Property intelligent work order scheduling service management method and system, and medium
By classifying, mapping, and building a network of historical work order data from the property management center, and combining real-time work order requests with current resource status, accurate and intelligent matching and scheduling of property work orders has been achieved. This has solved the problems of delayed response and inaccurate resource matching in property services, and improved service efficiency and user satisfaction.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- SHENZHEN LONGGUANGYUNZHONG INTELLIGENT TECH CO LTD
- Filing Date
- 2026-03-23
- Publication Date
- 2026-07-10
AI Technical Summary
Existing technologies suffer from delayed response times to property management work orders, inaccurate resource matching, and difficulty in coordinating and optimizing multi-dimensional scheduling factors, resulting in low efficiency of property management services and low user satisfaction.
By collecting historical work order data from the property center and classifying and mapping it, a work order type-execution resource mapping and worker location distribution network are established. Real-time work order requests are received and intelligently matched. Combined with the current worker status and resource warehouse network, a scheduling plan is generated.
It has enabled precise and intelligent matching and scheduling of property work orders, improved resource utilization efficiency, shortened service response time, and enhanced property service quality and user satisfaction.
Smart Images
Figure CN122366922A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the technical field of property service management, specifically to a method, system, and medium for intelligent property work order scheduling service management. Background Technology
[0002] Work order scheduling and resource allocation are crucial to the efficiency and quality of property management services. With the expansion of property management scope and the diversification of service types, traditional property work order processing has gradually revealed problems such as low scheduling efficiency, uneven resource allocation, and untimely response. This is especially true when facing sudden and diverse work order requests, where it is difficult to quickly match suitable workers and material resources. Currently, most property service centers rely on the experience of management personnel for decision-making, lacking systematic analysis of historical data and accurate real-time dynamic understanding. This easily leads to uneven worker task allocation, unreasonable resource allocation, and increased response delays. Furthermore, due to the diverse types of property work orders, such as maintenance, cleaning, security, and customer service, different types of work orders have different requirements for worker skills, tools, and material resources. Existing methods struggle to achieve accurate matching between work order types and execution resources. In addition, current property work order scheduling does not fully consider the diversity of work order types and their specific resource requirements, and lacks accurate analysis and matching of the dynamic distribution of worker locations and resource warehouse networks, thus affecting the overall service efficiency and user satisfaction of the property.
[0003] Therefore, current technologies suffer from technical problems such as delayed response to property work orders, inaccurate resource matching, and difficulty in coordinating and optimizing multi-dimensional scheduling factors. Summary of the Invention
[0004] This application provides a property management intelligent work order scheduling service management method, system, and medium, which solves the technical problems of delayed property work order scheduling response, inaccurate resource matching, and difficulty in coordinating and optimizing multi-dimensional scheduling factors in the existing technology. It achieves the technical effect of realizing accurate and intelligent matching and scheduling of property work orders, improving resource utilization efficiency, shortening service response time, and improving property service quality and user satisfaction.
[0005] This application provides a method for managing intelligent work order scheduling services in property management. The method includes: collecting historical work order data from the property management center, classifying and mapping work orders, and establishing a work order type-execution resource mapping; establishing an execution resource warehouse distribution network and a worker location distribution network for various work order types in the property management center; receiving real-time work order requests from the property management center and parsing them to obtain the target work order type and work order request location; matching a target execution resource set in the work order type-execution resource mapping based on the target work order type; matching the target worker location distribution network of the corresponding type with the target work order type, and reading the current worker scheduling status; using the target execution resource set and the work order request location as fixed conditions, and combining the execution resource warehouse distribution network to match the workers and resource warehouses of the real-time work order requests, and using the matching results for scheduling management.
[0006] In one possible implementation, the property intelligent work order scheduling service management method further performs the following processing: determining the idle status and current location of each target worker based on the current worker scheduling status, and filtering out a set of candidate workers who can respond to work order requests; reading the inventory status of each resource warehouse in the execution resource warehouse distribution network of the target execution resource set, and determining a set of candidate resource warehouses; and performing joint optimization matching based on the set of candidate workers and the set of candidate resource warehouses, selecting the optimal worker and the corresponding optimal resource warehouse, and generating a matching result.
[0007] In one possible implementation, the property intelligent work order scheduling service management method further performs the following processing: for each candidate worker in the candidate worker set, taking the location of each candidate worker as the starting point, taking any candidate resource warehouse location in the candidate resource warehouse set as the intermediate point, and taking the work order request location as the endpoint, the map navigation module is invoked to traverse and calculate to obtain the optimal navigation route corresponding to each candidate worker; the optimal navigation routes corresponding to each candidate worker are compared, and the optimal worker and corresponding optimal resource warehouse corresponding to the optimal navigation route with the shortest navigation distance are selected to generate the matching result.
[0008] In one possible implementation, the property intelligent work order scheduling service management method further performs the following processing: for each historical work order in the historical property work order data, extract the historical work order type and the set of work materials; classify the historical work order types to generate multiple work order types; sequentially merge the sets of work materials corresponding to all historical work orders corresponding to the multiple work order types to generate an execution resource set, and associate and map it with the multiple work order types to generate the work order type-execution resource mapping.
[0009] In one possible implementation, the property intelligent work order scheduling service management method further performs the following processing: if any historical work order data contains multiple work order types, then the work order is segmented before being classified.
[0010] In one possible implementation, the property intelligent work order scheduling service management method further performs the following processing: if the target work order type is at least two target types, based on the worker location distribution network of various work order types, identify mixed workers with functional attributes of at least two target types, and construct a mixed worker distribution network; based on the mixed worker scheduling status corresponding to the mixed worker distribution network, using the target execution resource set and the work order request location as fixed conditions, and combining the execution resource warehouse distribution network, perform mixed worker and resource warehouse matching; if matching fails, then segment the at least two target types and match them sequentially.
[0011] In one possible implementation, the property intelligent work order scheduling service management method further performs the following processing: the real-time work order request is created through the client's self-service channel, the Internet of Things automatic monitoring module, and / or manually.
[0012] In one possible implementation, the property intelligent work order scheduling service management method further performs the following processing: extracting historical worker scheduling trajectories from historical property work order data; identifying path loss caused by resource warehouses in high-density areas with a path density greater than a preset trajectory density based on historical worker scheduling trajectories; if the path loss is greater than a preset threshold, optimizing the distribution of resource warehouses in the high-density areas and pushing resource warehouse optimization suggestions to the property center.
[0013] This application also provides a property management intelligent work order scheduling service management system, the system comprising: a property work order data acquisition module, used to collect historical property work order data from the property center, perform work order classification mapping, and establish a work order type-execution resource mapping; a distribution network establishment module, used to establish an execution resource warehouse distribution network and a worker location distribution network for various work order types in the property center; a target resource matching module, used to receive real-time work order requests from the property center and parse to obtain the target work order type and work order request location, and match a target execution resource set in the work order type-execution resource mapping based on the target work order type; and a matching scheduling management module, used to match the target worker location distribution network of the corresponding type with the target work order type, read the current worker scheduling status, and use the target execution resource set and the work order request location as fixed conditions, combined with the execution resource warehouse distribution network, to perform worker and resource warehouse matching for the real-time work order request, and perform scheduling management based on the matching results.
[0014] This application also provides a computer-readable storage medium, including: a computer program stored thereon, which, when executed by a processor, implements a property intelligent work order scheduling service management method.
[0015] This application proposes a property management intelligent work order scheduling service management method, system, and medium. By integrating historical work order data for classification and mapping, it constructs a work order type-execution resource mapping, a resource warehouse distribution network, and a worker location distribution network. It receives real-time work order requests from the property center, parses and obtains the target work order type and request location, and matches the target execution resource set with the corresponding worker distribution network. Combining the current worker scheduling status, work order location, and resource warehouse network, it dynamically matches workers with resource warehouses to generate a scheduling plan. This solves the technical problems of delayed property work order scheduling response, inaccurate resource matching, and difficulty in coordinating and optimizing multi-dimensional scheduling factors in existing technologies. It achieves the technical effects of accurate and intelligent matching and scheduling of property work orders, improving resource utilization efficiency, shortening service response time, and enhancing property service quality and user satisfaction. Attached Figure Description
[0016] To more clearly illustrate the technical solutions of the embodiments of this disclosure, the accompanying drawings of the embodiments of this disclosure will be briefly described below. Flowcharts are used in this application to illustrate the operations performed by the system according to the embodiments of this application. It should be understood that the preceding or following operations are not necessarily performed precisely in sequence. Instead, various steps can be processed in reverse order or simultaneously as needed. Furthermore, other operations can be added to these processes, or one or more steps can be removed from these processes.
[0017] Figure 1 This is a schematic diagram of the property intelligent work order scheduling service management method provided in the embodiments of this application.
[0018] Figure 2 This is a schematic diagram of the structure of the property intelligent work order dispatch service management system provided in the embodiments of this application.
[0019] Explanation of reference numerals in the attached diagram: Property work order data acquisition module 10, distributed network establishment module 20, target resource matching module 30, and matching scheduling management module 40. Detailed Implementation
[0020] To further illustrate the technical means and effects adopted by the present invention in order to achieve the intended purpose, the following detailed description is provided in conjunction with the accompanying drawings and preferred embodiments, based on the specific implementation methods, structures, features and effects of the present invention.
[0021] This application provides a method for managing intelligent work order scheduling services in property management, such as... Figure 1 As shown, the method includes: Step S100: Collect historical property work order data from the property center, perform work order classification mapping, and establish work order type-execution resource mapping.
[0022] Step S100 further includes step S110, extracting the historical work order type and work material set for each historical work order in the historical property work order data; step S120, classifying based on the historical work order type to generate multiple work order types; step S130, sequentially merging the work material sets corresponding to all historical work orders corresponding to the multiple work order types to generate an execution resource set, and associating and mapping it with the multiple work order types to generate the work order type-execution resource mapping.
[0023] Preferably, historical property work order data from the property management center is collected, including at least the work order description, such as "The corridor light on the 7th floor of Unit 3, Building 5 in Area A is not working," "Water pipe leak in room 2304 of Unit 2, Building 1 in Area C," and "Safety indicator light malfunction on the 8th floor of Building 6 in Area D," the historical work order type, and the actual work materials used. For each historical work order in the historical property work order data, the historical work order type is automatically identified and extracted, that is, the category identifier marked by the work order in the business, such as "circuit repair," "pipe dredging," "glass replacement," etc., and the work material set, that is, a list of all materials and tools actually received or used when executing the historical work order task, such as energy-saving light bulbs, screwdrivers, ladders, tape, and test pens.
[0024] Preferably, based on the extracted historical work order types, all historical work order records are clustered and grouped to generate multiple non-repeating work order types. For example, all historical work order records marked as "circuit repair" or "lighting failure" are classified into the electrical work type. Then, the sets of work materials corresponding to all historical work order records for multiple work order types are merged in turn, and all materials used to process this type of property work order are summarized to determine the execution resource set, that is, the standardized material list for processing this type of property work order. This set is then associated and mapped with multiple work order types to generate a structured work order type-execution resource mapping. For example, the work order type "elevator routine maintenance" is associated with the execution resource set "lubricating oil", "screwdriver set", "multimeter", and "cleaning cloth", and the work order type "entrance door lock replacement" is associated with the execution resource set "new lock cylinder" and "screwdriver".
[0025] Furthermore, step S100 also includes that if any historical work order data contains multiple work order types, the work order will be segmented before being classified.
[0026] Preferably, when traversing historical property work order data, if the historical work order type of a certain data contains multiple type identifiers, such as the property work order type record being "Repair | Cleaning" or "Electrical Repair, Wall Repair", then the historical work order data is split into multiple new work order records according to the preset separator. Then, the new work order records are classified and the work order type and execution resource set are mapped to determine the work order type-execution resource mapping, thereby achieving more accurate resource summarization and ensuring that materials are accurately classified under the correct work order type.
[0027] Step S200: Establish the execution resource warehouse distribution network and the worker location distribution network for various work order types of the property center.
[0028] Preferably, the execution resource warehouse refers to a warehouse, storage point, or distribution center within the property's jurisdiction used to store physical resources required for work order execution, such as tools, spare parts, and consumables. A corresponding digital node is created for each execution resource warehouse, recording its unique identifier, geographical coordinates, resource type, and real-time inventory quantity. Then, a network topology relationship is established between nodes; that is, based on geographical location or logistics path, the connection relationship between nodes is defined, or the distance and path cost matrix between nodes is calculated to determine the spatial relationship between execution resource warehouses or between an execution resource warehouse and the work order location. Simultaneously, a worker location distribution network is established for various work order types. This means a separate dynamic network is created for each work order type, and all workers of that type are abstracted as nodes in the network. Specifically, workers are categorized into the corresponding work order type network based on their skills and qualifications. Each worker node in the network records its unique identifier, real-time geographical location information, current scheduling status, skill level, and work efficiency. The current scheduling status may be idle, busy, online, or offline. Furthermore, the worker location distribution network is highly dynamic, with worker locations and statuses changing in real time to reflect the latest situation.
[0029] Furthermore, step S200 also includes step S210, extracting historical worker scheduling trajectories from historical property work order data; step S220, identifying path loss caused by resource warehouses in high-density areas with a path density greater than a preset trajectory density based on historical worker scheduling trajectories; if the path loss is greater than a preset threshold, optimizing the distribution of resource warehouses in the high-density areas and pushing resource warehouse optimization suggestions to the property center.
[0030] Preferably, the spatiotemporal path records of each property work order task execution are extracted from historical property work order data, i.e., historical worker scheduling trajectories, including worker ID, work order sequence, and coordinates and time information of each key point, such as departure location, resource warehouse material pick-up point, work order execution point, and return / end point. All historical worker scheduling trajectories are spatially overlaid and analyzed. Through grid density statistics or heat map analysis, high-density areas with a density greater than the preset trajectory are identified, i.e., areas where worker activity frequency is abnormally higher than the average level. These may be buildings, parks, or business-concentrated areas with frequent repair requests. Then, the rationality of each trajectory in the high-density area is analyzed to determine the path loss caused by the resource warehouse. This includes checking whether the worker's scheduling trajectory shows a special trip to a distant resource warehouse to pick up materials when executing work orders in this area. The actual material pick-up path length is compared with the theoretical optimal path length, and the difference is calculated to determine unnecessary inefficient travel segments as the path loss for this task execution.
[0031] Preferably, a preset threshold is set based on the total mileage and total time indicators. The path loss is compared with the preset threshold. If the path loss is greater than the preset threshold, it is determined that the current resource warehouse layout causes low operational efficiency in the area. Then, the resource warehouse distribution is optimized in the high-density area. That is, with the goal of minimizing the total expected path loss in the high-density area, the resource warehouse optimization suggestions for adding micro resource warehouses and adjusting the structure of existing resource warehouses in the area are calculated in combination with business constraints. This may include a high-density area map, path loss data quantification, recommended optimization schemes, and expected efficiency improvement assessment. Finally, the resource warehouse optimization suggestions are pushed to the property center, thereby reducing the response time and scheduling cost of all future work orders.
[0032] Step S300: Receive the real-time work order request from the property center and parse it to obtain the target work order type and work order request location. Based on the target work order type, match the target execution resource set in the work order type-execution resource mapping.
[0033] Step S300 further includes the real-time work order request being created through a client's self-service channel, an IoT automatic monitoring module, and / or manually.
[0034] Preferably, the system receives real-time work order requests from the property management center. These requests are created through client-side self-service channels, IoT automatic monitoring modules, and / or manually. Specifically, creating real-time work order requests through client-side self-service channels means that property service users proactively submit service requests such as repairs, complaints, and appointments via self-service platforms such as mobile applications, WeChat official accounts, mini-programs, and web pages. Users fill in or select the work order type, problem description, and address information on the front-end page, which is then converted into a real-time work order request via API. Creating real-time work order requests through IoT automatic monitoring modules means that various sensors and smart devices installed on property facilities such as power distribution rooms, elevators, fire protection systems, and water supply networks automatically generate and report work orders when abnormal data is detected or an alarm is triggered. The IoT platform receives device alarm signals and categorizes them into structured real-time work order requests. Manually creating real-time work order requests means that property customer service personnel, inspection personnel, or management personnel discover and fill out work orders in the back-end management system based on phone calls or on-site inspections, inputting the type, location, urgency level, and a brief description, and submitting them. These requests also enter the dispatch queue as real-time work order requests.
[0035] Preferably, the form data of the real-time work order request is read, and the work order type and location fields are extracted from it through natural language processing to obtain the target work order type and work order request location. Then, the target work order type is used as the query key to search and match in the work order type-execution resource mapping to determine the target execution resource set, that is, the standardized list of materials required to complete this type of property work order determined based on historical work order data. For example, if the target work order type is "elevator entrapment rescue", then the corresponding target execution resources are matched in the work order type-execution resource mapping, including "triangular key", "safety warning sign", "intercom equipment" and "emergency lighting".
[0036] Step S400: Match the target worker location distribution network of the corresponding type with the target work order type, and read the current worker scheduling status. Using the target execution resource set and the work order request location as fixed conditions, match the workers and resource warehouses of the real-time work order request with the execution resource warehouse distribution network, and use the matching results for scheduling management.
[0037] Step S400 further includes step S410, determining the idle status and current location of each target worker based on the current worker scheduling status, and filtering out a set of candidate workers who can respond to work order requests; step S420, reading the inventory status of each resource warehouse in the execution resource warehouse distribution network of the target execution resource set, and determining a set of candidate resource warehouses; step S430, performing joint optimization matching based on the set of candidate workers and the set of candidate resource warehouses, selecting the optimal worker and the corresponding optimal resource warehouse, and generating a matching result.
[0038] Preferably, the target work order type is used as the query key to search and match in multiple worker location distribution networks pre-established according to the work order type to obtain the target worker location distribution network. For example, if the work order type is "circuit repair", it will match the "electrician worker location distribution network", and if it is "pipe dredging", it will match the "plumber worker location distribution network". Then, the worker scheduling status in the current target worker location distribution network is read.
[0039] Preferably, the target execution resource set and the work order request location are used as fixed conditions. Real-time work order request worker and resource warehouse matching is performed using the execution resource warehouse distribution network. This includes determining the idle status and current location of each target worker based on the current worker scheduling status, filtering out workers with an "idle" or "available" status, and forming a candidate worker set that can respond to work order requests. This set includes all workers with matching skills and available time status. The target execution resource set is read and used as a query condition. Each resource warehouse in the execution resource warehouse distribution network is traversed, and the real-time inventory status of each resource warehouse is checked to determine whether it can simultaneously meet the required type and quantity of materials, i.e., ensuring that the inventory is at least greater than the demand. Resource warehouses that fully meet the requirements are retained, thus determining the candidate resource warehouse set.
[0040] Preferably, based on the candidate worker set and candidate resource warehouse set, a joint optimization matching is performed in conjunction with a fixed work order request location. That is, each pairing combination of candidate worker and candidate resource warehouse is traversed, the estimated total path time or distance from the worker's current location to the resource warehouse to collect all materials and then to the work order request location to complete the property service is calculated, and the complete path cost is determined. Then, the pairing combination with the lowest complete path cost is selected, and the worker and resource warehouse included in the pairing combination are determined as the optimal worker and the corresponding optimal resource warehouse. The final matching result is then output. Finally, scheduling management is performed based on the matching result. That is, information including a detailed problem description, a list of required materials, and the location of the specified resource warehouse is sent to the optimal worker via APP push or smart terminal. At the same time, a material preparation instruction is issued to the optimal resource warehouse, and a complete navigation route from the current location → specified resource warehouse → work order location is generated for the worker and pushed to the worker's mobile terminal to ensure efficient completion of property work order tasks, thereby improving resource utilization efficiency, shortening service response time, and improving property service quality and user satisfaction.
[0041] Furthermore, step S430 also includes, for each candidate worker in the candidate worker set, taking the location of each candidate worker as the starting point, taking any candidate resource warehouse location in the candidate resource warehouse set as the intermediate point, and taking the work order request location as the endpoint, calling the map navigation module to traverse and calculate to obtain the optimal navigation route corresponding to each candidate worker; comparing the optimal navigation routes corresponding to each candidate worker, filtering the optimal worker and corresponding optimal resource warehouse corresponding to the optimal navigation route with the shortest navigation distance, and generating the matching result.
[0042] Preferably, local optimization calculations are performed for each candidate worker in the candidate worker set. That is, taking the location of each candidate worker as the starting point, any candidate resource warehouse location in the candidate resource warehouse set as the intermediate point, and the work order request location as the destination, each worker is simulated to start from their current location, go to a certain resource warehouse to collect all materials, and then rush to the work order location. For each resource warehouse set, the map navigation module is called to calculate the navigation distance or estimated time of the complete route, thereby obtaining the optimal navigation route for each candidate worker. Then, the optimal navigation routes for each candidate worker are compared, and the one with the shortest navigation distance is selected as the optimal navigation route. The corresponding optimal worker and corresponding optimal resource warehouse are obtained, and the final matching result is generated to ensure improved resource utilization efficiency and shortened service response time.
[0043] Furthermore, step S400 also includes: if the target work order type is at least two target types, reconstructing and identifying mixed workers with functional attributes of at least two target types based on the worker location distribution network of various work order types, and constructing a mixed worker distribution network; based on the mixed worker scheduling status corresponding to the mixed worker distribution network, using the target execution resource set and the work order request location as fixed conditions, and combining the execution resource warehouse distribution network to match mixed workers and resource warehouses; if the matching fails, then segmenting the at least two target types and matching them sequentially.
[0044] Preferably, if the target work order type is determined to contain at least two target types, the worker location distribution network corresponding to each work order type is retrieved and reconstructed to identify the workers that appear simultaneously in multiple worker location distribution networks, i.e., mixed workers with functional attributes of at least two target types. Then, mixed workers with multiple skills are extracted to form a new dynamic network to obtain a mixed worker distribution network, in which each node has all the skills required for the current composite work order. Next, the system reads the real-time scheduling status of all corresponding mixed workers in the mixed worker distribution network. Simultaneously, based on the type of the composite work order, it merges the total target execution resource set required to process all tasks from the work order type-execution resource mapping. Then, using the target execution resource set and the work order request location as fixed conditions, it performs mixed worker and resource warehouse matching in conjunction with the execution resource warehouse distribution network. This involves performing joint optimization matching for candidate mixed workers and calculating the optimal path from worker to execution resource warehouse to work order location, determining the optimal mixed worker and the optimal resource warehouse to supply all materials to them, and then directly generating scheduling instructions to execute the property work order task. If there are no suitable idle mixed workers in the mixed worker distribution network, or if all the necessary materials cannot be obtained from a single resource warehouse, resulting in the inability to determine a feasible complete path from worker to resource warehouse to work order location for any mixed worker, it indicates a matching failure. In this case, at least two target types are segmented and matched sequentially, i.e., the composite work order is split into multiple independent single-type work orders and matched according to a preset urgency priority. Finally, multiple workers are scheduled to execute the property task, thereby ensuring an intelligent balance between resource scheduling efficiency and scheduling feasibility.
[0045] In the above text, refer to Figure 1 The property intelligent work order scheduling service management method according to embodiments of the present invention is described in detail. Next, reference will be made to... Figure 2 This invention describes a property intelligent work order scheduling service management system according to an embodiment of the present invention.
[0046] The property intelligent work order scheduling service management system according to embodiments of the present invention addresses the technical problems in existing technologies, such as delayed response to property work order scheduling, inaccurate resource matching, and difficulty in coordinating and optimizing multi-dimensional scheduling factors. It achieves the technical effects of realizing accurate and intelligent matching and scheduling of property work orders, improving resource utilization efficiency, shortening service response time, and enhancing property service quality and user satisfaction. Figure 2 As shown, the property intelligent work order dispatch service management system includes: a property work order data acquisition module 10, a distributed network establishment module 20, a target resource matching module 30, and a matching dispatch management module 40.
[0047] The property work order data acquisition module 10 is used to collect historical property work order data from the property center, perform work order classification mapping, and establish a work order type-execution resource mapping. The distribution network establishment module 20 is used to establish the execution resource warehouse distribution network of the property center and the worker location distribution network for various work order types. The target resource matching module 30 is used to receive real-time work order requests from the property center, parse and obtain the target work order type and work order request location, and match the target execution resource set in the work order type-execution resource mapping based on the target work order type. The matching and scheduling management module 40 is used to match the target worker location distribution network of the corresponding type with the target work order type, read the current worker scheduling status, and use the target execution resource set and the work order request location as fixed conditions to match the workers and resource warehouses of the real-time work order requests in combination with the execution resource warehouse distribution network, and perform scheduling management based on the matching results.
[0048] The specific configuration of the matching and scheduling management module 40 will be described in detail below. The matching and scheduling management module 40 further includes: determining the idle status and current location of each target worker based on the current worker scheduling status, and filtering out a set of candidate workers who can respond to work order requests; reading the inventory status of each resource warehouse in the execution resource warehouse distribution network of the target execution resource set, and determining a set of candidate resource warehouses; and performing joint optimization matching based on the set of candidate workers and the set of candidate resource warehouses, selecting the optimal worker and the corresponding optimal resource warehouse, and generating a matching result.
[0049] The following will describe the specific configuration of the matching and scheduling management module 40 in detail. The matching and scheduling management module 40 further includes: for each candidate worker in the candidate worker set, taking the location of each candidate worker as the starting point, any candidate resource warehouse location in the candidate resource warehouse set as the intermediate point, and the work order request location as the endpoint, calling the map navigation module to traverse and calculate the optimal navigation route corresponding to each candidate worker; comparing the optimal navigation routes corresponding to each candidate worker, filtering the optimal worker and corresponding optimal resource warehouse corresponding to the optimal navigation route with the shortest navigation distance, and generating the matching result.
[0050] The specific configuration of the property work order data collection module 10 will be described in detail below. The property work order data collection module 10 further includes: extracting the historical work order type and work material set for each historical work order in the historical property work order data; classifying the historical work order types to generate multiple work order types; sequentially merging the work material sets corresponding to all historical work orders for the multiple work order types to generate an execution resource set, and associating and mapping it with the multiple work order types to generate the work order type-execution resource mapping.
[0051] The following section will continue to describe in detail the specific configuration of the property management work order data collection module 10. The property management work order data collection module 10 further includes: if any historical work order data contains multiple work order types, then the work order will be segmented before being categorized.
[0052] The specific configuration of the matching and scheduling management module 40 will be described in detail below. The matching and scheduling management module 40 further includes: if the target work order type has at least two target types, reconstructing and identifying mixed workers with functional attributes of at least two target types based on the worker location distribution network of various work order types, and constructing a mixed worker distribution network; based on the mixed worker scheduling status corresponding to the mixed worker distribution network, using the target execution resource set and the work order request location as fixed conditions, and combining the execution resource warehouse distribution network to perform mixed worker and resource warehouse matching; if matching fails, further segmenting the at least two target types and matching them sequentially.
[0053] The specific configuration of the target resource matching module 30 will be described in detail below. The target resource matching module 30 further includes: the real-time work order request is created through the client's self-service channel, the IoT automatic monitoring module, and / or manually.
[0054] The specific configuration of the distributed network establishment module 20 will be described in detail below. The distributed network establishment module 20 further includes: extracting historical worker scheduling trajectories from historical property work order data; identifying path losses caused by resource warehouses in high-density areas with a path density greater than a preset trajectory density based on historical worker scheduling trajectories; if the path loss is greater than a preset threshold, optimizing the distribution of resource warehouses in the high-density areas and pushing resource warehouse optimization suggestions to the property center.
[0055] The property intelligent work order scheduling service management system provided in the embodiments of the present invention can execute the property intelligent work order scheduling service management method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.
[0056] Based on the foregoing embodiments, this application also provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, it can implement the property intelligent work order scheduling service management method as described in any of the preceding embodiments.
[0057] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any modifications, equivalent changes, and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.
Claims
1. A property management intelligent work order dispatch service management method, characterized in that, include: Collect historical property work order data from the property center, classify and map work orders, and establish a work order type-execution resource mapping. Establish the execution resource warehouse distribution network and the worker location distribution network for various work order types in the property center; Receive the real-time work order request from the property center and parse it to obtain the target work order type and work order request location. Based on the target work order type, match the target execution resource set in the work order type-execution resource mapping. Match the target worker location distribution network with the target work order type, read the current worker scheduling status, and match the worker and resource warehouse of the real-time work order request with the target execution resource set and the work order request location as fixed conditions, and use the execution resource warehouse distribution network to perform scheduling management based on the matching results.
2. The property intelligent work order scheduling service management method according to claim 1, characterized in that, Matching the target work order type with the corresponding target worker location distribution network, and reading the current worker scheduling status, using the target execution resource set and the work order request location as fixed conditions, and combining the execution resource warehouse distribution network, performs worker and resource warehouse matching for the real-time work order request, including: Based on the current worker scheduling status, determine the idle status and current location of each target worker, and filter out a set of candidate workers who can respond to work order requests. Read the inventory status of each resource warehouse in the execution resource warehouse distribution network of the target execution resource set, and determine the candidate resource warehouse set; Based on the candidate worker set and the candidate resource warehouse set, a joint optimization matching is performed to select the optimal worker and the corresponding optimal resource warehouse, and a matching result is generated.
3. The property intelligent work order scheduling service management method according to claim 2, characterized in that, Based on the candidate worker set and the candidate resource warehouse set, a joint optimization matching is performed, including: For each candidate worker in the candidate worker set, starting from the location of each candidate worker, taking any candidate resource warehouse location in the candidate resource warehouse set as the intermediate point, and taking the work order request location as the endpoint, the map navigation module is called to traverse and calculate to obtain the optimal navigation route corresponding to each candidate worker. By comparing the optimal navigation routes for each candidate worker, the optimal worker and the corresponding optimal resource warehouse corresponding to the optimal navigation route with the shortest navigation distance are selected to generate the matching result.
4. The property intelligent work order scheduling service management method according to claim 1, characterized in that, Collect historical property management work order data from the property management center, classify and map work orders, and establish a work order type-execution resource mapping, including: For each historical work order in the historical property work order data, extract the historical work order type and the set of work materials; Based on the historical work order types, various work order types are generated; The sets of work materials corresponding to all historical work orders for various work order types are merged sequentially to generate an execution resource set, and then associated and mapped with various work order types to generate the work order type-execution resource mapping.
5. The property intelligent work order scheduling service management method according to claim 4, characterized in that, If any historical work order data contains multiple work order types, then the work order will be segmented before being classified.
6. The property intelligent work order scheduling service management method according to claim 1, characterized in that, When receiving a real-time work order request from the property center and parsing it to obtain the target work order type, the process also includes: If the target work order type is at least two target types, the worker location distribution network of each work order type is reconstructed to identify mixed workers with functional attributes of at least two target types, and a mixed worker distribution network is constructed. Based on the mixed worker scheduling status corresponding to the mixed worker distribution network, the target execution resource set and the work order request location are used as fixed conditions. The mixed workers and resource warehouses are matched in combination with the execution resource warehouse distribution network. If the matching fails, at least two target types are segmented and matched sequentially.
7. The property intelligent work order scheduling service management method according to claim 1, characterized in that, The real-time work order requests are created through the client's self-service channel, the IoT automatic monitoring module, and / or manually.
8. The property intelligent work order scheduling service management method according to claim 1, characterized in that, After establishing the execution resource warehouse distribution network of the property center, it also includes: Extract historical worker dispatch trajectories from historical property work order data; Based on historical worker scheduling trajectories, path loss caused by resource warehouses is identified in high-density areas where the path loss exceeds a preset trajectory density. If the path loss exceeds a preset threshold, resource warehouse distribution is optimized in the high-density areas, and resource warehouse optimization suggestions are pushed to the property center.
9. A property management intelligent work order dispatch service management system, characterized in that, The system is used to implement the property intelligent work order scheduling service management method according to any one of claims 1 to 8, and the system includes: The property work order data collection module is used to collect historical property work order data from the property center, perform work order classification mapping, and establish work order type-execution resource mapping. The distributed network establishment module is used to establish the execution resource warehouse distribution network and the worker location distribution network for various work order types of the property center. The target resource matching module is used to receive real-time work order requests from the property center, parse and obtain the target work order type and work order request location, and match the target execution resource set in the work order type-execution resource mapping based on the target work order type. The matching and scheduling management module is used to match the target worker location distribution network of the corresponding type with the target work order type, read the current worker scheduling status, and use the target execution resource set and the work order request location as fixed conditions to match the workers and resource warehouses of the real-time work order request in combination with the execution resource warehouse distribution network, and perform scheduling management based on the matching results.
10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the property intelligent work order scheduling service management method as described in any one of claims 1-8.