System and method for scheduling work schedule and non-transitory computer-readable medium

Abstract

One aspect of this disclosure is a system for scheduling work trips. The system includes a data loading module for loading work data related to the work trips. The system also includes a calculation module, connected via communication with the data loading module, to generate work order sorting based on the work data. The system also includes a route planning module, connected via communication with the calculation module, to generate route data based on the work order sorting. The system also includes a location determination module, connected via communication with the route planning module, to determine whether the work trip has been completed based on vehicle movement information and route data. If the work trip is determined to be completed, the system records the vehicle's destination time and destination location. If the work trip is determined not to be completed, the system continues to determine whether the work trip has been completed based on the vehicle's movement information and route data. The computer program also includes an output module for outputting the vehicle's movement information, destination time, and destination location.

Description

Technical Field

[0001] This invention relates to a technique for scheduling work processes, and more particularly to a method, system, and non-volatile computer-readable storage medium for scheduling work processes applied to maintenance tasks. Prior Technology

[0002] In specific application scenarios, such as street light or charging pile maintenance, maintenance workers typically need to report their actual maintenance routes to ensure transparency and traceability of the work process. This can be achieved using Global Positioning System (GPS) technology to collect GPS data on maintenance worker movements. However, simply reporting the worker's maintenance route lacks a dynamic adjustment mechanism, failing to optimize movement costs and work time. Furthermore, GPS records can be affected by drift points or anomalies, reducing the accuracy of route determination, such as leading to inaccurate determination of the start and end points of the work. Therefore, there is a need for technology that can calculate dynamic parameters such as speed changes and total travel time while processing GPS data for maintenance work routes. Summary of the Invention

[0003] According to a first aspect of the present invention, a system for scheduling work trips is provided. The system includes a data loading module for loading work data related to the work trip. The system also includes a calculation module, communicatively connected to the data loading module, to generate work order sorting based on the work data. The system also includes a route planning module, communicatively connected to the calculation module, to generate route data based on the work order sorting. The system also includes a location determination module, communicatively connected to the route planning module, to determine whether the work trip has been completed based on vehicle movement information and route data. If the work trip is determined to be completed, the vehicle's destination time and destination location are recorded. If the work trip is determined not to be completed, the system continues to determine whether the work trip has been completed based on the vehicle's movement information and route data. The computer program also includes an output module for outputting the vehicle's movement information, destination time, and destination location.

[0004] According to a second aspect of the present invention, a method for scheduling work trips is provided, which can be executed by a computer device. The method for scheduling work trips includes loading work data related to the work trips. The method for scheduling work trips also includes generating a work order order based on the work data. The method for scheduling work trips also includes generating path data based on the work order order order. The method for scheduling work trips also includes detecting vehicle movement information. Based on the movement information and the path data, it is determined whether the work trip has been completed. If the work trip is determined to be completed, the vehicle's destination time and destination location are recorded. If the work trip is determined not to be completed, the method continues to determine whether the work trip has been completed based on the movement information and the path data. The method for scheduling work trips also includes outputting the vehicle's movement information, destination time, and destination location.

[0005] According to a third aspect of the present invention, a non-volatile computer-readable storage medium is provided for use in a computing device or computer, which stores instructions for executing a method of scheduling work processes as proposed in the second aspect of the present invention.

[0006] The foregoing description is not intended to represent every embodiment or aspect of the invention. Rather, it provides only examples of some novel aspects and features of the invention. The foregoing description will become apparent, as well as other features and advantages of the invention, from the following detailed description of representative embodiments and modes of implementation when taken in conjunction with the accompanying drawings and the claims. Other aspects of the invention will be apparent to those skilled in the art from the detailed description of various embodiments with reference to the drawings and the brief description provided below.

[0007] To provide a better understanding of the above and other aspects of the present invention, specific embodiments are described below in conjunction with the accompanying drawings: Simple Explanation of the Diagram

[0008] Figure 1 illustrates a functional block diagram of a computer program product according to various embodiments of the present invention. Figure 2 illustrates a flowchart of a scheduling work process according to various embodiments of the present invention. Implementation

[0009] The following detailed embodiments of the present invention, illustrated in the accompanying drawings. In addition to these detailed descriptions, the present invention can be widely implemented in other embodiments, and any easy substitutions, modifications, or equivalent changes to the described embodiments are included within the scope of the present invention and are subject to the following patent claims. In the description of the specification, many specific details and implementation examples are provided to give the reader a more complete understanding of the present invention; however, these specific details and implementation examples should not be considered as limitations on the present invention. Furthermore, well-known steps or elements are not described in the details to avoid unnecessary limitations on the present invention. In the drawings, the same or similar element symbols are used to represent the same or similar elements.

[0010] Figure 1 illustrates a functional block diagram of a system 1 for scheduling work trips according to various embodiments of the present invention. The computer program for scheduling work trips provided according to various embodiments of the present disclosure can be mainly applied to maintenance scenarios of infrastructure such as streetlights and charging piles. It uses the trajectory data of GPS movement information of vehicles used for maintenance and analyzes it with relevant models to accurately and automatically record maintenance paths for planning or outputting complete work trips.

[0011] System 1 for scheduling work trips includes a data loading module 11, a calculation module 12, a route planning module 13, an information preprocessing module 14, a location determination module 15, and an output module 16. The data loading module 11 is communicatively coupled to the calculation module 12, the calculation module 12 is coupled to the route planning module 13 and the information preprocessing module 14, the location determination module 15 is coupled to the route planning module 13 and the information preprocessing module 14, and the output module 16 is coupled to the location determination module 15. The data loading module 11 is used to load work data related to the work trip. The work data may include multiple work orders, and the corresponding work location, priority, and remaining maintenance time for each work order.

[0012] Specifically, the system 1 for scheduling work processes can be built on electronic devices with appropriate computing mechanisms, such as the same (or different) servers (e.g., general-purpose servers, file servers, storage unit servers, etc.) and computers (e.g., personal computers, laptops, tablets, etc.). The modules in the system 1 for scheduling work processes can be software, hardware, or firmware. If it is hardware, it can be a processing unit, processor, computer, or server with data processing and computing capabilities. If it is software or firmware, it can include instructions executable by the processing unit, processor, computer, or server, and can be installed on the same hardware device or distributed across multiple different hardware devices. Furthermore, the system 1 for scheduling work processes includes hard drives (e.g., mechanical hard drives, solid-state hard drives, etc.), memory, other storage devices, or combinations of these devices.

[0013] The calculation module 12 is used to generate work order sorting based on the aforementioned work data, and can dynamically adjust the work order sorting. Specifically, it can evaluate the importance of each work order based on its priority score to ensure that high-priority tasks can be completed in a timely manner. It also calculates the most suitable dispatch order by taking into account parameters such as comprehensive fault level, waiting time, and customer importance, and uses a weight adjustment mechanism to automatically adapt to different work needs, without limitation.

[0014] The path planning module 13 is used to generate path data based on the aforementioned work order sorting. Specifically, the path planning module 13 calculates and selects the optimal repair sequence (or repair path) based on the priority score of each work order and the distance between the corresponding work positions of each work order. The path planning module 13 may, for example, apply a greedy algorithm to generate preliminary path data to ensure that the travel time of the vehicle used for repair is minimized as much as possible and to improve the efficiency of the trip. In some embodiments, the path planning module 13 selects the work position of the work order with the highest priority score as the first target point according to the work order sorting, and calculates multiple next target points sequentially based on the distance between the current position of the vehicle being repaired and the work positions of the uncompleted work orders, as well as the priority scores of the uncompleted work orders, and generates path data based on the first target point and the multiple next target points. When the status of a work order changes, such as when a change work order is inserted during the trip, the route planning module 13 can be updated and generated in real time by using the aforementioned data loading module 11 and calculation module 12, so as to adjust the route of the trip in real time.

[0015] The information preprocessing module 14 can be used to detect vehicle movement information and preprocess and filter anomalies in the GPS data within the movement information. Specifically, the Haversine formula can be used to calculate the distance between each working position to ensure that the movement trajectory of the vehicle used for maintenance is reasonable, and speed thresholds can be used to filter out abnormal data to ensure recording accuracy, automatically ignore GPS drift points, and improve the accuracy of path analysis.

[0016] The location determination module 15 can be used to determine whether a work trip has been completed based on movement information and path data. When the work trip is determined to be completed, the vehicle's destination time and location are recorded. Furthermore, the location determination module 15 can record the timestamp of the vehicle's arrival at the work location of each work order based on the vehicle's GPS coordinates and the work location of each work order. Combined with the aforementioned information, automated start and end point detection can be achieved. Through algorithms, the location determination module 15 can automatically identify the starting and ending points of the vehicle used for maintenance during its work trip, improving the accuracy and reliability of work trip data recording. For example, determining the starting point of movement can be achieved by automatically recording the start of the trip when the vehicle used for maintenance moves more than 200 meters and its speed exceeds 50 km / h, without requiring manual input. Determining the ending point of movement can be achieved by automatically determining the end of the trip when the vehicle used for maintenance returns to a specific location (e.g., the company) within 50 meters and the interval between this return and the previous recording point exceeds one hour.

[0017] Output module 16 can be used to output information about the completed trips for vehicle repair, including travel information, destination time, and destination location. By outputting the completed trip information, the repair of vehicles can be made transparent and management efficiency can be improved.

[0018] The following will describe in more detail the techniques for scheduling work processes provided according to various embodiments of this disclosure. Input parameters for inputting work data into the loading data module 11 include the number of accepted jobs and the job location (GPS) of each job, priority (the higher the value, the more important), and remaining repair time. Geographic information parameters used and / or calculated by the calculation module 12, the route planning module 13, the information preprocessing module 14, or the location determination module 15 may include the path distance between work locations (represented by a distance matrix calculated from GPS data), anomalies (GPS data threshold), and start / end point determination ranges (such as start point radius, end point radius, start point speed, and end point speed).

[0019] Specifically, the computing module 12 can use the GPS coordinates of each work location to calculate the distance matrix between the work locations corresponding to each work order, and can use the Haversine algorithm or the map API (Application Programming Interface) to perform distance calculation.

[0020] Next, the calculation module 12 can calculate the priority score for each work order based on its priority and remaining repair time. Where α and β are weighting coefficients used to adjust the proportion of influence of priority and remaining time.

[0021] Priority indicates the urgency level of a work order and is typically determined by the following factors (indicators): Severity, Waiting Time, Customer Importance, and Service Level Agreement (SLA). Severity can be categorized as, for example, from Level 1 to Level 5, with Level 5 being the most severe. Waiting Time is the time a customer waits for repairs, measured in hours. Customer Importance is also categorized as, for example, from Level 1 to Level 5, with Level 5 being the most important. The Service Level Agreement (SLA) is categorized as, for example, from Level 1 to Level 5, with Level 5 being the highest level of restriction.

[0022] Priority levels are typically set from 1 to 5 (5 being the highest), and can be calculated using weighted summation, as shown in the following equation (1): (1)

[0023] w1 to w4 are weighting coefficients (which can be adjusted according to maintenance needs). Each indicator needs to be standardized so that the final priority level falls between 1 and 5.

[0024] In an example of priority calculation, we can assume the following values ​​for the factors (indicators) of a work order: Severity = 5 (highest fault level), Waiting Time = 8 hours, Customer Importance = 3 (normal customer), and SLA Penalty = 2 (medium). The weights are set as w1 = 2.0 (most important fault level), w2 = 1.5, w3 = 1.0, and w4 = 1.2. According to the above equation (1), we can derive: Through standardization: The maximum value is calculated as: the maximum fault level. Maximum waiting time of the day Maximum Customer Importance SLA Penalty Maximum Value .

[0025] The remaining repair time represents the remaining repair time for this work order. When the system creates a work order, it will automatically generate a latest time that the repair must be completed, which is usually 72 hours (3 days). The remaining repair time indicates how much time is left before the latest time that the repair must be completed.

[0026] In one embodiment, the weighting coefficients of α and β can be calculated using a data-driven approach, for example, based on historical data, such as the example data in Table (1) below: Work order ID Priority Remaining Repair Time Actual completion order 102 4 1 hour 1 101 5 2 hours 2 104 2 0.5 hours 3 103 3 1.5 hours 4 Table (1)

[0027] First, calculate module 12 or establish a regression model through other calculation software (such as Matlab) to find α and β. The regression equation can be set as shown in the following equation (2): (2)

[0028] Next, the data in the above table (1) is converted into the following table (2): Work order ID Priority Remaining Repair Time 102 4 1 hour 1.000 101 5 2 hours 0.500 104 2 0.5 hours 0.333 103 3 1.5 hours 0.250 Table (2)

[0029] Next, based on the above table (2), the equation is established as follows:

[0030] Next, the least squares method is used to find approximate solutions for α and β: Let AX = B The standard formula for least multiplication is:

[0031] Therefore, we can conclude that α≈0.396 and β≈0.692.

[0032] The path data generated by the path planning module 13 can be used to establish a preliminary path in the following ways. First, set the starting point of the path (e.g., the location of the company). Next, sort the work orders according to their priority scores and select the work order with the highest priority score as the first target point. Based on the distance matrix, calculate the distance from the current location to other incomplete work orders, combine the distance with the priority score, and evaluate the next target point as shown in the following equation (3): (3)

[0033] Here, γ and δ are weighting coefficients used to balance the influence of priority and distance. Next, an initial path is generated using a heuristic algorithm (such as the nearest neighbor algorithm or the greedy algorithm), and the weighting coefficients γ and δ are calculated in the same way as α and β described above.

[0034] The path data generated and output by the path planning module 13 may include a list of work paths and corresponding visual path diagrams, and may include recommended maintenance paths, including the maintenance sequence, estimated arrival time and completion time of each work order.

[0035] The information preprocessing module 14 can preprocess and filter GPS data for anomalies using GPS coordinates from vehicles used for maintenance, filtering out abnormal data points (such as drift points) to ensure data accuracy and stability. For example, it can calculate whether data points from two GPS coordinates are within a reasonable distance, based on the distance formula. The speed v (m / s) can be obtained, where ∆x represents the distance between two points, and ∆t represents the time interval. For example, for a vehicle used for maintenance with a speed of 110 km / h, the abnormal data threshold (max_speed_threshold) is approximately 30.56 m / s. If the speed v is greater than 0 and less than 30.56 m / s, it indicates that the speed is a reasonable value, and the data at that location point should be recorded.

[0036] The calculation module 12 can also be used for speed and time calculations. Specifically, based on the location (GPS) and corresponding timestamp of the vehicle used for maintenance obtained from the information preprocessing module 14, the real-time speed and average speed of the vehicle used for maintenance along its path between various work locations can be calculated. Then, the work start time and end time can be used to calculate the total travel time (total travel time).

[0037] The location determination module 15 automatically identifies the starting and ending points of the vehicle's movement during the work journey, which is the detection of the starting and ending points of the work journey. When the vehicle's latest position leaves the range (e.g., the work start position) by more than 200 meters from the starting point radius and the time exceeds 50 kilometers, the geographical information can be set as the starting point of the movement. When the vehicle's latest position enters the range (e.g., the work start position) by more than 50 meters from the ending point radius and the distance from the previous point exceeds 1 hour and the speed does not exceed 20 kilometers per hour, it is considered to have returned to the origin, and the geographical information can be set as the ending point of the movement.

[0038] When a work order status changes or a new work order is detected, such as when data is added to the data loading module 11, the calculation module 12 can recalculate the priority score of all work orders based on the new work data. The route planning module 13 can then re-evaluate the next score of the target point to ensure that the currently selected next work order is still the best choice, thereby updating and generating new route data in real time to adjust the route in real time. Specifically, when the next score changes, the candidate work order list is reordered, a new target point is selected, and the route is dynamically updated. The triggering conditions and execution timing for real-time route adjustment are shown in the following table (3): Triggering conditions Execute action New work order added Recalculate the score, adjust the next score, and update the target point. Existing work orders completed Remove completed work orders and select the next best work order. Table (3)

[0039] Through the aforementioned operations—loading work data (initialization), establishing distance and priority matrices (calculation), calculating the priority score for each work order based on a weighted model (modeling), generating the optimal path, including a path list and a visualized path map (e.g., using the Google Maps API) (path result output), filtering abnormal geographical information (real-time information preprocessing), and detecting whether the work order has left the starting point or returned to the origin (start and end point detection)—a complete maintenance path can be generated (trip result output). The trip result output can include recommended maintenance paths (e.g., sequence: work order 1 → work order 2 → work order 3 → …), the completion time of each work order (estimated completion time), a visualized map, and a path map (marking the work location of each work order and the movement path between work locations).

[0040] The following is an example of a work order priority score ranking. Assume there are 4 maintenance work orders on the same day, as shown in the table below (4). The system calculates the priority score based on the priority and the remaining time. Work order ID Priority Remaining Repair Time 001 5 2 hours 002 4 1 hour 003 3 1.5 hours 004 2 0.5 hours Table (4)

[0041] The calculation formula is And setting α≈1.37 (weight of priority influence) and β≈1.68 (weight of remaining time influence), the calculated priority score is shown in the table below (5): Work order ID Score Calculation Priority score (Score) 001 3.5 002 3.8 003 1.6 004 2.0 Table (5)

[0042] According to the table (5) above, the system selects work order 002 as the first target point based on the priority score.

[0043] The following is an example of establishing a preliminary path. The starting point of vehicle A used by the staff for maintenance is set as the company. Based on the priority score mentioned above, work order 002 is selected as the first target point, and the distances from work order 002 to the work locations of other work orders are calculated as shown in the table below (6): Target work order Longitude Latitude Distance (km) 001 121.570 25.040 3.2 003 121.580 25.050 4.5 004 121.590 25.060 6.8 Table (6)

[0044] Next, according to Table 6 and Equation (3): The next target point is evaluated, and γ=1 (weight of priority score) and δ=0.1 (weight of distance) are set to obtain the following table (7): Work order ID Score Distance (km) Next Score 001 3.5 3.2 3.18 003 1.6 4.5 1.15 004 2.0 6.8 1.32

[0045] Next, select the next work order based on the calculated Next Score, and calculate the next work order. Repeat the above steps in sequence until all work orders are completed. The preliminary path after calculation can be obtained: Company -> Work Order 002, Work Order 002 -> Work Order 001, Work Order 001 -> Work Order 004, Work Order 004 -> Work Order 003, Work Order 003 -> Company.

[0046] When the system detects a new work order being inserted, it can recalculate the priority score in a timely manner based on the above operations and dynamically adjust the target point to adjust the route in real time.

[0047] The following is an example of trip start detection. The time is 07:30 AM, and the vehicle A used for maintenance is located at the company. When the GPS detects that vehicle A used for maintenance has left the company, moved a distance exceeding the start point radius (start_point_radius) by 200 ms, and moved a speed exceeding the start point speed (start_point_speed) by 50 km / h, the system determines that the trip has started and records the start time and location.

[0048] The following illustrates an example of route planning and anomaly data processing. The GPS records of vehicle A used for maintenance during its journey are shown in the following table (8): Time Longitude Latitude Speed ​​(m / s) 07:40 121.570 25.040 15.0 07:45 121.580 25.050 120.0 (Abnormal) 07:50 121.590 25.060 20.0 Table (8)

[0049] As can be seen in Table (8), the recorded speed at 07:45 is 120.0 m / s, which is higher than the abnormal data threshold (max_speed_threshold) of 30.56 m / s. Therefore, the system judges it as an abnormal recording point and automatically filters the recording point to avoid affecting the travel analysis.

[0050] The following is an example of trip end detection. The time is 05:30 PM, and vehicle A, used for maintenance, is returning to the company. When the GPS detects that vehicle A, used for maintenance, has entered the end point radius (end_point_radius) of 50m, and the time interval from the previous point exceeds 1 hour, and the speed exceeds the starting point speed (start_point_speed) by 50 km / h and is lower than the end point speed (end_point_speed) by 20 km / h, the system determines that the trip has ended and records the end time and location.

[0051] Figure 2 illustrates a flowchart of a scheduling work trip procedure according to various embodiments of the present invention. In step S210, the data loading module 11 loads work data related to the work trip. In step S220, the calculation module 12 generates a work order sorting based on the work data. In step S230, the route planning module 13 generates route data based on the work order sorting. In step S240, the information preprocessing module 14 detects vehicle movement information. In step S250, the position determination module 15 determines whether the work trip is completed based on the movement information. If the work trip is not completed, the process returns to step S240, and the information preprocessing module 14 continues to detect the vehicle's movement information. If the work trip is completed in step S250, the process proceeds to step S260, where the output module 16 records the vehicle's destination time and destination position, and then proceeds to step S270, where the output module 16 outputs the vehicle's movement information, destination time, and destination position.

[0052] In some specific settings, work data includes multiple work orders, and the work location, priority, and remaining repair time for each work order. Generating work order ranking based on the work data includes: calculating a priority score for each work order using a weighted model based on its priority and remaining repair time; and generating a work order ranking based on the priority scores of each work order.

[0053] In certain specific settings, generating path data based on work order sorting includes: selecting the work position of the work order with the highest priority score among all work orders as the first target point; calculating multiple next target points in sequence based on the distance between the current position and the work positions of each uncompleted work order, and the priority scores of each uncompleted work order; and generating path data based on the first target point and multiple next target points.

[0054] In some specific settings, path data includes a work path list and a visual path diagram. The work path list includes the maintenance sequence, estimated arrival time, and completion time for each work order.

[0055] In certain settings, when a new work order is added to the work data, the work schedule is updated, and the work order sorting and path data are updated accordingly.

[0056] In certain settings, detecting vehicle movement information includes: recording the timestamps of the vehicle's arrival at the work locations of each work order based on the GPS coordinates and work locations in the vehicle's movement information; calculating the actual speed and average speed of the vehicle between the work locations of each work order based on the timestamps and path data; filtering out abnormal data points based on the GPS coordinates in the vehicle's movement information, where the actual speed of the abnormal data points is greater than a speed threshold; and calculating the time taken for the work trip based on the timestamps of the vehicle's arrival at the work locations of each work order and path data.

[0057] Furthermore, this invention discloses a non-volatile computer-readable storage medium applied in a computing device or computer having a processor (e.g., CPU, GPU, etc.) and / or memory, storing instructions, and capable of executing the non-volatile computer-readable storage medium via the processor and / or memory using the computing device or computer to perform the aforementioned methods and steps when executing the non-volatile computer-readable storage medium. In one embodiment, this invention discloses a non-transitory computer-readable storage medium for performing the aforementioned methods and steps.

[0058] Therefore, as explained above, the technology provided by this invention plans optimized maintenance path data by combining work schedules and work order sequencing, and utilizes geographic information to dynamically detect start / end points and abnormal data points, thereby optimizing work scheduling and work movement time. Simultaneously, through the output of results, it enhances the transparency and management efficiency of work scheduling execution, providing users with efficient and accurate maintenance path planning solutions.

[0059] Various embodiments are described with reference to the accompanying drawings, wherein all drawings use the same element reference numerals to denote similar or equivalent elements. The drawings are not necessarily drawn to scale and are provided only to illustrate aspects and features of the invention. Numerous specific details, relationships, and methods are set forth to provide a comprehensive understanding of certain aspects and features of the invention, although those skilled in the art will recognize that these aspects and features can be implemented without one or more of the specific details, relationships, or methods. In some cases, well-known structures or operations are not shown in detail for illustrative purposes. The various embodiments disclosed herein are not necessarily limited to the order of the described actions or events, as some actions may occur in a different order and / or simultaneously with other actions or events. Furthermore, not all actions or events in the drawings are necessary to realize certain aspects and features of the invention.

[0060] Although the invention has been described and illustrated with respect to one or more embodiments, other skilled in the art will recognize or understand equivalent changes and modifications upon reading and understanding this specification and the accompanying drawings. Furthermore, while a particular feature of the invention may be disclosed only in one of several embodiments, this feature may be combined with one or more other features of other embodiments, as these features may be desired and advantageous for any given or particular application.

[0061] While various embodiments of the invention have been described above, it should be understood that they are presented by way of example only and not as limitation. Many changes may be made to the disclosed embodiments based on the disclosure without departing from the spirit or scope of the invention. Therefore, the breadth and scope of the invention should not be limited by any of the above embodiments. Rather, the scope of the invention should be defined according to the appended claims and their equivalents.

[0062] 1: A system for scheduling work processes 11: Load Data Module 12: Computing Module 13: Path Planning Module 14: Information Preprocessing Module 15: Position Determination Module S210~S270: Steps

Claims

1. A system for scheduling work processes, comprising: A data loading module loads maintenance work data related to a maintenance work schedule; a calculation module, communicatively connected to the data loading module, generates a work order sorting based on the maintenance work data; a route planning module, communicatively connected to the calculation module, generates route data based on the work order sorting; and an information preprocessing module, communicatively connected to the calculation module and used to detect the vehicle's movement information, and filter out an abnormal data point based on a GPS coordinate in the vehicle's movement information, wherein the actual speed corresponding to the abnormal data point is greater than a speed threshold. A location determination module, communicatively connected to the path planning module and the information preprocessing module, determines whether a maintenance work trip has been completed based on the vehicle's movement information and path data. If the maintenance work trip is determined to be completed, the module records the vehicle's destination time and destination location; or if the maintenance work trip is determined to be incomplete, the module continues to determine whether the maintenance work trip has been completed based on the movement information and path data. An output module, communicatively connected to the location determination module, outputs the vehicle's movement information, destination time, and destination location. The maintenance work data includes a plurality of work orders, and each work order has a work location, a priority, and a remaining maintenance time. The calculation module uses a weighted model to calculate a priority score for each work order based on its priority and remaining maintenance time, and generates a work order ranking based on the priority scores of each work order.

2. The system for scheduling work trips as described in claim 1, wherein the path planning module is used to: select the work position of the work order with the highest priority score among the work orders as a first target point according to the work order sorting; sequentially calculate a plurality of next target points based on a distance between a current position and the work positions of the unfinished work orders, and the priority scores of the unfinished work orders; and generate path data based on the first target point and the next target points.

3. The system for scheduling work processes as described in claim 2, wherein the path planning module generates path data including a work path list and a visual path map, wherein the work path list includes a maintenance sequence, an estimated arrival time and a completion time for each of the work orders.

4. The system for scheduling work schedules as described in claim 2, wherein when a new work order is added to the maintenance work data, the data loading module updates the maintenance work schedule, the calculation module generates an updated work order sorting accordingly, and the path planning module generates updated path data.

5. The system for scheduling work trips as described in claim 2, wherein the location determination module records a timestamp of the vehicle arriving at the work location of each of the work orders based on the GPS coordinates in the vehicle's movement information and the work location of each of the work orders, wherein the calculation module calculates the actual speed and an average speed of the vehicle between the work locations of each of the work orders based on the timestamp and the path data, wherein the calculation module calculates a time taken for the maintenance work trip based on the timestamp of the vehicle arriving at the work location of each of the work orders and the path data.

6. A method for scheduling work processes, performed by a computer device, comprising: Load maintenance work data related to a maintenance work schedule; generate a work order sorting based on the maintenance work data; The system generates path data based on the work order sorting; detects vehicle movement information; determines whether the repair work trip is completed based on the movement information and path data; if the repair work trip is completed, records the vehicle's destination time and destination location; or if the repair work trip is not completed, continues to determine whether the repair work trip is completed based on the movement information and path data; and outputs the vehicle's movement information, destination time, and destination location. The repair work data includes multiple work orders, and each work order's work location, priority, and remaining repair time. Generating the work order sorting based on the repair work data includes: using a weighted model to calculate a priority score for each work order based on its priority and remaining repair time; and generating the work order sorting based on the priority scores of each work order.

7. The method for scheduling work processes as described in Request 6, wherein generating the path data based on the work order sorting includes: Based on the work order sorting, the work position of the work order with the highest priority score among the work orders is selected as a first target point; based on a distance between the current position and the work positions of the uncompleted work orders, and the priority scores of the uncompleted work orders, a plurality of next target points are calculated sequentially; and the path data is generated based on the first target point and the next target points.

8. The method for scheduling work processes as described in claim 7, wherein the path data includes a work path list and a visual path diagram, wherein the work path list includes a maintenance sequence, an estimated arrival time and a completion time for each of the work orders.

9. The method for scheduling work schedules as described in claim 6, wherein when a new work order is added to the maintenance work data, the maintenance work schedule is updated, and a corresponding updated work order sort and updated path data are generated.

10. The method for scheduling work trips as described in claim 7, wherein detecting the movement information of a vehicle includes: Based on the GPS coordinates in the vehicle's mobility information and the work locations of each of the work orders, a timestamp is recorded indicating the vehicle's arrival at the work locations of each of the work orders; based on the timestamp and the route data, an actual speed and an average speed of the vehicle between the work locations of each of the work orders are calculated; based on the GPS coordinates in the vehicle's mobility information, an abnormal data point is filtered, the actual speed corresponding to the abnormal data point being greater than a speed threshold; and based on the timestamps of the vehicle's arrival at the work locations of each of the work orders and the route data, the time taken for the maintenance work trip is calculated.

11. A non-volatile computer-readable storage medium, used in a computing device or computer, storing instructions for performing a method for scheduling work processes as described in any one of claims 6 to 10.

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