collection and transportation link; and based on a pre-installed intelligent property management platform, according to the kitchen waste collection and transportation information tracing requirements corresponding to the kitchen waste collection and transportation links, kitchen waste collection and transportation resources of the position nodes in the kitchen waste collection and transportation links are scheduled. According to the method and the device, the kitchen waste collection and transportation information corresponding to the multiple kitchen waste collection and transportation links is subjected to data processing, so that the kitchen waste collection and transportation information tracing requirements corresponding to the kitchen waste collection and transportation links are determined, and the kitchen waste collection and transportation information is efficiently traced.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a method for tracing kitchen waste collection and transportation information of a smart property management platform. Background Art

[0002] The smart property management platform is a comprehensive management service platform that combines new-generation information technologies such as the Internet of Things, cloud computing, big data, and mobile Internet.

[0003] The smart property management platform can achieve traceability of food waste collection and transportation information through a variety of methods, such as: using IoT devices, such as sensors on smart trash cans to collect data, record the time and weight of food waste in real time and upload it to the platform; installing positioning devices for collection and transportation vehicles to display the driving trajectory in real time to ensure that collection and transportation are carried out according to the prescribed route; assigning QR codes or labels to trash cans or collection and transportation containers, scanning the code to record and associate information during collection and transportation; recording the identity information and operation records of collection and transportation personnel to ensure that responsibility can be traced; taking photos and leaving traces through vehicle-mounted or handheld devices during the collection and transportation process to record the status of garbage and the collection and transportation site, and at the same time associating information on garbage placement, collection and transportation, and processing to form a complete information chain. When there are abnormal conditions in the garbage collection and transportation process during the actual property management operation, the abnormal collection and transportation path node positioning and subsequent scheduling and processing of garbage collection and transportation vehicles and other resources can be realized quickly and accurately.

[0004] In the food waste collection and transportation information operation process of the smart property management platform, information collection is usually achieved through multiple garbage classification storage location information in different communities and different time nodes of different collection and transportation operations of garbage collection and transportation vehicles. The food waste collection and transportation information will show more obvious path structure information at the data level, that is, the actual geographical location structure of the routes of the garbage classification storage locations in the communities that the garbage collection and transportation vehicles pass through during the collection and transportation process. For the garbage collection and transportation process with abnormal conditions, the scheduling and processing of resources such as garbage collection and transportation vehicles managed by the property should be an efficient processing achieved in the information tracing process, and it is necessary to adjust the traceability information for the food waste collection and transportation conditions of multiple collection and transportation path information.

[0005] Therefore, how to efficiently trace the food waste collection and transportation information on the smart property management platform is an urgent problem that needs to be solved. Summary of the invention

[0006] In order to solve the technical problem of how to efficiently trace the collection and transportation information of restaurant kitchen waste on a smart property management platform, the purpose of the present invention is to provide a method for tracing the collection and transportation information of restaurant kitchen waste on a smart property management platform. The technical solution adopted is as follows: The present application embodiment provides a method for tracing kitchen waste collection and transportation information of a smart property management platform, the method comprising: 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, the food waste collection and transportation resources of the location nodes in the food waste collection and transportation links are scheduled and processed according to the food waste collection and transportation information traceability requirements corresponding to each of the food waste collection and transportation links.

[0007] In some embodiments, 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.

[0008] In some embodiments, the path structure trend of multiple location nodes in each of the food waste collection and transportation links is analyzed 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, including: 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.

[0009] In some embodiments, obtaining the path structure trend degree 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.

[0010] In some embodiments, 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.

[0011] In some embodiments, determining the timing 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.

[0012] In some embodiments, determining the path structure trend degree corresponding to each of the food 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.

[0013] In some embodiments, 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 tendency degree corresponding to each of the food waste collection and transportation links, the path structure tendency degree corresponding to the same type of collection and transportation operations at each of the location nodes is determined; 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.

[0014] In some embodiments, the scheduling of 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 of the food waste collection and transportation links 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.

[0015] In some embodiments, the scheduling of the food waste collection and transportation resources of the location nodes in the food 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, the food waste transport vehicles and food waste removal operators are dispatched to the location node to conduct abnormality investigation and abnormality processing.

[0016] The present invention has the following beneficial effects: 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

[0017] 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.

[0018] 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; 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; Figure 3 A schematic diagram of location nodes in a food waste transportation link provided by an embodiment of the present invention; Figure 4A schematic diagram of the structure of a device for tracing kitchen waste collection and transportation information of a smart property management platform provided by one embodiment of the present invention; Figure 5 A schematic diagram of the structure of a computer system suitable for electronic equipment provided by one embodiment of the present invention. DETAILED DESCRIPTION

[0019] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following is a detailed description of the specific implementation method, structure, features and effects of a method for tracing kitchen waste collection and transportation information of a smart property management platform proposed by the present invention in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0020] It should be noted that the terms "first", "second", etc. in the specification of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, device, product or equipment comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or equipment.

[0021] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0022] The following is a detailed description of a method for tracing kitchen waste collection and transportation information on a smart property management platform provided by the present invention in conjunction with the accompanying drawings.

[0023] See also Figure 1 , Figure 1 A schematic diagram of the 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. Figure 1As shown, the implementation environment includes a restaurant kitchen waste collection and transportation link 101, a smart property management terminal 102, and a server 103. The smart property management terminal 102 can be a terminal device installed with a smart property management platform, including but not limited to mobile devices, laptops, tablets, handheld computers, PADs, desktop computers, etc. with local computing capabilities; the smart 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 supports tracing the restaurant kitchen waste collection and transportation information; the smart property management terminal 102 can, but is not limited to, communicate with the server 103 through a network, and the above network can include but is not limited to: a wired network, a wireless network, wherein the wired network includes: a local area network, a metropolitan area network, and a wide area network, and the wireless network includes: Bluetooth, WIFI, and other networks that realize wireless communication. The above-mentioned smart property management terminal 102 can, but is not limited to, include a human-computer interaction screen, a processor, and a memory. The above-mentioned processor can, but is not limited to, be used to respond to human-computer interaction operations, perform corresponding operations, or generate corresponding instructions.

[0024] As an optional method, the smart property management terminal 102 can be a computer, through which the food waste collection and transportation information corresponding to the multiple food waste collection and transportation links 101 can be obtained in real time; the server 103 can be a single server, or a server cluster composed of multiple servers, or a cloud server. The above is only an example, and this embodiment does not make any limitation to this.

[0025] As an optional method, the following steps of the method for tracing kitchen waste collection and transportation information of the smart property management platform can be performed on the smart property management terminal 102: 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, the food waste collection and transportation resources of the location nodes in the food waste collection and transportation links are scheduled and processed according to the food waste collection and transportation information traceability requirements corresponding to each of the food waste collection and transportation links.

[0026] 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.

[0027] 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.

[0028] 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.

[0029] 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.

[0030] 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 be specifically executed by devices in other implementation environments, and this embodiment does not limit the implementation environment to which the method is applicable.

[0031] 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: In step S210, the food waste collection and transportation information corresponding to the multiple food waste collection and transportation links is obtained.

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] Among them, by analyzing the path structure trends of multiple position nodes in each of the food waste collection and transportation links, stable patterns or trends can be identified by analyzing the spatial and temporal relationships of multiple position nodes in each link in the food waste collection and transportation process.

[0037] Among them, when there is a need to trace the information of food waste collection and transportation, the information content and scope that needs to be traced in each food waste collection and transportation link can be determined based on the results of the path structure trend analysis. Traceability requirements include: responsibility tracing, determining the person responsible for each link, ensuring operational specifications, and preventing human errors or improper behavior; abnormality handling, when an abnormal situation is detected, the problem node can be quickly located and corresponding treatment measures can be taken; resource optimization, according to the traceability requirements, the collection and transportation vehicles and personnel are reasonably arranged to ensure the most effective use of resources.

[0038] In step S230, based on the pre-installed smart property management platform, the food waste collection and transportation resources of the location nodes in the food waste collection and transportation links are scheduled and processed according to the food waste collection and transportation information traceability requirements corresponding to each of the food waste collection and transportation links.

[0039] Among them, when scheduling and processing the food waste collection and transportation resources of the location nodes in the food waste collection and transportation link, the food waste collection and transportation resources (such as vehicles, personnel, etc.) can be dynamically adjusted and scheduled according to the traceability requirements of the food waste collection and transportation information to ensure that each link can complete the task efficiently and timely. Specifically, it includes: resource allocation, according to the amount of garbage and collection and transportation needs of each location node, reasonably arrange the collection and transportation vehicles and personnel; abnormal response, when an abnormal situation occurs, it can quickly dispatch spare vehicles or personnel to deal with it to ensure that the problem is solved in time; optimized scheduling, through the analysis of historical data and real-time monitoring, continuously optimize the collection and transportation routes and timetables to improve overall efficiency.

[0040] 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.

[0041] 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.

[0042] 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: 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.

[0043] Among them, in the food waste storage link, the location information and status information of the equipment are collected in real time through sensors installed on the food waste storage equipment (such as smart trash cans, garbage stations, etc.). Specifically, the sensor can obtain the geographical coordinates (longitude and latitude) of the trash can or garbage station to ensure that each storage point can be accurately located; status information: the sensor can monitor the status of the trash can, such as whether it is full, damaged, or has an odor, etc. This information can help determine whether it needs to be collected or maintained immediately. Common sensor types include: GPS (Global Positioning System) module, which is used to obtain geographical location information; weight sensor, which is used to monitor the weight of the garbage in the trash can to determine whether it is full; infrared sensor, which is used to detect the capacity of the trash can to determine whether it is close to overflowing; temperature and humidity sensor, which is used to monitor the environmental conditions in the trash can to prevent the garbage from corrupting and producing odor.

[0044] Among them, in the food waste transportation link, the vehicle's driving route, stop points and collection and transportation time are recorded in real time through positioning equipment (such as GPS, Beidou, etc.) installed on the transport vehicle. Specifically, it includes: driving route, recording the driving path of the vehicle from one storage point to another, ensuring that the vehicle travels according to the predetermined route; stop points, recording the specific location of each stop of the vehicle, ensuring that the vehicle is collected and transported at the designated storage point; collection and transportation time, recording the arrival time and departure time of the vehicle at each storage point, ensuring that the collection and transportation task is completed on time. Commonly used positioning equipment includes: GPS / Beidou positioning module, used to track the vehicle's driving route and location in real time; on-board camera, used to shoot the situation at the collection and transportation site to ensure standardized operation; RFID (Radio Frequency Identification) tag, used to identify the unique identification of the storage point to ensure that the vehicle is parked at the correct location.

[0045] Among them, in the process of kitchen waste collection and transportation, the operation information of the collection and transportation operators is recorded through scanning devices installed on handheld devices or vehicles (such as QR code scanners, RFID readers, etc.). Specifically, it includes: code scanning records, when the collection and transportation personnel use handheld devices to scan the QR code or RFID tag on the trash can every time they collect and transport the garbage, and record the source information of the garbage; operation information, recording the operation time and operation content (such as loading, unloading, etc.) of the collection and transportation personnel to ensure that each step of the operation is traceable; taking pictures to leave traces, the collection and transportation personnel can take pictures with handheld devices to record the status of the garbage and the situation at the collection and transportation site to ensure the operation is standardized. Commonly used scanning devices include: QR code scanners, used to scan the QR code on the trash can and record the source information of the garbage; RFID readers, used to read the RFID tags on the trash can to ensure that each trash can can be accurately identified; handheld terminals, handheld devices equipped with cameras and scanning functions, which are convenient for collection and transportation personnel to record operation information.

[0046] Among them, in the cleaning process of the 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 and end time of each cleaning to ensure that the cleaning work is completed on time; cleaning results, recording the status of the equipment after cleaning, such as whether it is clean or damaged, etc., to ensure that the equipment meets the hygiene standards; operator information, recording the information of the operator responsible for cleaning to ensure that responsibility can be traced. Commonly used cleaning equipment includes: sensors, used to monitor parameters such as water temperature, water pressure, and amount of cleaning agent during the cleaning process to ensure the quality of cleaning; manual input, manually inputting specific information of the cleaning operation through a handheld terminal or computer to ensure that each step of the operation is traceable; cameras, used to shoot the status of the equipment after cleaning to ensure that the cleaning effect meets the standards.

[0047] In this embodiment, through sensors and positioning devices, the status of the kitchen waste storage equipment and the driving conditions of the transport vehicles can be grasped in real time, and the collection and transportation tasks can be reasonably arranged to reduce unnecessary waiting time and empty driving rate. When the amount of garbage at a certain storage point suddenly increases, the collection and transportation route can be dynamically adjusted, and the collection and transportation tasks of the storage point can be arranged first to ensure that the garbage is cleared and transported in time. Through sensors and positioning devices, 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. Through detailed records of the removal and cleaning operations, the person in charge of each link can be identified to ensure the operation is standardized and prevent human errors or improper behavior. Through sensors, positioning devices and scanning devices, a large amount of historical data has been accumulated, and more accurate analysis and prediction can be performed. 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 long-term monitoring and analysis of historical data, 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 are often overflowing, it can be considered to increase the number of garbage bins in the area or adjust the collection and transportation time.

[0048] In one embodiment of the present application, the path structure trend of multiple location nodes in each of the food waste collection and transportation links is analyzed 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, including: 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.

[0049] Among them, in the process of food waste collection and transportation information circulation, since the changing characteristics of food waste collection and transportation information are mainly limited by the fixed influence of food waste removal, food waste collection and transportation routes, and food waste storage locations in multiple communities, the data will show an obvious path structure trend. The path structure trend will affect the traceability needs in the property management process. Therefore, information anomalies in the collection and transportation process will affect the position positioning analysis of the node's path structure trend, and should be adjusted.

[0050] Among them, the path structure trend refers to the stability and regularity of the spatial and temporal relationship of multiple location nodes in each food waste collection and transportation link during the food waste collection and transportation process. Specifically, the path structure trend reflects the following characteristics: node distribution, the geographical distribution of each location node, including the distance and relative position between them; topological relationship, the connection mode and order between nodes, that is, the driving path of a vehicle from one node to another; temporal association, the time series relationship between nodes, such as the time interval and residence time of each collection and transportation; anomaly detection, the path structure trend can also be used to identify behaviors that deviate from the normal mode, such as vehicles deviating from the scheduled route, abnormal increase in the amount of garbage at a certain node, etc.

[0051] In this embodiment, by analyzing the degree of trend of 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 reduced. For example, the collection and transportation routes can be optimized according to the path similarity to ensure that the vehicles travel along the shortest path. When the amount of garbage at a storage point suddenly increases, the collection and transportation routes can be dynamically adjusted according to the degree of trend of the path structure, and the collection and transportation tasks of the storage point can be prioritized to ensure that the garbage will not be stranded. Through the analysis of the degree of trend of the path structure, the whole process of food and 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 a vehicle deviates from the scheduled route or the amount of garbage in a trash can increases abnormally, an alarm will be immediately issued to notify relevant personnel to check. Through the analysis of the degree of trend of the path structure, the person in charge of each link can be clarified to ensure standardized operation and prevent human errors or improper behavior. For example, the person responsible for a certain cleaning operation can be quickly found by scanning the code and taking pictures to leave traces. Through the analysis of the degree of trend of 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 storage point can be predicted based on historical data, and collection and transportation tasks can be arranged in advance. Through long-term monitoring and analysis of the trend of the path structure, the collection and transportation process of food waste can be continuously optimized and the overall management level can be improved. For example, if it is found that certain storage points are often overflowing, it can be considered to increase the number of garbage bins in the area or adjust the collection and transportation time.

[0052] In one embodiment of the present application, obtaining the path structure trend degree 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.

[0053] Among them, the preset food waste collection and transportation area refers to the food waste collection and transportation service area pre-demarcated according to geographical and management needs. Each area usually contains multiple communities or a specific geographical range, which is used to centrally manage and analyze food waste collection and transportation information. By dividing the area, the collection and transportation tasks can be better organized and optimized to ensure that the collection and transportation work in each area is carried out efficiently. The preset food waste collection and transportation area can be determined by the following methods: Geographic Information System (GIS), using GIS technology to divide different collection and transportation areas according to geographical boundaries such as communities, streets, and administrative divisions; management needs, according to the property management company's operating strategy, the entire service area is divided into several sub-areas, each sub-area is responsible for a specific collection and transportation team; historical data, based on historical collection and transportation data, identify areas with large amounts of garbage and use them as key collection and transportation areas.

[0054] Among them, multiple information parts refer to dividing the entire food waste collection and transportation information according to the preset food waste collection and transportation area range to form multiple independent information units. Each information part contains relevant data of all food waste collection and transportation links in the area, such as location information of storage equipment, driving routes of transportation vehicles, operation records of cleaning operators, etc. The division of information parts can be carried out in the following ways: by region, according to the preset food waste collection and transportation area range, the entire information set is divided into multiple regional information parts, for example, a large community can be divided into multiple information parts such as the east district, the west district, the south district, and the north district; by time, according to the time period of collection and transportation, the information is divided into different information parts, for example, it can be divided into time periods such as days, weeks, and months, so as to facilitate the analysis of collection and transportation modes in different time periods; by collection and transportation type, according to the type of food waste (such as household food waste, commercial food waste, etc.), the information is divided into different information parts, so as to facilitate targeted analysis of the collection and transportation of different types of garbage.

[0055] Among them, the temporal correlation characteristics of each location node refer to the time series relationship between each location node during the collection and transportation of food waste. Specifically, the temporal correlation characteristics reflect the temporal regularity of the collection and transportation order, residence time, interval time, etc. between nodes. By analyzing these characteristics, common collection and transportation patterns and abnormal situations can be identified. The extraction and analysis of temporal correlation characteristics 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 timestamp 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 time of two nodes has a strong correlation to determine whether they belong to the same collection and transportation path; by comparing normal temporal correlation characteristics, behaviors that deviate from the normal pattern can be identified. For example, if the collection and transportation time of a node is suddenly extended, or the driving route of a vehicle changes, an alarm will be issued to indicate that there may be an abnormal situation.

[0056] The same category refers to food waste collection and transportation links or location nodes with similar characteristics during the food waste collection and transportation process. These links or nodes may belong to the same type of collection and transportation tasks, or have similar geographical locations, collection and transportation frequencies, etc. By grouping nodes of the same category, common collection and transportation patterns and abnormal situations can be better identified.

[0057] Among them, the path structure trend change range refers to a specific area composed of location nodes with similar temporal correlation characteristics and belonging to the same category during the collection and transportation of food waste. These nodes show consistent collection and transportation patterns in space and time, forming a stable path structure. The identification of 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 a preset temporal correlation feature threshold, the nodes whose temporal correlation features are greater than the threshold are screened out. For example, a minimum correlation coefficient threshold can be set. Only when the collection and transportation time correlation of two nodes exceeds the threshold, they are classified into the same path structure trend change range; with the continuous addition of new data, the path structure trend change range can be dynamically adjusted. For example, when the collection and transportation mode of a node changes, the path structure trend change range to which it belongs can be re-evaluated and adjusted accordingly; in the form of a map or chart, the node distribution and collection and transportation paths within the path structure trend change range can be intuitively displayed. For example, each node within the path structure trend change range can be marked on the map, and different collection and transportation paths can be represented by different colors.

[0058] Exemplarily, since the acquired information on the collection and transportation of food waste is mainly composed of time series data of multiple links in the process of food waste collection and transportation, that is, the placement of food waste bins in different communities, corresponding to the information set of multiple links such as food waste collection and transportation vehicles, sanitation and cleaning, and the placement of food waste collection and transportation equipment, in fact, when there is an abnormality in the collection and transportation of food waste and there is a need for tracing the source of information, it is necessary to locate the path structure trend of the node. The traceability demand in different links of the collection and transportation process will be closely related to the location of the collection and transportation process, that is, the time series correlation relationship of the records at different positions in the food waste collection and transportation process, and the determination of the path structure trend of the node is based on the difference in the change of food waste collection and transportation information at the node to achieve screening, so it is necessary to determine the traceability demand of the node according to the change characteristics of the correlation relationship of the food waste collection and transportation information at the node. The change characteristics of the correlation relationship of the food waste collection and transportation information are mainly manifested in the path structure trend of information change, that is, affected by the placement of the food waste bin and the community food waste removal route, there will be a time series correlation relationship between the collection and transportation information records of food waste transportation vehicles at different locations.

[0059] For example, see Figure 3 , Figure 3 This is a schematic diagram of the location nodes of the food waste transportation link provided by an embodiment of the present invention. Figure 3 It can be seen that the food waste transport vehicles often enter the community from Gate 1 of Community A to collect and transport food waste. For all the food waste bins in Community A (i.e. Figure 3 The circle in the figure and Gate 1, the starting point of the food waste transportation vehicle, will plan at least one shortest food waste collection and transportation route. For any food waste bin placement location, there will be a time-series correlation relationship between it and other nearby food waste bin placement locations in the food waste transportation vehicle removal record, which is manifested as a path structure trend.

[0060] In this embodiment, by analyzing the range of changes in the path structure trend, 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. When the amount of garbage at a storage point suddenly increases, the collection and transportation route can be dynamically adjusted according to the range of changes in the path structure trend, and the collection and transportation tasks of the storage point can be arranged first to ensure that the garbage will not be stranded. Through the analysis of the range of changes in the path structure trend, the whole process of food and 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 a vehicle is found to have deviated from the scheduled route, or the amount of garbage in a garbage bin has increased abnormally, an alarm will be immediately issued to notify relevant personnel to check. Through the analysis of the range of changes in the path structure trend, the person in charge of each link can be clarified to ensure standardized operation and prevent human errors or improper behavior. For example, the person responsible for a certain cleaning operation can be quickly found by scanning the code and taking pictures to leave traces. Through the analysis of the range of changes in the path structure trend, a large amount of historical data has been accumulated, and more accurate predictions and optimizations can be made. For example, the amount of garbage generated at a storage point can be predicted based on historical data, and collection and transportation tasks can be arranged in advance. Through long-term monitoring and analysis of the range of changes in the path structure, the collection and transportation process of food waste can be continuously optimized and the overall management level can be improved. For example, if it is found that certain storage points are often overflowing, it can be considered to increase the number of garbage bins in the area or adjust the collection and transportation time.

[0061] In one embodiment of the present application, after dividing the food waste collection and transportation information into multiple information parts, it also 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.

[0062] Among them, element items refer to the specific data items in the food waste collection and transportation information, and each element item represents a specific attribute or feature. These element items contain various information related to the food waste collection and transportation process, such as location, status, time, operator, etc. By analyzing these element items, we can fully understand the specific situation of each link. Common element items include: location information: the geographical location (longitude, latitude) of the food waste storage equipment; status information: the status of the trash 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 record of the cleaning personnel (such as scanning code records, taking photos to leave traces, etc.); cleaning information: the cleaning time and cleaning results of the storage equipment; garbage type: the specific type of food waste (such as household food waste, commercial food waste, etc.); collection and transportation frequency: the collection and transportation frequency of a certain node (such as once a day, twice a week, etc.).

[0063] The arrival order of a single batch of location nodes refers to the time sequence in which the transport vehicles arrive at each location node in accordance with 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 sequence of each node can be accurately grasped to ensure that the collection and transportation task is completed on time.

[0064] Among them, the element value refers to the specific value or state of each element item, which is used to describe the specific situation in the collection and transportation process of food waste. By analyzing the element values, the time-series 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: geographic location coordinates: specific latitude and longitude values, used to identify the exact location of each location node; garbage weight: the weight of garbage in the trash can, used to determine whether it is full; driving time: the driving time of the vehicle from one node to another, used to optimize route planning; dwell time: the dwell time of the vehicle at each node, used to evaluate the collection and transportation efficiency; operator information: the name, work number and other information of the operator responsible for the cleaning, used for responsibility tracing; cleaning results: the cleaning results of the storage equipment (such as whether it is clean, whether it is damaged, etc.), used to ensure hygiene standards.

[0065] Exemplarily, the range is divided according to different regional ranges of food waste collection and transportation, and the food waste collection and transportation information is divided into multiple parts. For the data of a single batch of food waste collection and transportation process, the element items of each data are arranged according to the arrival order of the food waste collection and transportation location nodes of a single batch, and the element values ​​are related information of food waste collection and transportation detection of each category. Then, the data information contained in each corresponding element value is mainly specific information of different collection and transportation links, such as food waste transportation vehicle collection and transportation information, cleaning staff cleaning process information and other data. The data information on the nodes of different collection and transportation links can be regarded as multi-type data, which is used to analyze the temporal correlation characteristics of subsequent path structure trends.

[0066] In this embodiment, by arranging the elements according to the arrival order of the location nodes of a single batch, 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, the collection and transportation routes can be optimized according to the arrival order to ensure that the vehicles travel along the shortest path. When the amount of garbage at a storage point suddenly increases, the collection and transportation routes can be dynamically adjusted according to the arrival order, and the collection and transportation tasks of the storage point can be prioritized to ensure that the garbage will not be stranded. By arranging the elements according to the arrival order of the location nodes of a single batch, the whole process of food and 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 a vehicle is found to have deviated from the scheduled route, or the amount of garbage in a garbage bin has increased abnormally, an alarm will be immediately issued to notify relevant personnel to check. By recording the arrival order, the person responsible for each link can be clarified to ensure standardized operation and prevent human errors or improper behavior. For example, the person responsible for a certain cleaning operation can be quickly found by scanning the code and taking photos to leave traces.

[0067] In one embodiment of the present application, determining 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.

[0068] The information change rate refers to the rate at which the relevant information of each location node (such as garbage volume, vehicle arrival time, stay time, etc.) changes over time during the collection and transportation of food waste. The information change rate reflects the dynamic changes of each location node in different time periods, helping to identify common collection and transportation patterns and abnormal situations.

[0069] Among them, the temporal correlation feature refers to the time series relationship between each location node, reflecting their relative order and time interval in the collection and transportation process. Through the comprehensive analysis of the information change rate and the number of location nodes, the temporal correlation feature of each location node can be determined, and common collection and transportation patterns and abnormal situations can be identified.

[0070] Exemplarily, by installing a weight sensor on the trash can, the change of the amount of garbage in each trash can is monitored in real time. For example, the weight of the trash can before a certain cleaning is recorded as 50 kg, and the weight after cleaning is 10 kg. It is calculated that the amount of garbage has decreased by 40 kg. The data of multiple cleanings are further analyzed to calculate the average rate of change of the amount of garbage in each trash can. The GPS positioning device on the transport vehicle is used to record the time of each arrival at a certain location node. For example, the time when a certain vehicle arrives at the three nodes A, B, and C in a week is recorded as 8:00, 8:15, and 8:30 respectively. The rate of change of each arrival time is calculated. If the time when the vehicle arrives at the A node is delayed to 8:10 on a certain day, the rate of change of the arrival time is calculated to be +10 minutes. The start time and end time of each cleaning operation are recorded by sensors or manual input. For example, the residence time of a cleaning operation at the A node is recorded as 15 minutes, and the residence time of the next cleaning operation is recorded as 20 minutes. The residence time is calculated to have increased by 5 minutes. The data of multiple cleanings are further analyzed to calculate the average rate of change of the residence time at each node. By scanning the code or manually entering the records, the operation frequency of each location node is counted. For example, the number of times node A was cleared in a certain week was recorded as 7 times, and the number of times it was cleared in the next week was 8 times. It is calculated that the operation frequency increased by 1 time / week. Further analysis of multiple weeks of data is performed to calculate the change rate of the operation frequency of each node. The number of location nodes involved in the collection and transportation is counted to ensure the integrity and representativeness of the data. For example, it is recorded that there are 10 location nodes (A, B, C, D, E, F, G, H, I, J) in a certain collection and transportation task. Further analysis of multiple collection and transportation data ensures that each collection and transportation task covers all necessary location nodes. Measure the time series correlation between different location nodes. 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 path. Further analysis of the arrival times of other nodes identifies more related nodes to form a stable collection and transportation pattern. Using clustering algorithms, nodes with similar information change rates are grouped together. For example, based on the garbage volume change rate, arrival time change rate, and residence time change rate, certain nodes are clustered together to form a stable collection and transportation path. The data of multiple collections are further analyzed to identify common collection and transportation patterns and abnormal situations. By comparing the normal time series correlation features, behaviors that deviate from the normal pattern are identified. For example, if the arrival time of a node is suddenly delayed, or the driving route of a vehicle changes, an alarm is issued to indicate that there may be an abnormal situation.

[0071] For example, the information change rate of the nodes is extracted in each link. Taking the filling rate of the kitchen waste bin of the kitchen waste collection and transportation as an example, the filling rate of the kitchen waste bin of all nodes in the collection and transportation process is extracted. The node Type of information change rate It is represented by the ratio of the difference between the node data at that location and the average data. The information change rate of the corresponding nodes in all links is obtained. The influence of the corresponding node information change rate on the path structure trend should be realized based on the previous and next time series correlation characteristics. That is, only when the adjacent nodes have multiple time series performances in the food waste collection and transportation link, they have structural trend characteristics. Then the correlation characteristics of each node in the link are analyzed. The representation of time series correlation characteristics can be: in, Indicates The temporal correlation characteristics of the position nodes, It means the The average rate of change of all types of information at the node position, It means the The node is The average change rate of all types of information of the next node on the data record, It represents the number of all position nodes.

[0072] in, Indicates The timing performance of a location node and its adjacent nodes in the food waste collection and transportation link. The larger the value, the greater the timing correlation feature, and it has a structural trend feature.

[0073] In this embodiment, by analyzing the information change rate and time series correlation characteristics, 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, the collection and transportation frequency can be optimized according to the garbage volume change rate to ensure that garbage can be effectively cleaned up every time; or the collection and transportation route can be adjusted according to the arrival time change rate to ensure that the vehicle travels along the shortest path. When the amount of garbage at a storage point suddenly increases, the collection and transportation frequency can be dynamically adjusted according to the information change rate, and the collection and transportation tasks of the storage point can be prioritized to ensure that the garbage will not be stranded. Through the analysis of the information change rate and time series correlation characteristics, the entire process of food and 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 the arrival time of a vehicle is suddenly delayed, or the amount of garbage in a garbage bin increases abnormally, an alarm will be immediately issued to notify relevant personnel to check. Through the analysis of the information change rate and time series correlation characteristics, the person in charge of each link can be clarified to ensure standardized operation and prevent human errors or improper behavior. For example, the person responsible for a certain cleaning operation can be quickly found by scanning the code and taking photos to leave traces.

[0074] In one embodiment of the present application, determining the path structure trend degree corresponding to each of the food 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.

[0075] Among them, the path subsequence refers to a sequence formed by arranging multiple position nodes in the same path structure trend change range in the process of food waste collection and transportation according to the order of arrival. 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 the preset time series correlation feature threshold, the position nodes whose time series correlation features are greater than the threshold are screened out, and these nodes are classified as within the same path structure trend change range. 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 constitute a path subsequence. For a larger collection and transportation area, the entire collection and transportation process can be divided into multiple path subsequences, each path subsequence corresponding to a specific collection and transportation path or time period. In this way, the path structure trend degree of each path subsequence can be analyzed in more detail.

[0076] The length of the path subsequence refers to the number of location nodes contained in the path subsequence. The length of the path subsequence reflects the complexity and coverage of the path subsequence, which is usually related to the scale and difficulty of the collection and transportation task.

[0077] Among them, path subsequence differences refer to the similarities and differences between different path subsequences. By comparing the length, node distribution, and time-series correlation characteristics of path subsequences, the differences between path subsequences can be identified to help optimize collection and transportation routes and resource scheduling.

[0078] For example, a smart property management platform manages a large community with multiple communities, each of which has multiple kitchen waste delivery points. According to the preset time series correlation feature threshold, the position nodes whose time series correlation features are greater than the threshold are screened out, and these nodes are classified into the same path structure trend change range. For example, it is found that the collection and transportation times of the three nodes A, B, and C are strongly correlated, so they are classified into the same path structure trend change range. 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 the three nodes A, B, and C in turn, so these three nodes constitute 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 tasks in the East District can be divided into two path subsequences: one is the path subsequence of the three nodes A, B, and C, and the other is the path subsequence of the three nodes D, E, and F. The number of position nodes contained 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 node changes, the path subsequence to which it belongs can be re-evaluated and adjusted accordingly. The length of the path subsequence can help optimize the collection and transportation route. For example, if the length of a path subsequence is too long, you can consider adding collection and transportation vehicles or adjusting the collection and transportation frequency to improve efficiency.

[0079] For example, for the traceability needs of the food waste collection and transportation process, the more obvious the temporal correlation characteristics are, the more obvious the impact of the abnormal information on the node on the nearby nodes is, so further analysis is needed from the perspective of the specific path structure impact. Since there are multiple node temporal correlation path information in the same type of collection and transportation process at the same link, it is regarded as a path subsequence. The structural trend characteristics are mainly related to the temporal correlation characteristics of the nodes in 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 path structure tendency of the abnormal information represented by its path subsequence. The expression of the path structure tendency degree can be: in, Indicates The degree of path structure tendency corresponding to each restaurant kitchen waste collection and transportation link; Indicates The average length of all path subsequences of the same type of collection and transportation operations in the food waste collection and transportation link; Indicates the length of the path subsequence within the range of path structure trend change; Indicates The mean value of the temporal correlation characteristics of all nodes in the food waste collection and transportation link; It is an exponential function in mathematical calculation.

[0080] in, It represents the difference between the length of the path subsequence within the range of path structure trend change and the average length of all path subsequences. The smaller the difference, the greater the degree of path structure trend.

[0081] In this embodiment, by taking the position nodes within the range of the path structure trend change as the path subsequence, and analyzing according to the length and difference of the path subsequence, 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 reduced. For example, the collection and transportation route can be optimized according to the length of the path subsequence to ensure that the vehicle travels along the shortest path; or the collection and transportation frequency can be adjusted according to the difference of the path subsequence to ensure that each collection and transportation can effectively clean up the garbage. When the amount of garbage at a 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 tasks of the storage point can be arranged first to ensure that the garbage will not be stranded. Through the length and difference analysis 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 the length of a path subsequence is found to increase suddenly, or the collection and transportation time of a node has changed significantly, an alarm will be immediately issued to notify relevant personnel to check. By analyzing the temporal correlation characteristics of the path subsequence, the person in charge of each link can be clarified to ensure standardized operation and prevent human errors or improper behavior. For example, you can quickly find the person responsible for a certain cleaning operation by scanning the code and taking photos.

[0082] In one embodiment of the present application, the requirement for tracing the food waste collection and transportation information corresponding to each food waste collection and transportation link is determined according to the path structure trend degree corresponding to each food waste collection and transportation link, including: According to the path structure tendency degree corresponding to each of the food waste collection and transportation links, the path structure tendency degree corresponding to the same type of collection and transportation operations at each of the location nodes is determined; 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.

[0083] 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.

[0084] 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.

[0085] For example, The demand for food waste collection and transportation information traceability corresponding to each location node can be expressed as: in, Indicates The demand for food waste collection and transportation information traceability corresponding to each location node; Indicates In the food waste collection and transportation link The degree of path structure tendency corresponding to the same type of collection and transportation operations at each location node; Indicates the path structure trend changes within the range of The length of the path subsequence corresponding to the same type of collection and transportation operations at the location nodes; represents positive correlation normalization; Represents the total number of food waste collection and transportation links.

[0086] in, , indicating the obvious situation of the path structure trend at the location node. The larger the value, the more obvious the path structure trend is, and the greater the demand for traceability of the food waste collection and transportation information corresponding to the location node.

[0087] In this embodiment, by analyzing the trend of the path structure of different types 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, the collection and transportation routes can be optimized according to the characteristics of the collection and transportation routes of household kitchen waste and commercial kitchen waste to ensure that vehicles travel along the shortest path; or the collection and transportation schedule can be adjusted according to the frequency of collection and transportation of different categories to ensure that each collection and transportation can effectively clean up the garbage. When the amount of garbage at a storage point suddenly increases, the collection and transportation route can be dynamically adjusted according to the trend of the path structure of different types of collection and transportation operations, and the collection and transportation tasks of the storage point can be prioritized to ensure that the garbage will not be stranded.

[0088] In one embodiment of the present application, the scheduling of 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 of the food waste collection and transportation links 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.

[0089] Among them, density clustering is a clustering algorithm based on data point density. It identifies data points in high-density areas and classifies these data points into the same category. Unlike traditional clustering algorithms, density clustering does not require the number of clusters to be specified in advance, can automatically discover clusters of any shape, and has good robustness to noise points. In the analysis of the traceability requirements of food waste collection and transportation information, density clustering can help identify location nodes with similar characteristics and form multiple clusters. First, the food waste collection and transportation information traceability requirements of each location node in each food waste collection and transportation link are obtained, including the degree of path structure trend, time series correlation characteristics, information change rate, etc. According to the characteristics of the data, the parameters of density clustering are set, such as the minimum number of samples and the radius. These parameters determine which points are considered to be core points and the size of the cluster. All location nodes are clustered using the density clustering algorithm to identify multiple clusters. Each cluster represents a group of location nodes with similar characteristics, usually with similar collection and transportation modes or abnormal situations.

[0090] Among them, a cluster refers to a group of location nodes with similar characteristics identified by a density clustering algorithm. The nodes in each cluster show consistent regularity in terms of geographical location, collection and transportation frequency, time series, etc., forming a stable collection and transportation pattern. By analyzing the clusters, we can better understand the relationship between nodes in different locations and optimize the scheduling of collection and transportation resources.

[0091] Among them, the location nodes in the same cluster are taken as the dispatch traceability scope of the same level to obtain the multi-level dispatch traceability scope. By managing the dispatch traceability scopes of different levels, the allocation of collection and transportation resources can be controlled more finely to ensure that the responsibilities of each link are clear and the operation is standardized. According to the characteristics of the cluster, all location nodes are divided into multiple levels. Each level represents a specific dispatch traceability scope, which usually contains a group of location nodes with similar characteristics. For example, nodes can be divided into three levels of high priority, medium priority and low priority according to the characteristics such as the degree of path structure tendency and the frequency of collection and transportation. Based on the multi-level dispatch traceability scope, the collection and transportation vehicles and personnel are arranged reasonably. For example, for high-priority nodes, the collection and transportation tasks can be arranged first to ensure that the garbage is cleaned up in time; while for low-priority nodes, the collection and transportation frequency can be appropriately adjusted to reduce unnecessary waste of resources. With the continuous addition of new data, the multi-level dispatch traceability scope can be dynamically adjusted. For example, when the collection and transportation mode of a node changes, the dispatch traceability scope to which it belongs can be re-evaluated and adjusted accordingly.

[0092] For example, a smart property management platform manages a large community with multiple communities, each of which has multiple food waste delivery points. The food waste collection and transportation information traceability requirements of each location node in each food waste collection and transportation link are obtained, including the degree of path structure trend, time series correlation characteristics, information change rate, etc. For example, the garbage volume change rate, arrival time change rate, and residence time change rate of each node are 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, which means that there must be at least 5 nodes within a range of 0.5 kilometers to form a cluster. All location nodes are clustered and multiple clusters are identified. For example, it is found that the three nodes A, B, and C form a cluster, the three nodes D, E, and F form another cluster, and the three nodes G, H, and I form a third cluster. According to the characteristics of the cluster, all location nodes are divided into multiple levels. For example, it is found that the collection and transportation frequency of nodes A, B, and C is high, and the path structure tendency is high, so they are classified as high priority; the collection and transportation frequency of nodes D, E, and F is moderate, and the path structure tendency is general, so they are classified as medium priority; the collection and transportation frequency of nodes G, H, and I is low, and the path structure tendency is low, so they are classified as low priority. Based on the multi-level scheduling traceability scope, the collection and transportation vehicles and personnel are arranged reasonably. For example, for the three nodes A, B, and C with high priority, the collection and transportation tasks are arranged first to ensure that the garbage is cleaned up in time; for the three nodes D, E, and F with medium priority, the collection and transportation frequency is appropriately adjusted to ensure that each collection and transportation can effectively clean up the garbage; for the three nodes G, H, and I with low priority, the collection and transportation frequency can be appropriately reduced to reduce unnecessary waste of resources. With the continuous addition of new data, the multi-level scheduling traceability scope can be dynamically adjusted. For example, when the collection and transportation mode of a node changes, the scheduling traceability scope to which it belongs can be re-evaluated and adjusted accordingly. According to the multi-level scheduling traceability scope, the person in charge of each location node is clarified to ensure standardized operation. For example, you can quickly find the person responsible for a certain removal operation by scanning the code and taking photos. If the amount of garbage at a node increases abnormally, you can quickly locate the operator responsible for the node and trace the responsibility. By comparing normal clusters, you can identify behaviors that deviate from the normal pattern. For example, if the collection and transportation time of a node in a cluster is suddenly extended, or the driving route of a vehicle changes, an alarm will be issued to indicate that there may be an abnormal situation. Spare vehicles or personnel can be dispatched immediately to deal with the problem to ensure that it is resolved in a timely manner. According to the multi-level scheduling traceability scope, 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 overall efficiency.

[0093] In one embodiment of the present application, the scheduling of the food waste collection and transportation resources of the location nodes in the food 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, the food waste transport vehicles and food waste removal operators are dispatched to the location node to conduct abnormality investigation and abnormality processing.

[0094] Among them, abnormality detection refers to identifying behaviors or abnormal situations that deviate from the normal pattern and determining their causes by analyzing the food waste collection and transportation information. Abnormality handling refers to taking corresponding measures after discovering the abnormality to ensure that the problem is solved in a timely manner and normal operations are restored. Abnormality detection and handling are important means to ensure the smooth progress of the food waste collection and transportation process, and can effectively improve reliability and management level.

[0095] Among them, the highest level of dispatch traceability scope is dispatched and processed, with the purpose of focusing on the highest level (i.e., the highest priority) dispatch traceability scope in the multi-level dispatch traceability scope. Usually, the highest level of dispatch traceability scope includes the most urgent or important location nodes, and the abnormal conditions of these nodes may have a greater impact on the entire collection and transportation process. Therefore, priority will be given to dispatching food waste transport vehicles and transportation operators to these nodes to conduct abnormal investigation and processing to ensure that the problems are resolved in a timely manner.

[0096] For example, according to the adjusted traceability information, the resource scheduling of food waste collection and transportation at the node structure trend position is first monitored in real time by sensors, such as the filling degree and temperature of the food waste bin, and an alarm is automatically generated when overflow or abnormal conditions are detected. After receiving the alarm, the dispatch center and relevant staff will be notified, and the urgency of the problem will be assessed to determine whether resources need to be mobilized immediately. The dynamic resource allocation within the divided traceability range is used to optimize the dispatch of food waste collection and transportation vehicles and personnel, and the nearest food waste collection and transportation vehicles and an appropriate number of staff are dispatched to handle the problem first. After the on-site staff arrives, they will quickly clean up the food waste and check the cause of the abnormality, and take necessary measures to solve the problem. If a safety hazard is found, the safety emergency procedure is initiated to ensure on-site safety. Through this process, the property management company can efficiently respond to abnormal situations and ensure the environmental sanitation and safety of the community.

[0097] In this embodiment, by scheduling the highest level of scheduling and tracing scope, the most urgent or important location nodes can be prioritized to ensure that the problem is solved in a timely manner. For example, according to the priority evaluation results, spare vehicles and transportation personnel can be dispatched to the highest level nodes to ensure that the garbage will not be stranded. When the amount of garbage at a storage point suddenly increases or the collection and transportation path changes, the collection and transportation plan can be dynamically adjusted according to the results of abnormal investigation and processing to ensure that each collection and transportation can effectively clean up the garbage. By scheduling the highest level of scheduling and tracing scope, the entire 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 the collection and transportation time of a node is suddenly extended, or the driving route of a vehicle has changed, an alarm will be immediately issued to notify relevant personnel to check. By recording the results of abnormal investigation and processing, the person responsible for each link can be clarified, the operation can be standardized, and human errors or improper behavior can be prevented. For example, by scanning the code and taking pictures to leave traces, the person responsible for a certain transportation operation can be quickly found and responsibility can be traced.

[0098] Figure 4 This is a schematic diagram of a device for tracing kitchen waste collection and transportation information of a smart property management platform provided by an embodiment of the present invention. The device can be applied to Figure 1 The device may also be applicable to other exemplary implementation environments and specifically configured in other devices, and this embodiment does not limit the implementation environment to which the device is applicable.

[0099] like Figure 4 As shown, the exemplary food waste collection and transportation information traceability device of the smart property management platform includes: The information acquisition module 401 is used to acquire the food waste collection and transportation information corresponding to multiple food waste collection and transportation links; A path structure trend analysis module 402 is used to analyze the path structure trends of multiple 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; The scheduling and processing module 403 is used to schedule and process the food waste collection and transportation resources of the location nodes in the food waste collection and transportation links based on the pre-installed smart property management platform and according to the food waste collection and transportation information traceability requirements corresponding to each of the food waste collection and transportation links.

[0100] 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.

[0101] 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.

[0102] 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.

[0103] 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.

[0104] like Figure 5As shown, the computer system 500 includes a central processing unit (CPU) 501, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 502 or the program loaded from the storage part 508 to the random access memory (RAM) 503, such as executing the method described in the above embodiment. In the RAM 503, various programs and data required for system operation are also stored. The CPU 501, the ROM 502 and the RAM 503 are connected to each other through the bus 504. The input / output (I / O) interface 505 is also connected to the bus 504.

[0105] 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 a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker; 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 therefrom is installed into the storage section 508 as needed.

[0106] In particular, 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, which 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 through a communication part 509, and / or installed from a 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.

[0107] It should be noted that the computer-readable medium shown in the embodiment of the present application may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media 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 disk 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 part of a carrier, which carries a computer-readable computer program. This propagated data signal may take a variety of forms, including but not limited to an electromagnetic signal, an optical signal, 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 may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. A computer program contained on a computer-readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0108] The flowcharts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the apparatus, methods and computer program products according to various embodiments of the present application. Among them, each box in the flowchart or block diagram can represent a module, a program segment, or a part of the code, and the above-mentioned module, program segment, or a part of the 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 box can also occur in an order different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart, can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0109] The units involved in the embodiments described in this application may be implemented by software or hardware, and the units described may also be set in a processor. The names of these units do not, in some cases, constitute limitations on the units themselves.

[0110] Another aspect of the present application further provides a computer-readable storage medium storing a plurality of instructions suitable for a processor to load to execute the steps in any method for tracing kitchen waste collection and transportation information of a smart property management platform provided in the embodiments of the present application. The computer-readable storage medium may be included in the electronic device described in the above embodiments, or may exist independently without being assembled into the electronic device.

[0111] It should be noted that the sequence of the above embodiments of the present invention is for description only and does not represent the advantages and disadvantages 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.

[0112] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and 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, the food waste collection and transportation resources of the location nodes in the food waste collection and transportation links are scheduled and processed according to the food waste collection and transportation information traceability requirements corresponding to each of the food waste collection and transportation links.

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: 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, including: 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.

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: 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.

5. The method for tracing kitchen waste collection and transportation information of a smart property management platform as claimed in claim 4, 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.

6. The method for tracing kitchen waste collection and transportation information of a smart property management platform as claimed in claim 4, 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.

7. The method for tracing kitchen waste collection and transportation information of a smart property management platform as claimed in claim 4, 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.

8. The method for tracing kitchen waste collection and transportation information of a smart property management platform as claimed in claim 4, 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.

9. The method for tracing kitchen waste collection and transportation information of a smart property management platform as claimed in claim 8, characterized in that: 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.

10. The method for tracing kitchen waste collection and transportation information of a smart property management platform according to claim 9, 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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