A national IT service crowdsourcing scheduling platform system and a work order intelligent dispatching method thereof

Abstract

The application discloses a kind of national IT service crowdsourcing scheduling platform systems, including terminal access system, application service system, platform scheduling control system, scheduling decision system, engineer supervision system, execution coordination system, data storage analysis system, the terminal access system, application service system, platform scheduling control system, scheduling decision system, engineer supervision system, execution coordination system, data storage analysis system pass through standardized API gateway two-way intercommunication data, unified docking enterprise customer.The national IT service crowdsourcing scheduling platform system and its work order intelligent dispatching method disclosed in the application realize the unified scheduling of distributed IT engineer resources nationwide, greatly improve the accuracy of work order matching and the efficiency of on-site response, standardize the quality of crowdsourcing service, balance platform operation cost control and user data security, and are suitable for data center operation and maintenance, hardware and software installation and debugging, fault repair and other national offline IT on-site service scenarios.

Description

Technical Field

[0001] This invention relates to the field of IT service crowdsourcing scheduling technology, and in particular to a nationwide IT service crowdsourcing scheduling platform system and its intelligent work order dispatching method. Background Technology

[0002] An IT service crowdsourcing dispatch platform is a system for dispatching IT on-site services. With the comprehensive advancement of digital transformation, organizations and SMEs are generating a large number of offline IT on-site service needs, covering services such as server deployment, computer repair, network troubleshooting, system implementation, and data center inspection. As technology continues to develop, people's requirements for IT service crowdsourcing dispatch platform systems are also getting higher and higher.

[0003] Existing IT service models have certain drawbacks. Most existing IT service providers are regional, lacking a unified nationwide dispatch platform. Enterprise clients with cross-province, multi-site, and batch work orders must manually connect with service providers offline, making it impossible to uniformly manage nationwide service resources and resulting in fragmented supply and demand information. Traditional work order dispatch relies solely on manual allocation based on distance, failing to consider multiple factors such as engineer skill level, service reputation, time cost, regional congestion, weather, work order urgency, and skill matching. This leads to problems such as assigning high-difficulty work orders to junior engineers, leaving remote work orders unattended, duplicate work orders within the same region, and uncontrollable service costs. Furthermore, issues arise in the workflow of work order publication, engineer acceptance, on-site implementation, and acceptance. Information is not shared across different stages of the settlement process, lacking a unified online collaboration mechanism, real-time status tracking, and risk warning mechanisms. Furthermore, the lack of standardized data storage, security auditing, and a closed-loop credit evaluation system prevents long-term constraints on service providers and engineers, leading to issues such as delivery delays, substandard service quality, and settlement disputes. Existing dispatch systems only support simple proximity-based allocation, lacking capabilities for order clustering, batch work order path planning, dynamic price control, and multi-dimensional feedback correction. They also cannot dynamically adjust dispatch strategies based on real-time traffic conditions, weather, and engineer workload, resulting in severe work order congestion during peak periods and idle manpower during off-peak periods. Therefore, we propose a nationwide IT service crowdsourcing dispatch platform system and its intelligent work order dispatch method. Summary of the Invention

[0004] Technical problem solved: In response to the shortcomings of existing technologies, this invention provides a nationwide IT service crowdsourcing scheduling platform system and its intelligent work order dispatching method, which realizes unified access for service providers and engineers nationwide, multi-dimensional intelligent matching of work orders, large-scale model-assisted scheduling decision-making, online collaborative supervision throughout the entire process, and real-time feedback to dynamically correct dispatching strategies, thereby improving work order delivery efficiency, reducing overall service costs, and unifying the management of the quality of nationwide IT crowdsourcing services.

[0005] Technical Solution: To achieve the above objectives, the technical solution adopted by this invention is as follows: a nationwide IT service crowdsourcing dispatch platform system, comprising a terminal access system, an application service system, a platform dispatch control system, a dispatch decision system, an engineer supervision system, an execution collaboration system, and a data storage and analysis system. The terminal access system, application service system, platform dispatch control system, dispatch decision system, engineer supervision system, execution collaboration system, and data storage and analysis system communicate with each other bidirectionally through a standardized API gateway, and uniformly connect to enterprise customers, third-party service providers, engineer mobile terminals, and the operation management backend. The terminal access system includes a service provider module, an application access module, and an operation management module; The application service system includes a demand publishing module, a market service module, a project work module, a message notification module, and a settlement module; The platform scheduling and control system includes a task allocation module, a work hour calculation module, an order evaluation module, an intelligent scheduling module, a user authentication module, a crowdsourcing order assignment module, an access control module, and a cost assessment module. The scheduling decision system includes a large model planning module, an order clustering module, an order dispatch display module, an intelligent decision-making module, a service outlet module, a task details module, a crowdsourcing matching module, and a price control module. The engineer supervision system includes a status monitoring module, a service feedback module, an IT engineer supervision module, a task supervision module, and a credit scoring module. The execution collaboration system includes a project collaboration module, an online communication module, a delivery and acceptance module, a status tracking module, and a risk warning module. The data storage and analysis system includes a database module, a data analysis module, an operation monitoring module, a gateway module, and a security audit module.

[0006] As a preferred technical solution of this application, the intelligent scheduling module transmits signals bidirectionally with the task allocation module, work hour calculation module, order evaluation module, user authentication module, crowdsourcing order assignment module, permission management module and cost assessment module.

[0007] As a preferred technical solution of this application, the large model planning module of the scheduling decision system is equipped with a lightweight large model that is finely tuned for IT operation and maintenance scenarios, and constructs a weighted matching scoring model that includes six dimensions: geographical distance, skill matching, credit score, time adaptation, load balancing, and cost adaptation.

[0008] As a preferred technical solution of this application, the credit scoring module of the engineer supervision system sets a scoring range of 0-100 points, dynamically updates the credit score based on work order response speed, completion time, number of rework, customer evaluation, and complaint records, and sets differentiated order acceptance permission restrictions for different score ranges.

[0009] As a preferred technical solution of this application, the risk warning module of the execution collaboration system is equipped with a three-level warning mechanism, which pushes corresponding level of operation personnel to handle the corresponding scenarios of minor work order timeout, severe timeout / customer complaint, and major abnormality such as engineer loss of contact.

[0010] As a preferred technical solution of this application, the data storage and analysis system adopts a database sharding and table sharding cold and hot data separation storage architecture. The gateway module performs anonymization processing on sensitive information of customers and engineers, and the security audit module retains operation logs of the entire platform for a period of not less than 3 years.

[0011] A nationwide IT service crowdsourcing dispatch platform system comprises seven core subsystems: a terminal access system, an application service system, a platform dispatch and control system, a dispatch decision system, an engineer supervision system, an execution collaboration system, and a data storage and analysis system. Each subsystem communicates bidirectionally through a standardized API gateway, enabling unified access to various terminals, including enterprise customers, third-party service providers, engineer mobile devices, and the operations management backend. This allows for digital management of the entire lifecycle of work orders, from demand posting, intelligent dispatching, on-site execution, acceptance feedback, and settlement archiving.

[0012] Terminal access system The terminal access system is used for unified authentication access of multi-role terminals and includes a service provider module, an application access module, and an operation management module. Service Provider Module: Opens an onboarding channel for third-party IT service providers, allowing them to upload service provider qualifications, report regional service areas, and import their own engineer resources in batches; Application access module: Provides web management interface, engineer mini-program / APP, enterprise customer PC work order submission interface, and third-party business system integration interface, supporting both API and SDK integration modes; Operations Management Module: This module handles platform operations personnel account login, access permission allocation, terminal access log query, and abnormal access interception.

[0013] Application Service System The application service system is the basic support layer for platform business, including a demand publishing module, a market service module, a project work module, a message notification module, and a settlement module; Request posting module: Receives IT service tickets submitted by enterprise customers, supporting the filling in of service type, fault description, equipment model, service address, appointment time, budget limit, and required engineer skill tags; Market Services Module: Showcases nationwide dispatchable engineer resources, service network coverage, and standardized service pricing packages to enterprise clients; Project work module: For projects involving multiple devices in batches, large data center renovations, and other projects with multiple work orders, this module enables project breakdown, sub-work order binding, and overall progress summary. Message notification module: Synchronizes work order assignment, rescheduling, acceptance, and early warning information with customers, engineers, and operations personnel via SMS, APP push, and in-app messages; Settlement module: Automatically calculates the service fee for each work order, the platform service fee, and the service provider's share, and generates settlement documents and reconciliation reports.

[0014] Platform scheduling and control system The platform scheduling and control system is the basic scheduling and control hub, which includes a task allocation module, a work hour calculation module, an order evaluation module, an intelligent scheduling module, a user authentication module, a crowdsourcing order assignment module, an access control module, and a cost assessment module. User authentication module: Completes three-level real-name authentication, qualification verification, and online filing of skills certificates for enterprise customers, service providers, and crowdsourced engineers; Access control module: Based on the RBAC role-based access control model, it distinguishes the operation permissions of customers, engineers, service providers, platform operators, and super administrators; Task assignment module: Extracts basic tags from new work orders and automatically marks the service type, region, difficulty level, and skill requirements; Work Hour Calculation Module: Built-in standardized work hour database, automatically calculates standard service work hours based on work order type and implementation environment; Cost assessment module: Automatically calculates the minimum service cost for a work order by combining the average regional labor cost, working hours, material costs, and platform commission. Intelligent scheduling module: Receives the matching results output by the scheduling decision system and performs automatic order dispatch, re-dispatch, additional dispatch, and order cancellation operations; Crowdsourcing order dispatch module: Opens an order-grabbing pool to unemployed registered engineers nationwide, supporting two modes: targeted assignment and regional broadcast order grabbing; Work order evaluation module: After the work order is delivered, customer satisfaction and engineer service scores are collected and entered into the credit file simultaneously.

[0015] Scheduling Decision System The scheduling and decision-making system is the core engine of the platform's intelligent order dispatching. It is equipped with an industry-wide large model to complete multi-dimensional intelligent matching and includes a large model planning module, an order clustering module, an order dispatching display module, an intelligent decision-making module, a service outlet module, a task details module, a crowdsourcing matching module, and a price control module. Order clustering module: Clusters batch work orders by city, service type, and appointment time, merges work orders of the same type in the same region, and reduces the travel distance for engineers; Service network module: Stores the geographical location of self-operated / cooperative IT service outlets nationwide, the number of on-site engineers, and the service capabilities of the outlets; Large-scale planning module: Input multi-dimensional parameters such as work order requirements, engineer profiles, real-time traffic conditions, appointment time, and network resources, and output the optimal matching engineer candidate list; Task Details Module: Structures and parses all requirement parameters of the work order, outputting standardized feature vectors for large model calculations; Crowdsourcing matching module: Builds a multi-dimensional profile of engineers, including geographical location, skills and certificates, years of experience, historical rework rate, credit score, available time, and order acceptance threshold; Intelligent decision-making module: Set multi-level dispatch strategy priority, prioritize matching with nearby high-credit certified engineers, and automatically expand the matching radius for work orders with scarce skills; Price control module: Dynamically adjust service prices based on regional supply and demand saturation and the urgency of work orders, raising premiums during peak periods and offering preferential pricing during off-seasons; The work order display module visually displays the work order matching list, engineer distance, estimated arrival time, and overall matching score to the operations backend.

[0016] Engineer monitoring system The engineer supervision system is used for the credit and status management of crowdsourced engineers throughout their entire lifecycle, and includes a status monitoring module, a service feedback module, an IT engineer supervision module, a task supervision module, and a credit scoring module. IT Engineer Supervision Module: Unifies the management of files of registered crowdsourcing engineers nationwide, storing skills, qualifications, work experience, and service areas; Status monitoring module: Real-time acquisition of engineer online / offline status, current order status, geographical location, and number of uncompleted work orders; Task monitoring module: Tracks the entire process of a work order from order acceptance, dispatch, on-site visit, implementation, and acceptance, and automatically triggers an alert if a timeout occurs; Service feedback module: collects customer complaints, on-site fault feedback, and service provider rectification suggestions; Credit scoring module: The credit score is dynamically calculated based on order response speed, completion time, number of rework, customer reviews, and complaint records. Engineers with low scores will have their order acceptance privileges restricted.

[0017] Execution Collaboration System The execution collaboration system supports multi-party collaborative interaction during the on-site implementation phase of work orders, and includes a project collaboration module, an online communication module, a delivery and acceptance module, a status tracking module, and a risk warning module. Online communication module: Establishes an online chat channel for customers, engineers, and service providers, supporting the uploading of images, videos, and screenshots of faults; Project collaboration module: Large-scale multi-work order projects support multi-person collaboration, assigning a main person in charge and assistant engineers, and sharing implementation data synchronously; Status tracking module: Engineers can upload their location, on-site photos, and construction progress in real time via their mobile devices, and the backend displays the real-time location of work orders visually; Delivery and Acceptance Module: Online acceptance process, where customers confirm completion, sign electronic acceptance forms, and retain acceptance documents for archiving; Risk warning module: Monitors abnormal scenarios such as work order timeouts, engineer unreachability, multiple customer complaints, and cost overruns, and automatically pushes warnings to operations personnel.

[0018] Data storage and analysis system The data storage and analysis system serves as the foundation for the entire platform, providing hierarchical storage, data analysis, and security audit capabilities. It includes a database module, a data analysis module, an operation monitoring module, a gateway module, and a security audit module. Gateway module: The unified entry and exit point for data interaction across the entire system, performing traffic control, request authentication, and data anonymization for all interface requests; Database module: It adopts a database sharding and table sharding architecture, which distinguishes between customer business database, engineer resource database, work order archive database, and settlement finance database, and separates and stores hot and cold data; Data analysis module: Statistics on work order acceptance rate, on-time completion rate, average productivity per engineer, regional supply and demand gap, customer repurchase rate, and output of operation reports; Operations monitoring module: summarizes operational metrics across the entire platform, and identifies regional resource gaps, high-frequency fault types, and high-complaint work order categories; Security audit module: Records all terminal logins, work order modifications, settlement operations, and data export behaviors, generating tamper-proof audit logs to meet data compliance requirements.

[0019] A method for intelligent work order dispatching on a nationwide IT service crowdsourcing platform includes the following steps: S1. Work Order Access and Parsing: The terminal access system receives customer work orders. The demand publishing module extracts the work order address, service type, skill, urgency, and budget parameters. The task matching module standardizes the work order by tagging it and stores it in the data storage and analysis system. S2. Initial screening of engineer resources: The platform's scheduling and control system retrieves the national engineer resource pool and filters the initial set of engineers based on work order skills, service coverage, and daily load. S3. Multi-dimensional matching calculation for scheduling decisions: The scheduling decision system clusters and groups work orders, calculates the comprehensive matching score of engineers based on six dimensions, generates a candidate list for ranking, and the crowdsourcing matching module outputs the optimal engineer ranking list according to the comprehensive score. S4. Automatic work order distribution and control: The crowdsourcing order dispatch module pushes work orders to the first engineer in the sorted list, sets a fixed time limit for accepting orders, and automatically transfers the order to the next candidate if the order is not accepted within the time limit. If no one accepts the order, a risk warning is triggered and the service subsidy is increased for rematching. S5. Collaborative Implementation of Work Orders: After an engineer receives an order, he enters the execution collaboration system to synchronize the work order implementation progress in real time. Upon completion, he uploads the delivery materials, the customer conducts online acceptance, and if the acceptance is rejected, the work order is returned to the scheduling system for reassignment. S6. Service Evaluation and Credit Update: After the work order is accepted, the customer scores it online, the credit scoring module updates the engineer's credit profile, and all work order data is stored in the data storage and analysis system. S7. Feedback closed-loop model optimization: The feedback system continuously collects business data from all dimensions, periodically inputs it into the large model planning module, dynamically adjusts the weights of each matching factor, and iteratively optimizes the order dispatch matching accuracy.

[0020] As a preferred technical solution of this application, the matching factor weights in step S3 are set as follows: skill matching degree 40%, service distance 15%, engineer credit score 25%, current work order load 10%, time adaptation 5%, and cost adaptation 5%.

[0021] Beneficial Effects: Compared with existing technologies, this invention provides a nationwide IT service crowdsourcing dispatch platform system and its intelligent work order dispatching method, which has the following beneficial effects: This nationwide IT service crowdsourcing dispatch platform system and its intelligent work order dispatching method have the ability to uniformly dispatch resources across the country: By aggregating nationwide service providers and massive crowdsourced IT engineer resources through the terminal access system, and coordinating offline physical outlets with the service outlet module, it breaks the geographical limitations of a single service provider, realizes the rapid matching of technical personnel with work orders in any city across the country, and significantly shortens the on-site response time.

[0022] The large-scale model enables multi-dimensional intelligent work order dispatch, significantly improving matching accuracy: It abandons the manual single-distance work order dispatch mode and relies on a large-scale model to comprehensively consider multiple dimensions such as geography, skills, credit, working hours, and load for weighted scoring. It differentiates work orders of different urgency levels and implements differentiated work order dispatch strategies, effectively reducing mis-dispatch and rework rates, and optimizing the load balance of engineer resources.

[0023] Work order full lifecycle closed-loop management: Seven subsystems work together to cover the entire process of work order release, dispatch, on-site implementation, online acceptance, settlement, and credit update. The execution collaboration system enables multi-party online communication and real-time location tracking. The risk warning mechanism handles anomalies such as timeouts and complaints in advance, and the whole process is traceable.

[0024] Standardized Crowdsourcing Credit Supervision System: The engineer supervision system establishes a dynamic credit scoring mechanism that binds service quality, performance timeliness, customer evaluation, and order acceptance authority to constrain the service behavior of crowdsourced engineers and unify the national IT crowdsourcing service quality standards.

[0025] Data tiered storage and end-to-end security compliance: The data storage and analysis system is equipped with a unified gateway, data anonymization, and security audit modules. It separates and stores hot and cold data in databases and tables, and retains complete operation logs to meet the compliant storage requirements of enterprise customer information and engineer privacy data.

[0026] Operational data continuously iterates and optimizes the scheduling model: The massive work order matching data accumulated on the platform continuously flows back to the large model planning module, automatically optimizing the matching weights and continuously improving the accuracy of order dispatch as the platform operates; the data analysis module outputs regional supply and demand reports, which facilitates the operation to replenish scarce engineer resources in advance.

[0027] Reduce overall costs for both supply and demand: The order clustering module merges similar work orders in the surrounding area to reduce round-trip costs, while the cost assessment and price control modules standardize working hours and quotations to avoid disorderly price increases; enterprise customers do not need to build their own nationwide engineering teams, and small and medium-sized engineers can obtain nationwide orders by relying on the platform, achieving cost reduction and efficiency improvement for both supply and demand. Attached Figure Description

[0028] Figure 1 This is a schematic diagram of the overall structure of a nationwide IT service crowdsourcing dispatch platform system and its intelligent work order dispatching method according to the present invention.

[0029] Figure 2 This is a schematic diagram of the platform scheduling and control system in the nationwide IT service crowdsourcing scheduling platform system and its intelligent work order dispatching method of the present invention.

[0030] Figure 3 This is a schematic diagram of the scheduling decision system in the nationwide IT service crowdsourcing scheduling platform system and its intelligent work order dispatching method of the present invention.

[0031] Figure 4 This is a schematic diagram of the engineer supervision system in the nationwide IT service crowdsourcing dispatch platform system and its intelligent work order dispatching method of the present invention.

[0032] Figure 5 This is a schematic diagram of the application service system in the nationwide IT service crowdsourcing dispatch platform system and its intelligent work order dispatching method of the present invention.

[0033] Figure 6 This is a schematic diagram of the terminal access system in the nationwide IT service crowdsourcing dispatch platform system and its intelligent work order dispatching method of the present invention.

[0034] Figure 7 This is a schematic diagram of the data storage and analysis system in the nationwide IT service crowdsourcing dispatch platform system and its intelligent work order dispatching method of the present invention.

[0035] Figure 8 This is a schematic diagram of the execution collaboration system in the nationwide IT service crowdsourcing scheduling platform system and its intelligent work order dispatching method of the present invention. Detailed Implementation

[0036] The technical solution of the present invention will be clearly and completely described below with reference to the accompanying drawings and specific embodiments. However, those skilled in the art will understand that the embodiments described below are some embodiments of the present invention, but not all embodiments, and are only used to illustrate the present invention, and should not be regarded as limiting the scope of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention. Where specific conditions are not specified in the embodiments, conventional conditions or conditions recommended by the manufacturer shall be followed. Where the manufacturers of reagents or instruments are not specified, they are all conventional products that can be purchased commercially.

[0037] In the description of this invention, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing the invention and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0038] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0039] like Figure 1-8 As shown, a nationwide IT service crowdsourcing dispatch platform system includes a terminal access system, an application service system, a platform dispatch control system, a dispatch decision system, an engineer supervision system, an execution collaboration system, and a data storage and analysis system. The terminal access system, application service system, platform dispatch control system, dispatch decision system, engineer supervision system, execution collaboration system, and data storage and analysis system communicate with each other bidirectionally through a standardized API gateway, and uniformly connect to enterprise customers, third-party service providers, engineer mobile terminals, and the operation management backend. The terminal access system includes a service provider module, an application access module, and an operation management module; The application service system includes a demand publishing module, a market service module, a project work module, a message notification module, and a settlement module. The platform scheduling and control system includes a task allocation module, a work hour calculation module, an order evaluation module, an intelligent scheduling module, a user authentication module, a crowdsourcing order assignment module, a permission management module, and a cost assessment module. The scheduling and decision-making system includes a large-scale model planning module, an order clustering module, an order dispatch display module, an intelligent decision-making module, a service outlet module, a task details module, a crowdsourcing matching module, and a price control module. The engineer monitoring system includes a status monitoring module, a service feedback module, an IT engineer monitoring module, a task monitoring module, and a credit scoring module. The execution collaboration system includes a project collaboration module, an online communication module, a delivery and acceptance module, a status tracking module, and a risk warning module. The data storage and analysis system includes a database module, a data analysis module, an operations monitoring module, a gateway module, and a security audit module.

[0040] The intelligent scheduling module transmits signals bidirectionally with the task allocation module, work hour calculation module, order evaluation module, user authentication module, crowdsourcing order assignment module, permission management module, and cost assessment module.

[0041] The scheduling decision system's large model planning module is equipped with a lightweight large model that is fine-tuned for IT operation and maintenance scenarios. It constructs a weighted matching and scoring model that includes six dimensions: geographical distance, skill matching, credit score, time adaptation, load balancing, and cost adaptation.

[0042] The engineer supervision system's credit scoring module sets a scoring range of 0-100 points. The credit score is dynamically updated based on work order response speed, completion time, number of rework, customer evaluation, and complaint records. Differentiated order acceptance permissions are set for different score ranges.

[0043] The risk warning module of the collaborative system is equipped with a three-level warning mechanism, which pushes corresponding level of operation personnel to handle the situation for minor work order timeouts, severe timeouts / customer complaints, and major abnormal scenarios such as engineers being out of contact.

[0044] The data storage and analysis system adopts a sharded database and table architecture that separates hot and cold data. The gateway module performs anonymization processing on sensitive information of customers and engineers, and the security audit module retains operation logs across the entire platform for no less than 3 years.

[0045] Intelligent work order dispatching method A method for intelligent work order dispatching applied to the aforementioned national IT service crowdsourcing dispatch platform system includes the following steps: S1. Standardized Work Order Entry and Feature Extraction Enterprise customers submit IT service work orders through the terminal access system. The demand publishing module collects basic work order information; the task allocation module automatically extracts work order feature tags: service city, detailed address, service category, hardware / software skill requirements, scheduled on-site time, urgency level, budget limit, and work order difficulty; the task details module converts all features into structured parameter vectors and transmits them to the scheduling decision system.

[0046] S2, Order Clustering and Regional Resource Pre-screening The order clustering module clusters current work orders awaiting assignment in batches by city, service category, and appointment time, and merges work orders within the same area; the service outlet module retrieves all self-operated outlets and cooperative outlets with on-site engineers in the city to which the work order belongs; the crowdsourcing matching module retrieves the basic profiles of available crowdsourcing engineers in the city and its surrounding area to complete the first round of resource screening, eliminating engineers whose skills do not match, whose credit scores are below the threshold, or whose service areas do not cover the address.

[0047] S3, Large Model Multidimensional Comprehensive Matching and Scoring The large-scale model planning module receives the work order parameter vector and the engineer profile data after preliminary screening, and calculates the comprehensive matching score: ① Geographic distance weighting: The straight-line distance from the engineer's real-time location to the work order service address and the travel time; ② Skill matching weight: The degree of overlap between the engineer's certified skills and the technical tags required for the work order; ③ Credit score weighting: Engineer's historical credit score, rework rate, and deductions for complaint records; ④ Time-matching weight: The degree of overlap between the engineer's free time and the work order appointment window; ⑤ Load balancing weight: The number of unfinished work orders currently held by the engineer, to avoid over-assigning work orders; ⑥ Cost-fit weighting: The degree of matching between the engineer's service quote and the work order budget; The large model outputs a list of engineer candidates sorted from highest to lowest overall score.

[0048] S4, Intelligent Decision-Making and Hierarchical Order Dispatch The intelligent decision-making module executes differentiated dispatch strategies based on the urgency level of the work order: Level 1 Emergency Work Order (Fault Downtime, System Paralysis): The work order will be automatically pushed to the engineer with the highest overall score. If the work order is not accepted within 5 minutes, it will be automatically pushed to the second highest scorer. At the same time, the work order will be pushed to the operations team for backup. Level 2 Regular Work Orders (Installation, Debugging, Routine Maintenance): The top 5 high-scoring engineers are allowed to enter the regional order-grabbing pool. They have 10 minutes to grab the order. If no one grabs the order, the best candidate will be automatically assigned. Level 3 appointment work order (non-urgent long-term implementation): All matched engineers are pushed simultaneously, and engineers can independently schedule and accept orders; After the order is dispatched, the intelligent scheduling module pushes the order dispatch result to the terminal access system simultaneously, and the message notification module pushes reminders to the customer and engineer respectively.

[0049] S5, Work Order Execution Full-Process Collaboration and Status Tracking After an engineer accepts an order, the workflow of the collaborative system is executed: the online communication module supports real-time communication among the three parties; the engineer continuously uploads location and on-site construction materials on their mobile device, and the status tracking module updates the work order progress in real time; if there is a timeout, loss of contact, or customer objection, the risk warning module generates a warning message and pushes it to the platform operations personnel for intervention and coordination.

[0050] S6. Completion Acceptance, Credit Update and Data Archiving After the engineer completes the on-site service, they initiate an online delivery and acceptance process. Once the customer confirms the acceptance, the dispatch and evaluation module collects customer feedback and scores. The credit scoring module updates the engineer's credit profile based on the performance of this work order. The settlement module generates settlement documents for working hours and service fees. All work order data is synchronously written to the data storage and analysis system for archiving, and the data analysis module synchronously updates regional supply and demand and engineer capacity operation indicators.

[0051] S7, Order Dispatch Data Iterative Optimization The data storage and analysis system continuously accumulates work order matching, completion, and complaint data, and periodically feeds it back to the scheduling decision system's large model planning module to dynamically adjust the weights of each matching dimension and continuously optimize the accuracy of subsequent work order matching.

[0052] Example 1: Complete Intelligent Scheduling Process for IT Data Center Maintenance Work Orders Nationwide like Figure 1 As shown, the overall platform system of this invention consists of seven subsystems: terminal access system, application service system, platform scheduling and control system, scheduling decision system, engineer supervision system, execution collaboration system, and data storage and analysis system. The subsystems communicate with each other through a unified gateway module.

[0053] Work order submission stage A corporate customer submits a server fault repair work order through the PC work order backend of the application access module within the terminal access system. The customer fills in the service address, data center hardware fault, required server maintenance engineer, emergency level 1, and schedules immediate on-site service. The application service system's demand publishing module receives the work order and stores the basic information, while the task allocation module extracts the work order's feature tags and transmits them to the platform's scheduling and control system.

[0054] Work order preprocessing and resource screening The scheduling decision system's order clustering module retrieves work orders to be assigned within a 3-kilometer radius of the city where the work order is located; if there are no similar work orders, they do not need to be merged. The service outlet module retrieves on-site engineers from two local partner data center service outlets. The crowdsourcing matching module screens 12 crowdsourcing engineers in the city who hold server operation and maintenance qualifications, have a credit score of ≥70, and are currently available, completing the initial screening.

[0055] Large model matching, scoring, and order dispatching The large-scale model planning module takes work order features and profiles of 12 engineers as input, calculates a comprehensive score based on six dimensions: distance, skills, credit, time, workload, and cost, and outputs a list of the top 5 engineers. The intelligent decision-making module determines the work order as a first-level urgent work order and automatically pushes the assigned work order to the first engineer. The engineer accepts the work order on the mobile device within 3 minutes.

[0056] On-site collaborative supervision After receiving an order, the engineer enters the execution collaboration system and remotely confirms the data center fault with the customer through the online communication module; the status tracking module uploads the engineer's location in real time, and the risk warning module monitors the estimated arrival time in real time; after the engineer arrives on site, he uploads photos of the equipment fault, and the work order status is updated synchronously during the implementation process.

[0057] Acceptance, credit update and data archiving After the fault is repaired, the engineer initiates online delivery and acceptance. The customer electronically signs to confirm completion and gives a five-star rating. The dispatch evaluation module collects the evaluation data and transmits it to the engineer's supervision system credit scoring module, and the engineer's credit score increases by 2 points for the month. The settlement module calculates the standard working hours based on the working hour calculation module to generate a settlement bill. The entire work order data is encrypted and stored in the data storage and analysis system database module. The safety audit module records all operation logs for this dispatch, acceptance, and settlement.

[0058] Model Iterative Optimization Every day at midnight, the data analysis module summarizes all work order matching, completion, and complaint data for the day, and feeds it back to the large model planning module in batches. It automatically fine-tunes the skill matching weights for server maintenance work orders and continuously optimizes the matching accuracy of subsequent similar work orders.

[0059] Example 2: Clustering and Scheduling of Batch Office Equipment Installation Work Orders A company submitted a work order for 20 computer installations, located on the 3rd, 5th, and 7th floors of the same office building, scheduled for the following morning. The order clustering module automatically merged work orders from the same office building and at the same time. The large-scale planning module prioritized matching engineers in the vicinity of the office building who could handle batch installations and were skilled in desktop maintenance, assigning two engineers to perform the installations simultaneously on different floors. This significantly reduced the need for individual engineers to travel back and forth multiple times. The cost assessment module calculated and merged work orders to standardize working hours, reducing the company's service fee expenses. The full-process task monitoring module simultaneously monitored the progress of the two engineers, and upon completion, a unified online batch acceptance was conducted.

[0060] Example 3: Low-Credit Engineer Management Mechanism A crowdsourcing engineer completed three consecutive orders late and received two customer complaints. The credit scoring module lowered his credit score from 72 to 58. The platform's dispatch and control system's permission management module automatically restricted the engineer from receiving first-level emergency work orders and allowed him to accept only third-level long-term appointment work orders. The engineer supervision system pushed a rectification notice. After completing online service standard training and passing the assessment, his credit score was gradually restored, and the order-accepting restriction was lifted.

[0061] Working Principle: This invention's platform uses a data storage and analysis system as its underlying data foundation. The terminal access system uniformly accepts requests from customers, service providers, and engineers across all channels. The application service system handles basic business processes such as work order publishing, project management, message notifications, and settlement. The platform's scheduling and control system implements user authentication, access control, time cost calculation, and basic work order routing. The scheduling decision system, as the core intelligent engine, relies on an industry-fine-tuned large model to complete work order clustering, multi-dimensional engineer profile matching, dynamic pricing, and work order strategy output. The engineer monitoring system continuously collects service feedback and dynamically updates engineer credit files. The execution collaboration system supports multi-party communication, progress tracking, and risk warnings at work order sites. Data from all subsystems flows back to the data storage and analysis system in real time for storage, statistics, and security auditing. The accumulated operational data is used to reverse-optimize the large model's matching weights, forming a closed-loop intelligent scheduling logic of "work order entry - intelligent work order dispatch - on-site implementation - acceptance evaluation - credit update - data iteration," achieving standardized, automated, and precise scheduling of nationwide distributed IT crowdsourcing resources.

[0062] It should be noted that, in this document, relational terms such as first and second (number one, number two), etc., are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0063] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the claimed invention.

Claims

1. A nationwide IT service crowdsourcing dispatch platform system, comprising a terminal access system, an application service system, a platform dispatch and control system, a dispatch decision system, an engineer monitoring system, an execution collaboration system, and a data storage and analysis system, characterized in that: The terminal access system, application service system, platform scheduling and control system, scheduling decision system, engineer supervision system, execution collaboration system, and data storage and analysis system communicate with each other bidirectionally through a standardized API gateway, and uniformly connect with enterprise customers, third-party service providers, engineer mobile terminals, and the operation and management backend; The terminal access system includes a service provider module, an application access module, and an operation management module; The application service system includes a demand publishing module, a market service module, a project work module, a message notification module, and a settlement module; The platform scheduling and control system includes a task allocation module, a work hour calculation module, an order evaluation module, an intelligent scheduling module, a user authentication module, a crowdsourcing order assignment module, an access control module, and a cost assessment module. The scheduling decision system includes a large model planning module, an order clustering module, an order dispatch display module, an intelligent decision-making module, a service outlet module, a task details module, a crowdsourcing matching module, and a price control module. The engineer supervision system includes a status monitoring module, a service feedback module, an IT engineer supervision module, a task supervision module, and a credit scoring module. The execution collaboration system includes a project collaboration module, an online communication module, a delivery and acceptance module, a status tracking module, and a risk warning module. The data storage and analysis system includes a database module, a data analysis module, an operation monitoring module, a gateway module, and a security audit module.

2. The nationwide IT service crowdsourcing dispatch platform system according to claim 1, characterized in that: The intelligent scheduling module communicates bidirectionally with the task allocation module, work hour calculation module, order evaluation module, user authentication module, crowdsourcing order assignment module, permission management module, and cost assessment module.

3. The nationwide IT service crowdsourcing dispatch platform system according to claim 1, characterized in that: The scheduling decision system's large model planning module is equipped with a lightweight large model that is fine-tuned for IT operation and maintenance scenarios. It constructs a weighted matching and scoring model that includes six dimensions: geographical distance, skill matching, credit score, time adaptation, load balancing, and cost adaptation.

4. The nationwide IT service crowdsourcing dispatch platform system according to claim 1, characterized in that: The engineer supervision system's credit scoring module sets a scoring range of 0-100 points. The credit score is dynamically updated based on work order response speed, completion time, number of reworks, customer evaluations, and complaint records. Differentiated order acceptance permissions are set for different score ranges.

5. The nationwide IT service crowdsourcing dispatch platform system according to claim 1, characterized in that: The risk warning module of the execution collaboration system is equipped with a three-level warning mechanism, which pushes corresponding level of operation personnel to handle the corresponding abnormal scenarios such as minor work order timeout, severe timeout / customer complaint, and engineer loss of contact.

6. The nationwide IT service crowdsourcing dispatch platform system according to claim 1, characterized in that: The data storage and analysis system adopts a sharded database and table architecture that separates hot and cold data. The gateway module performs anonymization processing on sensitive information of customers and engineers, and the security audit module retains operation logs across the entire platform for no less than 3 years.

7. A method for intelligent work order dispatching on a nationwide IT service crowdsourcing platform, characterized in that: Specifically, the following steps are included: S1. Work Order Access and Parsing: The terminal access system receives customer work orders. The demand publishing module extracts the work order address, service type, skill, urgency, and budget parameters. The task matching module standardizes the work order by tagging it and stores it in the data storage and analysis system. S2. Initial screening of engineer resources: The platform's scheduling and control system retrieves the national engineer resource pool and filters the initial set of engineers based on work order skills, service coverage, and daily load. S3. Multi-dimensional matching calculation for scheduling decisions: The scheduling decision system clusters and groups work orders, calculates the comprehensive matching score of engineers based on six dimensions, generates a candidate list for ranking, and the crowdsourcing matching module outputs the optimal engineer ranking list according to the comprehensive score. S4. Automatic work order distribution and control: The crowdsourcing order dispatch module pushes work orders to the first engineer in the sorted list, sets a fixed time limit for accepting orders, and automatically transfers the order to the next candidate if the order is not accepted within the time limit. If no one accepts the order, a risk warning is triggered and the service subsidy is increased for rematching. S5. Collaborative Implementation of Work Orders: After an engineer receives an order, he enters the execution collaboration system to synchronize the work order implementation progress in real time. Upon completion, he uploads the delivery materials, the customer conducts online acceptance, and if the acceptance is rejected, the work order is returned to the scheduling system for reassignment. S6. Service Evaluation and Credit Update: After the work order is accepted, the customer scores it online, the credit scoring module updates the engineer's credit profile, and all work order data is stored in the data storage and analysis system. S7. Feedback closed-loop model optimization: The feedback system continuously collects business data from all dimensions, periodically inputs it into the large model planning module, dynamically adjusts the weights of each matching factor, and iteratively optimizes the order dispatch matching accuracy.

8. The intelligent work order dispatching method for a nationwide IT service crowdsourcing dispatching platform according to claim 7, characterized in that: In step S3, the matching factor weights are set as follows: skill matching degree 40%, service distance 15%, engineer credit score 25%, current work order load 10%, time fit 5%, and cost fit 5%.

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