Service capacity scheduling method, device, equipment, storage medium and program product

Abstract

This invention relates to the field of computer technology, providing a service capacity scheduling method, apparatus, device, storage medium, and program product. The method includes: acquiring user service request information; matching the service request information with service resource information to determine target service personnel; the service resource information includes one or more of service technical capabilities, service areas, and service brand categories; determining the target service personnel's travel planning information based on the target service personnel's work schedule and the user's location information; and determining the target service personnel's arrival time based on the travel planning information. This invention, based on service resource information such as the service personnel's technical capabilities, service areas, and service brand categories, determines the service personnel's work schedule and plans their travel, providing users with accurate arrival times, achieving intelligent service capacity scheduling, ensuring reasonable travel arrangements for service personnel, and effectively improving service experience and efficiency.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of computer, and in particular, to a service capacity scheduling method and device, an electronic device, a non-transitory computer readable storage medium, and a computer program product. BACKGROUND

[0002] With the rapid popularization of home appliances and home devices, the use frequency of home appliances is increasing, and the demand for after-sales service is also showing a growing trend year by year. Especially the maintenance, installation, debugging, and maintenance of home appliances, which are after-sales services, have become an important link to ensure user experience and improve product satisfaction.

[0003] However, the traditional after-sales service scheduling method has certain limitations, mainly manifested as: the traditional after-sales service scheduling relies on manual allocation of tasks, and cannot reasonably match and optimize resources according to actual conditions, which easily causes scheduling delay or resource waste, affecting the timeliness and response speed of the service. In addition, the traditional after-sales service scheduling process is complicated, thereby reducing user satisfaction. Therefore, how to efficiently and intelligently realize after-sales service capacity scheduling has become a problem to be solved. SUMMARY

[0004] The present application aims to at least solve one of the problems in the prior art. To this end, the present application provides a service capacity scheduling method, which determines the work schedule of service personnel and plans the itinerary by service resource information such as service technical ability, service area, and service brand category of the service personnel, provides accurate arrival time for users, realizes intelligent service capacity scheduling, ensures reasonable arrangement of service personnel itinerary, and effectively improves service experience and service efficiency.

[0005] The present application also provides a service capacity scheduling device, an electronic device, a non-transitory computer readable storage medium, and a computer program product.

[0006] According to the service capacity scheduling method of the first aspect of the present application, the method comprises: obtaining service demand information of a user; matching the service demand information with service resource information to determine a target service personnel; the service resource information includes one or more of service technical ability, service area, and service brand category; determining itinerary planning information of the target service personnel according to the work schedule of the target service personnel and the location information of the user; determining the arrival time of the target service personnel according to the itinerary planning information of the target service personnel.

[0007] According to one embodiment of the present application, the matching of the service appeal information with the service resource information to determine the target service personnel comprises: parsing the service appeal information to determine a problem type and a device type of the device to be serviced, and location information of the user; determining a matching result of a service technical capability required for processing the problem type with the service technical capability in the service resource information, a matching result of the device type with the service brand category, and / or a matching result of the location information with the service area; determining the target service personnel according to at least one of the matching results.

[0008] According to one embodiment of the present application, the work schedule of the target service personnel is determined in the following manner: determining an environment label corresponding to an address of the location information according to the location information of the user; predicting a target service duration of the device to be serviced according to mapping information of the environment label and the service duration; determining the work schedule of the target service personnel according to the existing workload of the target service personnel and the target service duration.

[0009] According to one embodiment of the present application, the mapping information of the environment label and the service duration is determined in the following manner: obtaining a user address reported by a user from a historical service work order; performing environment recognition on the user address to parse one or more of floor information, community information, and building facility information of the user; predicting a service duration corresponding to an address environment of the user address according to at least one of the floor information, the community information, and the building facility information; determining an environment label of the user address according to a matching result of an environment database and the user address; the environment database is obtained by aggregating and classifying the user address; establishing a mapping relationship between the service duration and the environment label to generate the mapping information.

[0010] According to one embodiment of the present application, the service resource information further comprises a commuting tool; and the determination of the work schedule of the target service personnel according to the existing workload of the target service personnel and the target service duration comprises: determining a commuting time of the target service personnel according to the commuting tool; determining a priority of a service work order according to the service appeal information; According to the existing workload of the target service personnel, the target service time length, the commuting time, the priority, and weather information, a work schedule of the target service personnel is determined.

[0011] According to an embodiment of the present application, the determining the work schedule of the target service personnel according to the existing workload of the target service personnel and the target service time length further comprises: According to the service demand information, a user identity is acquired; According to the user identity, a user portrait of the user is matched from a database; the user portrait is constructed based on historical service work orders of the user; According to the customer satisfaction score information of the target service personnel, a service star level of the target service personnel is determined; According to the existing workload of the target service personnel, the target service time length, the user portrait, and the service star level, the work schedule of the target service personnel is determined.

[0012] According to an embodiment of the present application, the method further comprises: According to historical service operation data of a service site, a work order quantity of the service site in a future set time is predicted; the work order quantity comprises a cumulative work order quantity and a new work order quantity in the future set time; According to the work order quantity of the service site in the future set time, a required service personnel quantity of the service site in the future set time is predicted; According to the required service personnel quantity of the service site in the future set time, personnel reserves are made.

[0013] According to an embodiment of the present application, the service resource information further comprises a service type; the predicting the work order quantity of the service site in the future set time according to the historical service operation data of the service site comprises: A prediction granularity is determined; the prediction granularity comprises one or more of the service area, the service brand category, and the service type; According to the historical service operation data and the prediction granularity, the work order quantity of the service site in the future set time is predicted.

[0014] The service operation scheduling device according to the second aspect embodiment of the present application comprises: An acquisition module is configured to acquire service demand information of a user; A target service personnel determination module is configured to match the service demand information with service resource information to determine a target service personnel; the service resource information comprises one or more of a service technical capability, a service area, and a service brand category; The itinerary planning information determination module is used to determine the itinerary planning information of the target service personnel based on the work schedule of the target service personnel and the location information of the user; The on-site arrival time determination module is used to determine the on-site arrival time of the target service personnel based on their travel planning information.

[0015] An electronic device according to a third aspect of the present invention includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the service capacity scheduling method as described above.

[0016] According to a fourth aspect of the present invention, a non-transitory computer-readable storage medium is provided thereon storing a computer program that, when executed by a processor, implements the service capacity scheduling method as described above.

[0017] A computer program product according to a fifth aspect of the present invention includes a computer program that, when executed by a processor, implements the service capacity scheduling method as described above.

[0018] The above-described one or more technical solutions in the embodiments of the present invention have at least one of the following technical effects: Based on service personnel's technical capabilities, service areas, service brand categories, and other service resource information, the system determines the service personnel's work schedule and plans their itineraries, providing users with accurate on-site arrival times, achieving intelligent service capacity scheduling, ensuring reasonable scheduling of service personnel's schedules, and effectively improving service experience and efficiency.

[0019] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 This is one of the flowcharts illustrating the service capacity scheduling method provided in this embodiment of the invention.

[0022] Figure 2 This is the second flowchart of the service capacity scheduling method provided in this embodiment of the invention.

[0023] Figure 3This is a schematic diagram of the work order allocation process provided in an embodiment of the present invention.

[0024] Figure 4 This is a schematic diagram of the service capacity scheduling system provided in an embodiment of the present invention.

[0025] Figure 5 This is a schematic diagram of the service capacity scheduling device provided in an embodiment of the present invention.

[0026] Figure 6 This is a schematic diagram of the structure of the electronic device provided in an embodiment of the present invention. Detailed Implementation

[0027] The embodiments of the present invention will be described in further detail below with reference to the accompanying drawings and examples. The following examples are for illustrative purposes only and should not be construed as limiting the scope of the invention.

[0028] In the description of the embodiments of the present invention, it should be noted that the terms "first", "second" and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0029] In embodiments of the present invention, unless otherwise explicitly specified and limited, "above" or "below" the second feature can mean that the first feature is in direct contact with the second feature, or that the first feature is in indirect contact with the second feature through an intermediate medium. Furthermore, "above," "on top of," and "over" the second feature can mean that the first feature is directly above or diagonally above the second feature, or simply that the first feature is at a higher horizontal level than the second feature. "Below," "below," and "under" the second feature can mean that the first feature is directly below or diagonally below the second feature, or simply that the first feature is at a lower horizontal level than the second feature.

[0030] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0031] Figure 1 This is one of the flowcharts illustrating the service capacity scheduling method provided in this embodiment of the invention. (Refer to...) Figure 1 This invention provides a service capacity scheduling method, comprising: Step 101: Obtain the user's service request information.

[0032] User service request information can be obtained through various channels (such as telephone, APP, website, etc.). This service request information may include basic user information (such as name, contact information, address, etc.), equipment information (such as equipment brand, equipment model, equipment fault description, etc.), service request type (such as repair service, installation service, maintenance service, replacement parts, etc.), service time requirements (such as appointment time, urgency level, available time period, etc.), historical repair records, and equipment usage environment information, etc.

[0033] For example, taking telephone order placement as an example, when a user dials the service hotline, the system uses IVR (Interactive Voice Response) voice navigation to guide the user in selecting the service type. When the user selects to place an order, the system automatically triggers speech recognition technology to convert the user's speech into text content and record their service request. Through speech recognition and Natural Language Processing (NLP), the system can intelligently identify and extract key information such as equipment brand, model, and fault type. The system can further generate a work order based on the user's voice or voice commands, recording the user's basic information, including equipment brand, model, fault type, address, and contact information.

[0034] For example, taking app or website order submission as an example, users can submit repair requests through a dedicated app or official website. In the app, users fill in relevant equipment information, a description of the fault, and upload photos or videos of the equipment. Utilizing 5G video calling, users can communicate directly with customer service in real time via video, allowing technicians to more intuitively understand the equipment malfunction. The system will automatically identify the equipment type and fault category based on user input and information such as images and videos, and generate a corresponding service order.

[0035] Understandably, whether submitted via phone, app, or website, voice or text information undergoes intelligent analysis. Through natural language processing technology, the system can identify user needs, further extract key information (such as fault description, equipment brand, repair time, etc.), and automatically convert it into structured data for subsequent processing and scheduling.

[0036] Step 102: Match the service request information with the service resource information to determine the target service personnel.

[0037] Service resource information may include one or more of the following: service technical capabilities, service area, and service brand category. Service technical capabilities refer to the professional skills and knowledge possessed by service personnel in a specific field or technology, determining whether they can handle a particular type of equipment malfunction or problem. Service area refers to the geographical range within which service personnel can provide services, determining whether they can provide services at the user's location. The service area can be determined by factors such as the service personnel's work location, accessibility, and the coverage of the service network. Service brand category refers to the brand and type of equipment that service personnel can repair or maintain.

[0038] The service request information is matched with the service resource information to identify the target service personnel, who can be understood as personnel who provide on-site repair or other on-site services.

[0039] In one embodiment, the service request information is parsed to determine the problem type and device type of the device to be serviced, as well as the user's location information; the matching result between the service technical capabilities required to handle the problem type and the service technical capabilities in the service resource information, the matching result between the device type and the service brand category, and / or the matching result between the location information and the service area is determined; and the target service personnel are determined based on at least one matching result.

[0040] The service request information is analyzed to extract key information, which may include the type of equipment to be serviced (e.g., television, air conditioner, refrigerator, washing machine, etc.), the type of problem (e.g., not turning on, display malfunction, water leakage, etc.), and the user's location information (e.g., the user's specific address). Further, technical capability matching, brand category matching, and / or service area matching are performed. Technical capability matching determines whether the service personnel possess the necessary technical skills to handle the user's equipment problem; brand matching determines whether the service personnel are familiar with the user's equipment brand; and area matching determines whether the service personnel can provide service in the user's region. Finally, based on one or more matching results, the system selects a technician capable of handling the problem, ensuring that the technician is technically suitable and can conveniently and quickly reach the user's location to provide timely service.

[0041] For example, suppose a user requests repair of a refrigerator of brand A, the problem being that it is not cooling, and the user is located in region B. After parsing the user's service request information, the system identifies the device to be serviced as a refrigerator, the device type as brand A, the problem type as refrigerator not cooling, and the user's location as region B. Based on service resource information, the system will first search for technicians capable of repairing brand A refrigerators, then check whether these technicians have the skills to repair refrigerators that are not cooling, and further check whether any service personnel cover region B. If so, the system will select a service personnel whose technical capabilities, equipment brand, and region match the user's requirements.

[0042] By analyzing user needs in detail and matching them appropriately with service resources, we can ensure that suitable service personnel are assigned to handle user issues, thereby effectively improving service experience and efficiency.

[0043] In one embodiment, an environmental tag corresponding to the address of the user's location information is determined; the target service duration of the device to be served is predicted based on the mapping information between the environmental tag and the service duration; and the work schedule of the target service personnel is determined based on the existing workload of the target service personnel and the target service duration.

[0044] Specifically, an environmental tag is assigned to a user using their location information (such as geographic coordinates and address). This environmental tag is an identifier describing the relevant characteristics or information of a specific location or area. Environmental tags may include: whether there is an elevator, air conditioning installation location, reserved smoke exhaust duct, and reserved smoke exhaust vent, etc. These environmental tags can affect the complexity of the service or the time required. For example, in a community without an elevator, the service may take longer.

[0045] Different environment labels have a certain mapping relationship with service duration; that is, the complexity and time of the service will vary depending on the environment. For example, if the environment label is "no elevator," the predicted service duration may increase accordingly. If the environment label is "high floor" or "complex equipment," the service duration may also increase, taking into account the need for additional handling tools, time, etc.

[0046] Based on the predicted service duration and the workload of each target service worker, a suitable work schedule is arranged. A service worker's workload can refer to the number of tasks already assigned, the expected completion time, and available free time. For example, if a service worker already has multiple tasks assigned, the system needs to assess whether they have sufficient time to complete additional tasks. Service workers with heavier workloads may require more rest time or fewer tasks. Based on the predicted service duration, the system determines whether the service worker can complete the new task within a day. For example, if the target service duration is too long, the system may choose to assign more service workers or distribute the tasks across multiple workdays.

[0047] The above methods can effectively improve the accuracy of service scheduling, reduce service delays, improve resource utilization, and also help optimize customer experience.

[0048] Step 103: Determine the travel planning information of the target service personnel based on their work schedule and the user's location information; A work schedule can be understood as the available working time for service personnel on the same day or for a period of time to come, other tasks already arranged, rest time, etc.

[0049] First, check the service personnel's work schedule to understand their available time for the day. For example, if the service personnel already have other tasks, it's necessary to determine whether the current user's service request can be completed during their spare time, or whether the original plan needs to be adjusted. If the service personnel already have multiple tasks, avoid scheduling them too tightly to prevent delays. Next, analyze the feasibility of the service personnel traveling to the user's location. For example, if the user's location is close to the service personnel's current location, the service can be scheduled during their spare time. If the user's location is far away, more time may be needed, and transportation factors need to be considered. For example, it's necessary to confirm in advance whether the service personnel need to depart early and whether they have sufficient time to complete multiple tasks. Based on the above analysis, determine the service personnel's actual itinerary. If the original plan is already full, consider adjusting the task order or reserving time for urgent tasks; if necessary, the dispatch system can automatically adjust according to the user's needs and the service personnel's schedule to ensure all tasks are completed on time.

[0050] Optionally, when planning trips, factors such as traffic conditions and service time windows can be considered to avoid delays. Understandably, changes in traffic flow can cause congestion or smooth flow on road sections, requiring the system to adjust service personnel's routes based on real-time data. For example, if a road section experiences congestion, the system will suggest that service personnel avoid that road and choose an alternative route. During peak hours, when congestion is more severe, the system will estimate the impact of peak-hour traffic in advance and adjust service personnel's departure times or choose less busy roads. Based on traffic conditions, the system can automatically select the best route, optimize travel time, and reduce the impact of traffic delays. For example, considering traffic accidents or road construction, the system will recommend detour routes.

[0051] Each user's service request typically has a service time window, meaning the user wants service within a specific time period. The system needs to find a balance between the availability of service personnel and the user's time requirements. For example, a user might request service to be completed within a specific time frame (e.g., 9:00 AM to 11:00 AM, or 2:00 PM to 4:00 PM). If the service request time is inflexible, the system needs to find a suitable time slot during the service personnel's available time to meet the user's request. If certain service requests have a high degree of urgency (such as production stoppage due to equipment failure), the system will prioritize these requests to ensure that these tasks are not delayed. For some tasks, such as installing new equipment or performing specific inspections, there may be strict time requirements; the system needs to prioritize these tasks and schedule service personnel's schedules within a limited time window.

[0052] By combining multiple factors such as service personnel's schedules, users' geographical locations, real-time traffic conditions, and service time windows, the system can intelligently plan the optimal travel route to maximize the work efficiency of service personnel.

[0053] Step 104: Determine the arrival time of the target service personnel based on their travel planning information.

[0054] The arrival time refers to the exact time when the service personnel arrive at the user's location. The arrival time should be determined as accurately as possible to avoid arriving too early or too late, which could affect the user experience or the subsequent task arrangements for the service personnel.

[0055] First, it's necessary to review the service personnel's current schedule to ensure a reasonable time slot has been allocated to the user. It's also crucial to check if the service personnel have sufficient time to travel to the next location after completing their current task. Then, based on the service personnel's current location and the user's address, calculate the travel time to the user's location, taking into account traffic conditions, especially potential delays during peak hours, and allowing more time for travel. If the service personnel's schedule falls during peak traffic periods, it may be necessary to schedule departure times in advance.

[0056] After calculating the estimated arrival time of the service personnel, adjustments can be made based on the user's needs. For example, if the user has time requirements, those needs can be prioritized to ensure on-time arrival. If there are no specific requirements, the service personnel's arrival time should be as precise as possible to avoid unnecessary waiting due to arriving too early or affecting subsequent arrangements due to arriving too late. For example, suppose service personnel A's previous task is expected to end at 12:00, and user B's location is about a 40-minute drive from service personnel A's current location, and service personnel A has a tight work schedule. In this case, the service personnel can be arranged to depart after 12:00 and is expected to arrive at user B around 12:40.

[0057] Optionally, if the user's need is urgent (e.g., downtime due to equipment failure), the on-site visit time needs to be adjusted, arriving earlier or later to ensure timely service. If the service task is routine and the user does not have specific time requirements, the on-site visit time can be arranged more flexibly.

[0058] Once the service personnel's arrival time is confirmed, the user and service personnel need to be notified promptly. Inform the user of the service personnel's specific arrival time, and ensure the service personnel understand the detailed arrangements of the task, including the user's address, estimated arrival time, and traffic conditions.

[0059] The service capacity scheduling method provided in this invention obtains user service request information; matches the service request information with service resource information to determine the target service personnel; the service resource information includes one or more of service technical capabilities, service areas, and service brand categories; determines the target service personnel's travel planning information based on the target service personnel's work schedule and the user's location information; and determines the target service personnel's arrival time based on the target service personnel's travel planning information. This invention, based on service resource information such as service personnel's service technical capabilities, service areas, and service brand categories, determines the service personnel's work schedule and plans their travel, providing users with accurate arrival times, achieving intelligent service capacity scheduling, ensuring reasonable travel arrangements for service personnel, and effectively improving service experience and efficiency.

[0060] Based on the above embodiments, the mapping information between the environment tag and the service duration is predetermined in the following manner: Step 110: Obtain the user address reported by the user from the historical service tickets; Step 111: Perform environmental identification on the user address to parse one or more of the following: the user's floor information, the community information, and the building facility information; Step 112: Based on at least one of the floor information, the community information, and the building facility information, predict the service duration corresponding to the address environment of the user address; Step 113: Determine the environmental tag of the user address based on the matching result between the environmental database and the user address; the environmental database is obtained by aggregating and classifying the user address. Step 114: Establish a mapping relationship between the service duration and the environment tag to generate mapping information.

[0061] To improve service efficiency and reduce errors, the system utilizes user address data from historical service orders. By parsing and matching different environmental features (such as floor information, community information, building facility information, etc.), it predicts the time required to provide service to users and generates environmental tags based on these features. For example, this can be achieved through the following steps: (1) The historical service work orders contain address data, from which the system extracts the user's address information, such as community name, building number, floor, house type, etc.

[0062] (2) Based on the address information provided by the user, the system needs to identify and parse the environment. For example, extracting specific environmental features from the user's address may include: Floor information: such as whether the user lives on a high floor or a low floor, whether it is the top floor or the ground floor, or whether there is an elevator, etc.; Community information: such as the size of the community where the user lives, whether it is an old or newly developed community, supporting facilities, etc.; Building facilities information: Does the building have any special building facilities, such as elevators, underground parking, whether a smoke exhaust duct is reserved, whether a smoke exhaust hole is reserved, air conditioner installation space, etc.

[0063] (3) Based on the environmental information (such as floor, community, building facilities, etc.) parsed from the user's address, the system predicts the service time for the user in that environment. Different environmental characteristics will affect the service duration. For example, if the user lives on a high floor without an elevator, the service personnel may need to spend more time climbing the stairs, and the service duration may be longer; if the user lives in a newly built community with complete facilities, the service duration may be shorter because the environment may be easier to access and the service facilities are more convenient. Among them, the service duration prediction can be based on the correlation model of these environmental characteristics. The system predicts the service duration of a specific address by analyzing the relationship between historical data and environmental characteristics.

[0064] (4) By aggregating and classifying user addresses (e.g., by community, floor, and building facility features), the system matches user addresses with predefined environmental tags. These environmental tags can be the aggregation results of these features, such as high-rise (top floor or high-rise floors without elevators), newly built communities (well-equipped facilities and a new community environment), and old communities (poor facilities and a relatively outdated community). These environmental tags reflect the typical environment of the user address and can help with subsequent service arrangements and duration prediction.

[0065] (5) Establish a mapping relationship to associate environment tags with predicted service durations. For example, for different environment tags, the system can define a general range of service durations: The "No Elevator" label for high-rise buildings can correspond to a longer service time (e.g., 60 minutes). Newly created cell tags can correspond to shorter service durations (e.g., 30 minutes). By analyzing historical data, the system can assign a corresponding service duration to different environment tags, so that when a user service request is received, it can quickly predict and arrange an appropriate service duration based on the environment tag of the user's address.

[0066] This invention, through detailed analysis and classification of the environmental characteristics of user addresses (such as floor, community, building facilities, etc.), enables the system to predict and optimize service duration. Based on this, service personnel can make adjustments and preparations in advance according to different environmental conditions, avoiding unnecessary delays caused by environmental factors during service, and improving service response speed and timeliness. Through accurate environmental identification and duration prediction, service efficiency is improved, operating costs are reduced, customer experience is optimized, prediction accuracy is increased, and data-driven decision-making is enhanced, ultimately achieving efficient resource allocation and higher-quality customer service.

[0067] Based on the above embodiments, the service resource information further includes commuting tools; determining the work schedule of the target service personnel based on their existing workload and the target service duration includes: Step 120: Determine the commute time of the target service personnel based on the commuting vehicle; Step 121: Determine the priority of the service order based on the service request information; Step 122: Determine the work schedule of the target service personnel based on their existing workload, target service duration, commuting time, priority, and weather information.

[0068] In practical service dispatch systems, the commuting vehicles used by service personnel (such as cars, trucks, electric bikes, motorcycles, etc.) directly affect their commuting time, itinerary arrangements, and work efficiency. Therefore, the differences in commuting vehicles should be reasonably considered when scheduling work schedules. Based on the different commuting vehicles, the system can schedule service personnel's work schedules according to the following aspects.

[0069] First, determine the impact of commuting modes on commuting time: different commuting modes vary significantly in road conditions, speed, and traffic adaptability, which directly affects service personnel's commuting time. In service dispatching, the system needs to estimate service personnel's commuting time based on the characteristics of these commuting modes. For example, service personnel using cars may need extra time during peak hours to avoid congested areas, while electric bikes and motorcycles can navigate traffic-intensive streets more flexibly.

[0070] Each service order has a different priority. The urgency of the service order can be determined based on the service request information, and then the priority of the service order can be determined based on the urgency.

[0071] Further, based on the target service personnel's existing workload, target service duration, commute time, priority, and weather information, determine the target service personnel's work schedule. For example, suppose service personnel A has already been assigned a medium-priority work order today, which is expected to take 2 hours to complete. A new work order (high priority) is expected to take 3 hours to complete, with a commute time of 40 minutes (one way). The weather forecast indicates heavy rain in the afternoon, which may cause traffic congestion. Based on the above information, the following arrangements can be made: Service personnel A already has 2 hours of work scheduled and needs to allocate 3 hours to handle the new work order. Since the new work order is high priority, it needs to be completed first to minimize delays. Adding the 40-minute one-way commute time, and considering that the weather may affect traffic and extend the commute time, extra time needs to be considered in advance. Since heavy rain may increase the commute time, additional time can be allocated to cope with this. Finally, service personnel A's work schedule can be: 9:00 AM - 11:00 AM: Complete existing work orders (2 hours); 11:00-12:00: Commuting time (40 minutes to reach the client's location, but 45 minutes are allowed in case of heavy rain). 12 PM - 3 PM: Processing new work orders (high priority, estimated 3 hours); 3-4 PM: Commute back to the company (allow extra time, taking into account the weather).

[0072] This invention, through the reasonable arrangement of service personnel's schedules, taking into account factors such as commuting methods, existing workload, service duration of each task, weather information, and the priority of service work orders, can help the system dynamically optimize work arrangements, improve service efficiency, and avoid delays and resource waste caused by improper time and tool selection.

[0073] In one embodiment, determining the work schedule of the target service personnel based on their existing workload and the target service duration further includes: Step 130: Obtain the user's identity identifier based on the service request information; Step 131: Based on the user identity identifier, match the user profile from the database; the user profile is constructed based on the user's historical service tickets; Step 132: Determine the service star rating of the target service personnel based on their customer satisfaction rating information; Step 133: Determine the work schedule of the target service personnel based on their existing workload, target service duration, user profile, and service rating.

[0074] Service request information may include key elements such as the user's contact information (phone number, email, etc.), username, or specific business number related to the user. From this information, a unique identifier for the user can be extracted.

[0075] After identifying a user, the system retrieves the corresponding user profile from the database. This profile is a comprehensive user information file built upon the user's past behavior and needs (such as historical service tickets, complaint records, and feedback ratings). User profiles help determine service priorities and complexity. For example, if user A frequently complains about a particular feature, experienced and problem-solving personnel may be assigned; conversely, if user B has high expectations for communication skills, personnel with smooth communication abilities and professional expertise may be needed.

[0076] By analyzing the rating data of target service personnel, the service quality level of the personnel is measured, and their service star rating is determined, that is, the service personnel are divided into corresponding levels. For example, those with a high satisfaction rating that is consistently in the excellent range will have a higher service star rating; conversely, those with a low rating and frequent customer complaints will have a lower service star rating. Different service star ratings represent different levels of service quality.

[0077] Furthermore, based on the target service personnel's existing workload, target service duration, user profile, and service rating, the work schedule for the target service personnel is determined. For example, suppose there are the following tasks: Task A: Solve a technical problem for user A, estimated service time 2 hours; Task B: Answer a simple question for user B, estimated service time 1 hour; Task C: Perform a routine check for user C, estimated service time 3 hours. Suppose a service personnel with a rating of 4 stars has completed 3 hours of work, with 5 hours remaining. Based on the difficulty of the tasks and the capabilities of the service personnel, the schedule is arranged as follows: Task A (2 hours): Because user A's needs are relatively complex and the service personnel have a high rating, this task is assigned; Task B (1 hour): The task is relatively simple and can be assigned to this service personnel; Task C (3 hours): This task requires a service personnel with higher skills and can be postponed to the next shift or assigned to a service personnel with a higher rating.

[0078] By combining user profiles, service personnel star ratings, historical workload and service duration data, this invention can help the system dynamically optimize work arrangements, accurately match service personnel and user needs, and achieve personalized, high-quality and efficient services.

[0079] Based on the above embodiments, the method further includes: Step 140: Based on the historical service operation data of the service outlets, predict the number of work orders for the service outlets within a future set time period; the number of work orders includes the cumulative number of work orders and the number of new work orders within the future set time period. Step 141: Based on the number of work orders at the service outlets within a future set time period, predict the number of service personnel required for the service outlets within the future set time period. Step 142: Prepare personnel reserves based on the number of service personnel required for the service outlets within a future set time period.

[0080] Historical service operation data can include service type, historical work order volume, regional finished product sales, retail volume, work order status, regional capacity (population), weather, and other data.

[0081] To identify future order volume and provide advance warnings for operations, service outlets, and fourth-level regions, and to prepare service personnel in advance, historical service operation data can be used to predict the number of work orders and service personnel required for service outlets within a specified future timeframe. These predictions can include static forecasts (monthly) and dynamic forecasts (e.g., 3-day, 7-day, 15-day).

[0082] (1) Static Forecast (Monthly): Forecast future order volume on a monthly basis using regression forecast (quantity forecast): Predict the service order volume for the next month by using regression analysis of historical data. Forecast the number of service personnel needed on a monthly basis using regression forecast (quantity forecast): Based on the predicted service order volume, further predict the number of service personnel required. Forecast the order volume level for the next month (categorical forecast): Determine whether the order volume for the next month reaches a certain percentage, such as 20%, 50%, or 100%.

[0083] (2) Dynamic Forecasting (3 days, 7 days, 15 days): Predicting the cumulative number of work orders in the next 15 days using regression forecasting (quantitative forecasting): Predicting the cumulative number of work orders in the next 15 days through regression analysis. Predicting the degree of order volume in the next 15 days by combining the number of service personnel and the current work order situation (categorical forecasting): Considering the current number of service personnel and the current work order situation, predicting whether the order volume in the next 15 days will reach a specific percentage, such as 20%, 50%, or 100%, etc. Among these, When conducting static and dynamic forecasting, feature factors are constructed around multi-source factors (such as work order status, service type, historical work order volume, sales policy, regional finished product sales, regional capacity (population), retail volume, and weather) to learn future trend information. Model selection can adopt small-scale models, general-purpose large models, and time-series large-scale models for forecasting.

[0084] After predicting the number of service personnel needed at service outlets within a set future timeframe, the system prepares personnel reserves based on these predictions. For example, if high service demand is anticipated at some point in the future, the system will reserve additional personnel in advance. Therefore, when demand surges, service outlets can promptly dispatch sufficient personnel to handle the situation, preventing service quality degradation or excessively long customer wait times due to staff shortages.

[0085] Optionally, when building up staff reserves, it is also necessary to flexibly arrange the working hours and shifts of service personnel based on actual forecast data. For example, when demand is high during certain periods, more personnel can be deployed in advance, while during periods of lower demand, fewer personnel can be deployed, thereby achieving optimal personnel allocation and resource utilization.

[0086] This personnel reserve mechanism effectively avoids service resource shortages caused by demand fluctuations, improving service timeliness and customer satisfaction. At the same time, it also helps avoid idle personnel and unnecessary cost waste caused by excessive personnel reserves.

[0087] In one embodiment, the forecast granularity is determined; based on historical service operation data and the forecast granularity, the work order volume of service outlets within a future set time period is predicted. The forecast granularity refers to the level of detail or segmentation used in the forecast; it can include one or more of the following: service area (e.g., a fourth-level region), service brand category, and service type, i.e., forecasts are made separately for different region levels, service brand categories, and service types. In actual forecasting operations, to achieve more accurate work order volume forecasts, multiple factors are usually considered comprehensively. For example, in different fourth-level regions, the demand for different service types varies for different product categories. In one fourth-level region, the demand for repair services (service type) of a certain product (e.g., air conditioners) may be higher, while in another fourth-level region, the demand for installation services of the same product may be higher. By considering these three forecast granularities simultaneously, a more comprehensive understanding of the demand situation in different regions, for different products, and for different services can be achieved.

[0088] This invention, by introducing granular forecasting, enables more refined and accurate service demand forecasting. This not only improves forecast accuracy and resource allocation flexibility but also enhances customer satisfaction, optimizes cost control, strengthens emergency response capabilities, and supports data-driven decision-making processes. Refining forecast granularity is not only key to improving operational efficiency but also an important means to enhance customer experience, reduce risks, and improve competitiveness.

[0089] To further explain the service capacity scheduling method provided by the present invention, please refer to the following embodiments.

[0090] This invention aims to effectively improve service experience and ensure reasonable scheduling of service personnel's schedules through an intelligent scheduling system. To achieve the above objective, this invention provides a service capacity scheduling method, referencing... Figure 2 It mainly includes the following: (1) Obtaining user service request information: Users submit service requests via telephone, APP or website, describing in detail the problems of home appliances or home equipment that need repair or maintenance. Among them, telephone and APP order reporting adopt IVR voice navigation, voice to text, 5G video call, etc. For example, when the user says "I want to report an order", a work order is automatically generated, and the system records the user's basic information, including address, contact information, equipment brand and model, etc.

[0091] (2) Determine the service personnel's schedule based on their technical skills, service area, service brand category, and commuting method: The system will match service personnel based on information such as their technical skills (e.g., whether they are proficient in repairing a particular brand), service area (the service personnel's work scope), and service brand category (the brands and types of equipment that the service personnel are good at repairing). It will also consider the service personnel's mode of transportation (e.g., cars, trucks, electric bikes, motorcycles, etc.) to rationally schedule their work.

[0092] (3) Itinerary planning: The system will plan the optimal itinerary based on the service personnel's schedule and the user's geographical location to ensure that the service personnel can efficiently complete multiple service requests. When planning the itinerary, factors such as traffic conditions and service time windows will also be considered to avoid delays.

[0093] (4) Providing users with accurate on-site arrival times and real-time online access: The system will generate service personnel's schedules and inform users of the accurate arrival times via SMS, APP notifications, etc. Users can view the service personnel's schedule progress in real time through the APP or website, and understand the service personnel's current location and estimated arrival time.

[0094] To better understand the present invention, the present invention will be described in detail below with reference to specific embodiments: Example 1: Users submit service requests via the app, and the system records the user's detailed information. The system matches suitable service personnel based on their technical capabilities and service area, taking into account their commuting methods and scheduling. The system plans the optimal route and notifies the user of the exact arrival time via the app. Users can view the service personnel's progress in real time to ensure smooth service delivery.

[0095] Example 2: Users submit service requests via telephone, and the system records the user's detailed information. The system matches suitable service personnel based on their technical capabilities and service brand category, taking into account their commuting methods and scheduling. The system plans the optimal route and notifies the user of the exact arrival time via SMS. Users can track the service personnel's progress in real time through the website, ensuring smooth service delivery.

[0096] refer to Figure 3 The work order assignment process can include: (1) User places an order: The user submits a service request; (2) Matching the order address with the AOI (Area of ​​Interest): The system will match the user's order address with the AOI. This step is to determine the user's geographical location so that the work order can be allocated more accurately in the future. (3) Matching work order type with skill layer: The system will match the engineer's skill layer according to the type of work order (such as different types of services such as repair and installation). This means that the system will find an engineer with the corresponding skills to handle the work order. (4) Matching AOI-AOI area association: Further associate the AOI information of the work order with the AOI area where the engineer is located. This step is to find engineers who are geographically closer to the user and improve service efficiency. (5) Obtain the corresponding engineer according to the dispatch rules: According to the preset dispatch rules, the system will filter out the engineers that meet the conditions. The rules may include factors such as the engineer's skills, geographical location, and workload. (6) Determine the number of engineers: The system will determine the number of engineers selected; if the number is equal to 1, that is, only one engineer meets the conditions, the work order will be directly assigned to that engineer; if the number is greater than 1, that is, multiple engineers meet the conditions, the system will proceed to the next step. (7) Decision on engineer based on work order balance + AOI distance: When multiple engineers meet the conditions, the system will comprehensively consider the work order balance (which can refer to the current workload allocation of the engineer) and AOI distance (the geographical distance between the engineer and the user) to determine the engineer who will be assigned the work order. This step is to ensure that the most suitable one is selected from multiple suitable engineers. (8) Work order enters engineer's schedule: Finally, the selected engineer will receive the work order and add it to their schedule to prepare to provide service.

[0097] The above process is an automated work order allocation system that ensures that users' service requests are assigned to the most suitable engineers through multi-step screening and decision-making. It also takes into account factors such as geographical location and engineer workload to improve service efficiency and quality.

[0098] refer to Figure 4 The service capacity scheduling system may include the following: Users submit service requests through their user terminals, and the service request recording module records the user's detailed information. The dispatching and matching module extracts information on matching service personnel from the service personnel information database and performs matching. The trip planning module plans the optimal route based on the matching results and the user's geographical location. The notification module informs the user of the exact arrival time via SMS, app notifications, etc. The real-time tracking module provides the service personnel's trip progress, allowing users to view the service personnel's current location and estimated arrival time in real time.

[0099] Through the above-described embodiments, the system of this invention can effectively improve the user's service experience, reduce waiting time, and increase service efficiency. At the same time, it can rationally schedule the service personnel's schedules, avoiding unnecessary travel and time waste, and improving the job satisfaction of service personnel.

[0100] The service capacity scheduling device provided by the present invention is described below. The service capacity scheduling device described below can be referred to in correspondence with the service capacity scheduling method described above.

[0101] refer to Figure 5 The service capacity scheduling device provided by the present invention includes an acquisition module 501, a target service personnel determination module 502, a trip planning information determination module 503, and a door-to-door arrival time determination module 504.

[0102] Module 501 is used to obtain user service request information; The target service personnel determination module 502 is used to match the service request information with service resource information to determine the target service personnel; the service resource information includes one or more of the following: service technical capabilities, service area, and service brand category. The itinerary planning information determination module 503 is used to determine the itinerary planning information of the target service personnel based on the work schedule of the target service personnel and the location information of the user; The on-site arrival time determination module 504 is used to determine the on-site arrival time of the target service personnel based on the travel planning information of the target service personnel.

[0103] The service capacity scheduling device provided in this invention obtains user service request information; matches the service request information with service resource information to determine the target service personnel; the service resource information includes one or more of service technical capabilities, service areas, and service brand categories; determines the target service personnel's travel planning information based on the target service personnel's work schedule and the user's location information; and determines the target service personnel's arrival time based on the target service personnel's travel planning information. This invention, based on service resource information such as the service personnel's service technical capabilities, service areas, and service brand categories, determines the service personnel's work schedule and plans their travel, providing users with accurate arrival times, achieving intelligent service capacity scheduling, ensuring reasonable travel arrangements for service personnel, and effectively improving service experience and efficiency.

[0104] In one embodiment, the target service personnel determination module 502 is specifically used for: The service request information is parsed to determine the problem type and device type of the device to be served, as well as the user's location information; the matching result between the service technical capabilities required to handle the problem type and the service technical capabilities in the service resource information, the matching result between the device type and the service brand category, and / or the matching result between the location information and the service area is determined; based on at least one of the matching results, the target service personnel are determined.

[0105] In one embodiment, the trip planning information determination module 503 is further configured to: Based on the user's location information, determine the environmental tag corresponding to the address in the location information; based on the mapping information between the environmental tag and the service duration, predict the target service duration of the device to be served; based on the existing workload of the target service personnel and the target service duration, determine the work schedule of the target service personnel.

[0106] In one embodiment, the trip planning information determination module 503 is further configured to: The system retrieves the user address reported by the user from historical service orders; performs environmental identification on the user address to parse one or more of the user's floor information, community information, and building facility information; predicts the service duration corresponding to the address environment of the user address based on at least one of the floor information, community information, and building facility information; determines the environmental tag of the user address based on the matching result between the environmental database and the user address; the environmental database is obtained by aggregating and classifying the user address; and establishes a mapping relationship between the service duration and the environmental tag to generate mapping information.

[0107] In one embodiment, the service resource information further includes commuting tools; the trip planning information determination module 503 is also used for: Based on the commuting tool, determine the commuting time of the target service personnel; based on the service request information, determine the priority of the service work order; based on the target service personnel's existing workload, the target service duration, the commuting time, the priority, and weather information, determine the target service personnel's work schedule.

[0108] In one embodiment, the trip planning information determination module 503 is further configured to: Based on the service request information, obtain the user's identity identifier; based on the user's identity identifier, match the user's user profile from the database; the user profile is constructed based on the user's historical service work orders; based on the customer satisfaction rating information of the target service personnel, determine the service star rating of the target service personnel; based on the target service personnel's existing workload, the target service duration, the user profile, and the service star rating, determine the target service personnel's work schedule.

[0109] In one embodiment, the service capacity scheduling device further includes a personnel reserve module, used for: Based on the historical service operation data of the service outlets, predict the number of work orders for the service outlets within a future set time period; the number of work orders includes the cumulative number of work orders and the number of new work orders within the future set time period; based on the number of work orders for the service outlets within the future set time period, predict the number of service personnel required for the service outlets within the future set time period; and make personnel reserves based on the number of service personnel required for the service outlets within the future set time period.

[0110] In one embodiment, the service resource information further includes service type, and the service capacity scheduling device further includes a personnel reserve module, and is also used for: Determine the prediction granularity; the prediction granularity includes one or more of the service area, the service brand category, and the service type; based on the historical service operation data and the prediction granularity, predict the number of work orders for the service outlets within a future set time period.

[0111] Figure 6 An example is a schematic diagram of the physical structure of an electronic device, such as... Figure 6As shown, the electronic device may include a processor 610, a communications interface 620, a memory 630, and a communication bus 640, wherein the processor 610, communications interface 620, and memory 630 communicate with each other via the communication bus 640. The processor 610 can invoke logical instructions in the memory 630 to execute the following methods: obtaining user service request information; matching the service request information with service resource information to determine the target service personnel; the service resource information includes one or more of service technical capabilities, service areas, and service brand categories; determining the target service personnel's travel planning information based on the target service personnel's work schedule and the user's location information; and determining the target service personnel's arrival time based on the target service personnel's travel planning information.

[0112] Furthermore, the logical instructions in the aforementioned memory 630 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0113] On the other hand, embodiments of the present invention also provide a non-transitory computer-readable storage medium storing a computer program thereon. When executed by a processor, the computer program implements the service capacity scheduling method provided in the above embodiments, which includes, for example,: obtaining user service request information; matching the service request information with service resource information to determine target service personnel; the service resource information including one or more of service technical capabilities, service areas, and service brand categories; determining the travel planning information of the target service personnel based on the work schedule of the target service personnel and the location information of the user; and determining the arrival time of the target service personnel based on the travel planning information of the target service personnel.

[0114] In another aspect, embodiments of the present invention disclose a computer program product, which includes a computer program stored on a non-transitory computer-readable storage medium. The computer program includes program instructions, and when the program instructions are executed by a computer, the computer can execute the service capacity scheduling method provided in the above-described method embodiments, such as: obtaining user service request information; matching the service request information with service resource information to determine target service personnel; the service resource information includes one or more of service technical capabilities, service areas, and service brand categories; determining the travel planning information of the target service personnel based on the work schedule of the target service personnel and the location information of the user; and determining the arrival time of the target service personnel based on the travel planning information of the target service personnel.

[0115] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0116] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0117] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

[0118] The above embodiments are for illustrative purposes only and are not intended to limit the scope of the invention. Although the invention has been described in detail with reference to the embodiments, those skilled in the art should understand that various combinations, modifications, or equivalent substitutions of the technical solutions of the invention do not depart from the spirit and scope of the invention and should be covered within the scope of the invention.

Claims

1. A service capacity scheduling method, characterized in that, include: Obtain information about users' service requests; The service request information is matched with service resource information to determine the target service personnel; The service resource information includes one or more of the following: service technical capabilities, service areas, and service brand categories. Based on the target service personnel's work schedule and the user's location information, determine the target service personnel's travel planning information; Based on the travel planning information of the target service personnel, the arrival time of the target service personnel is determined.

2. The service capacity scheduling method according to claim 1, characterized in that, The step of matching the service request information with service resource information to determine the target service personnel includes: The service request information is parsed to determine the problem type and device type of the device to be serviced, as well as the user's location information; Determine the matching result between the service technical capabilities required to handle the problem type and the service technical capabilities in the service resource information, the matching result between the device type and the service brand category, and / or the matching result between the location information and the service area; The target service personnel are determined based on at least one of the matching results.

3. The service capacity scheduling method according to claim 1 or 2, characterized in that, The work schedule of the target service personnel is determined based on the following method: Based on the user's location information, determine the environmental tag corresponding to the address in the location information; Based on the mapping information between the environmental tags and service duration, the target service duration of the device to be served is predicted; The work schedule of the target service personnel is determined based on their existing workload and the target service duration.

4. The service capacity scheduling method according to claim 3, characterized in that, The mapping information between the environment tag and the service duration is predetermined based on the following method: Obtain the user address reported by the user from historical service tickets; Environmental identification is performed on the user address to parse one or more of the following: the user's floor information, the community information, and the building facility information; Based on at least one of the floor information, the community information, and the building facility information, predict the service duration corresponding to the address environment of the user address; Based on the matching results between the environment database and the user address, determine the environment tag of the user address; The environment database is obtained by aggregating and classifying the user addresses; Establish a mapping relationship between the service duration and the environment tag to generate mapping information.

5. The service capacity scheduling method according to claim 3 or 4, characterized in that, The service resource information also includes commuting tools; determining the work schedule of the target service personnel based on their existing workload and the target service duration includes: Based on the commuting mode, determine the commuting time of the target service personnel; Based on the service request information, determine the priority of the service order; The work schedule of the target service personnel is determined based on their existing workload, target service duration, commute time, priority, and weather information.

6. The service capacity scheduling method according to claim 3 or 4, characterized in that, The step of determining the work schedule of the target service personnel based on their existing workload and the target service duration also includes: Based on the service request information, obtain the user's identity identifier; Based on the user's identity identifier, a user profile is generated from the database; the user profile is constructed based on the user's historical service tickets. The service star rating of the target service personnel is determined based on the customer satisfaction rating information of the target service personnel. The work schedule of the target service personnel is determined based on their existing workload, target service duration, user profile, and service rating.

7. The service capacity scheduling method according to claim 1, characterized in that, The method further includes: Based on the historical service operation data of the service outlets, predict the number of work orders for the service outlets within a future set time period; the number of work orders includes the cumulative number of work orders and the number of new work orders within the future set time period. Based on the number of work orders at the service outlets within a future set time period, predict the number of service personnel required at the service outlets within the future set time period. Personnel reserves will be prepared based on the number of service personnel required for the service outlets within a specified future timeframe.

8. The service capacity scheduling method according to claim 7, characterized in that, The service resource information also includes service type; predicting the number of work orders for the service outlets within a set future time period based on their historical service operation data includes: Determine the prediction granularity; the prediction granularity includes one or more of the service area, the service brand category, and the service type; Based on the historical service operation data and the prediction granularity, the number of work orders for the service outlets within a set future time period is predicted.

9. A service capacity scheduling device, characterized in that, include: The acquisition module is used to acquire users' service request information; The target service personnel identification module is used to match the service request information with service resource information to identify the target service personnel; the service resource information includes one or more of the following: service technical capabilities, service area, and service brand category. The itinerary planning information determination module is used to determine the itinerary planning information of the target service personnel based on the work schedule of the target service personnel and the location information of the user; The on-site arrival time determination module is used to determine the on-site arrival time of the target service personnel based on their travel planning information.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the service capacity scheduling method as described in any one of claims 1 to 8.

11. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the service capacity scheduling method as described in any one of claims 1 to 8.

12. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the service capacity scheduling method as described in any one of claims 1 to 8.

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