Delivery man dynamic monitoring management method, device and equipment and storage medium

Abstract

The invention relates to the field of logistics, and discloses a courier dynamic monitoring management method, device and equipment and a storage medium, and the method is used for realizing courier dynamic monitoring management. The method comprises the following steps: obtaining order information, traffic road conditions and weather data, and constructing a spatial-temporal characteristic matrix; dynamically adjusting the parcel collection and delivery fence boundary of each geographic area based on the spatial-temporal characteristic matrix; when the distance between the real-time geographic position of the courier and the adjusted boundaries of the express collection and delivery fences is smaller than a preset distance threshold value, early warning is triggered, and an early warning report is generated; acquiring a collection and dispatch track of the courier on the day, analyzing and calculating the collection and dispatch track of the courier on the day and the order information to obtain the residence time of the courier in each geographic area and the collection and dispatch task completion rate, and generating a collection and dispatch analysis report; and performing analysis according to the early warning report and the collection and delivery analysis report to obtain the abnormal condition of the courier and the transport capacity condition of each region, and generating a summary report.

Description

Technical Field

[0001] The present invention relates to the field of logistics technology, and in particular to a method, device, equipment and storage medium for dynamic monitoring and management of couriers. Background Art

[0002] In the rapidly developing express delivery industry, the timeliness and stability of express delivery services have become core competitive factors. To improve the overall delivery capacity of couriers, managers need to comprehensively monitor the real-time dynamic location and collection and delivery data of couriers across the network to ensure stable transportation capacity. At the same time, they need to monitor the delivery points and courier collection and delivery fences to achieve comprehensive coverage of collection and delivery capacity nationwide.

[0003] However, existing logistics monitoring methods are severely inadequate. Traditional tools can only provide partial and delayed information, failing to meet real-time, global management needs. This makes it difficult to allocate express delivery capacity in a timely and effective manner, and service quality is difficult to guarantee, resulting in inconsistent performance. This significantly limits company development and weakens their market competitiveness. The current lack of system tools that can effectively support these monitoring scenarios has become a bottleneck for the further development of the express delivery industry.

[0004] Therefore, the existing technology still needs to be improved and developed. Summary of the Invention

[0005] The present invention provides a courier dynamic monitoring and management method, device, equipment and storage medium for implementing courier dynamic monitoring and management.

[0006] A first aspect of the present invention provides a method for dynamic monitoring and management of couriers, the method comprising:

[0007] Obtain order information, traffic conditions and weather data, and construct a spatiotemporal feature matrix based on the order information, traffic conditions and weather data, wherein the rows of the spatiotemporal feature matrix represent time slices and the columns represent geographical areas; dynamically adjust the collection and delivery fence boundaries of each geographical area based on the spatiotemporal feature matrix; obtain the real-time geographic location of the courier, and compare the real-time geographic location of the courier with the adjusted collection and delivery fence boundaries; when the distance between the real-time geographic location of the courier and the adjusted collection and delivery fence boundaries is less than a preset distance threshold, trigger an early warning and generate an early warning report; obtain the collection and delivery trajectory of the courier on the day, and analyze and calculate the collection and delivery trajectory of the courier on the day and the order information to obtain the courier's residence time in each geographical area and the collection and delivery task completion rate, and generate a collection and delivery analysis report; analyze the courier's abnormal situation and the transportation capacity of each area based on the early warning report and the collection and delivery analysis report, and generate a summary report.

[0008] Optionally, in a first implementation method of the first aspect of the present invention, the obtaining of order information, traffic conditions and weather data, and constructing a spatiotemporal feature matrix based on the order information, traffic conditions and weather data, includes: obtaining order information, traffic conditions and weather data, analyzing the distribution of shipping addresses and receiving addresses based on the order information to determine the service area, and dividing the service area into several geographical areas, and assigning a geographical code to each of the geographical areas; dividing a day into multiple time slices, and counting the number of orders, average traffic congestion index, and weather data code in each time slice and each geographical area; constructing a two-dimensional matrix, and filling the number of orders, average traffic congestion index, and weather data code in each time slice and each geographical area as eigenvalues into corresponding elements of the two-dimensional matrix to obtain a spatiotemporal feature matrix, wherein the rows of the spatiotemporal feature matrix represent time slices and the columns represent geographical areas.

[0009] Optionally, in a second implementation method of the first aspect of the present invention, the dynamic adjustment of the collection and delivery fence boundaries of each of the geographical areas based on the spatiotemporal feature matrix includes: inputting the spatiotemporal feature matrix into a pre-trained spatiotemporal graph convolutional network model to obtain the collection and delivery fence adjustment coefficient for the next N hours output by the spatiotemporal graph convolutional network; counting the order demand probability of each of the geographical areas, and simulating the randomness of the order distribution of each of the geographical areas in the next N hours through Monte Carlo sampling to generate a probability heat map; based on the collection and delivery fence adjustment coefficient for the next N hours and the probability heat map, determining the fence boundary adjustment direction and amplitude of each of the geographical areas through weighted fusion, and based on the fence boundary adjustment direction and amplitude, using GIS topology operations to generate new collection and delivery fence boundaries corresponding to each of the geographical areas.

[0010] Optionally, in a third implementation method of the first aspect of the present invention, the real-time geographic location of the courier is obtained, and the real-time geographic location of the courier is compared with the adjusted collection and delivery fence boundary. When the distance between the real-time geographic location of the courier and the adjusted collection and delivery fence boundary is less than a preset distance threshold, an early warning is triggered, and an early warning report is generated, including: obtaining the real-time geographic location of the courier, calling the Euclidean distance formula to calculate the shortest distance between the real-time geographic location of the courier and the adjusted collection and delivery fence boundary; comparing the shortest distance with the preset distance threshold to determine whether the shortest distance is less than the preset distance threshold; if so, triggering an early warning, and generating an early warning report, the early warning report including the courier's basic information, current geographic location, actual distance from the fence boundary, early warning trigger time, and the collection and delivery fence boundary involved.

[0011] Optionally, in a fourth implementation method of the first aspect of the present invention, the courier's collection and delivery trajectory for the day is obtained, and the courier's collection and delivery trajectory for the day and the order information are analyzed and calculated to obtain the courier's residence time and collection and delivery task completion rate in each geographical area, and generate a collection and delivery analysis report, including: obtaining the courier's collection and delivery trajectory for the day, and preprocessing the courier's collection and delivery trajectory for the day to obtain a preprocessed collection and delivery trajectory; analyzing and calculating the preprocessed collection and delivery trajectory and the order information to obtain the courier's residence time in each area and the collection and delivery task completion rate; presenting the courier's residence time in each area and the collection and delivery task completion rate in the form of a chart, and inserting the chart into a preset collection and delivery analysis report template to generate a collection and delivery analysis report.

[0012] Optionally, in a fifth implementation method of the first aspect of the present invention, the pre-processed collection and delivery trajectory and the order information are analyzed and calculated to obtain the courier's residence time in each area and the collection and delivery task completion rate, including: determining the courier's residence time in each area based on the timestamp and location information of the pre-processed collection and delivery trajectory; counting the total number of collection and delivery tasks assigned to the courier on that day, the number of collected orders, and the number of delivered orders based on the order information; calculating the collection and delivery task completion rate based on the total number of collection and delivery tasks assigned to the courier on that day, the number of collected orders, and the number of delivered orders.

[0013] Optionally, in a sixth implementation method of the first aspect of the present invention, the abnormal conditions of the couriers and the transportation capacity of each region are analyzed according to the early warning report and the collection and delivery analysis report, and a summary report is generated, including: obtaining the number of each courier, using the courier's number as the associated field, integrating the data involving the same courier in the early warning report and the collection and delivery analysis report, and constructing a comprehensive data set; analyzing the courier's cross-border abnormalities, efficiency abnormalities and behavior pattern abnormalities according to the comprehensive data set to generate a summary of abnormal conditions, and analyzing the order demand and transportation capacity matching, average collection and delivery efficiency and dynamic transportation capacity changes in each region according to the comprehensive data set to generate a summary of transportation capacity in each region; generating a summary report based on the summary of abnormal conditions and the summary of transportation capacity in each region.

[0014] According to a second aspect of the present invention, a device for dynamic monitoring and management of couriers is provided, comprising: a construction module for acquiring order information, traffic conditions and weather data, and constructing a spatiotemporal feature matrix based on the order information, traffic conditions and weather data, wherein the rows of the spatiotemporal feature matrix represent time slices and the columns represent geographical areas; an adjustment module for dynamically adjusting the collection and delivery fence boundaries of each geographical area based on the spatiotemporal feature matrix; an early warning module for acquiring the real-time geographic location of the courier, comparing the real-time geographic location of the courier with the adjusted collection and delivery fence boundaries, and triggering an early warning when the distance between the real-time geographic location of the courier and the adjusted collection and delivery fence boundaries is less than a preset distance threshold, and generating an early warning report; a first analysis module for acquiring the collection and delivery trajectory of the courier on the day, and analyzing and calculating the collection and delivery trajectory of the courier on the day and the order information to obtain the courier's stay time in each geographical area and the collection and delivery task completion rate, and generate a collection and delivery analysis report; a second analysis module for analyzing the courier's abnormal situation and the transportation capacity of each area based on the early warning report and the collection and delivery analysis report, and generating a summary report.

[0015] Optionally, in a first implementation manner of the second aspect of the present invention, the construction module includes: an acquisition unit, used to acquire order information, traffic conditions and weather data, analyze the distribution of shipping addresses and receiving addresses based on the order information to determine the service area, and divide the service area into several geographical areas, and assign a geographical code to each of the geographical areas; a division unit, used to divide a day into multiple time slices, and count the number of orders, average traffic congestion index, and weather data code in each time slice and each geographical area; a construction unit, used to construct a two-dimensional matrix, and fill the number of orders, average traffic congestion index, and weather data code in each time slice and each geographical area as eigenvalues into corresponding elements of the two-dimensional matrix to obtain a spatiotemporal feature matrix, wherein the rows of the spatiotemporal feature matrix represent time slices and the columns represent geographical areas.

[0016] Optionally, in a second implementation of the second aspect of the present invention, the adjustment module includes: a prediction unit, used to input the spatiotemporal feature matrix into a pre-trained spatiotemporal graph convolutional network model, and obtain the next N hours' collection and delivery fence adjustment coefficient output by the spatiotemporal graph convolutional network; a statistical unit, used to count the order demand probability of each of the said geographical areas, and simulate the randomness of the order distribution of each of the said geographical areas in the next N hours through Monte Carlo sampling to generate a probability heat map; an adjustment unit, used to determine the fence boundary adjustment direction and amplitude of each of the said geographical areas through weighted fusion based on the next N hours' collection and delivery fence adjustment coefficient and the probability heat map, and based on the fence boundary adjustment direction and amplitude, use GIS topology operation to generate new collection and delivery fence boundaries corresponding to each of the said geographical areas.

[0017] Optionally, in a third implementation of the second aspect of the present invention, the early warning module includes: a calculation unit, used to obtain the real-time geographic location of the courier, and call the Euclidean distance formula to calculate the shortest distance between the real-time geographic location of the courier and the adjusted collection and delivery fence boundary; a comparison unit, used to compare the shortest distance with a preset distance threshold, and determine whether the shortest distance is less than the preset distance threshold; an early warning unit, used to trigger an early warning when the shortest distance is less than the preset distance threshold, and generate an early warning report, the early warning report including the courier's basic information, current geographic location, actual distance from the fence boundary, early warning trigger time, and the collection and delivery fence boundary involved.

[0018] Optionally, in a fourth implementation of the second aspect of the present invention, the first analysis module includes: a preprocessing unit, used to obtain the courier's collection and delivery trajectory on the day, and preprocess the courier's collection and delivery trajectory on the day to obtain a preprocessed collection and delivery trajectory; a first analysis unit, used to analyze and calculate the preprocessed collection and delivery trajectory and the order information to obtain the courier's residence time in each area and the collection and delivery task completion rate; a first generation unit, used to present the courier's residence time in each area and the collection and delivery task completion rate in the form of a chart, and insert the chart into a preset collection and delivery analysis report template to generate a collection and delivery analysis report.

[0019] Optionally, in a fifth implementation of the second aspect of the present invention, the second analysis module includes: an integration unit, used to obtain the number of each courier, using the courier's number as the associated field, integrating the data involving the same courier in the early warning report and the collection and delivery analysis report, and constructing a comprehensive data set; a second analysis unit, used to analyze the courier's cross-border anomalies, efficiency anomalies, and behavior pattern anomalies based on the comprehensive data set, generate an anomaly summary, and analyze the order demand and capacity matching, average collection and delivery efficiency, and dynamic capacity changes in each region based on the comprehensive data set to generate a capacity summary for each region; a summary unit, used to generate a summary report based on the anomaly summary and the capacity summary for each region.

[0020] The third aspect of the present invention provides a courier dynamic monitoring and management device, comprising: a memory and at least one processor, wherein the memory stores computer-readable instructions, and the memory and the at least one processor are interconnected through a line; the at least one processor calls the computer-readable instructions in the memory so that the courier dynamic monitoring and management device executes each step of the courier dynamic monitoring and management method as described above.

[0021] A fourth aspect of the present invention provides a computer-readable storage medium, which stores computer-readable instructions. When the computer-readable storage medium is run on a computer, it enables the computer to execute the various steps of the courier dynamic monitoring and management method as described above.

[0022] In the technical solution provided by the present invention, a spatiotemporal feature matrix is constructed through order information, traffic conditions and weather data to realize dynamic adjustment of the boundaries of the collection and delivery fence. At the same time, the courier's position is monitored in real time and timely warnings are issued. The collection and delivery data are deeply analyzed to generate a collection and delivery analysis report, and then the abnormal situation of the courier and the transportation capacity of each region are fully understood and a summary report is generated, so that the express operation management can accurately grasp the business dynamics, respond to problems in advance, reasonably allocate resources, effectively improve the efficiency and quality of express services, and enhance the company's operational management capabilities and market competitiveness. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 A first flow chart of the method for dynamic monitoring and management of couriers provided by an embodiment of the present invention;

[0024] Figure 2 A second flow chart of the method for dynamic monitoring and management of couriers provided by an embodiment of the present invention;

[0025] Figure 3 A third flow chart of the courier dynamic monitoring and management method provided by an embodiment of the present invention;

[0026] Figure 4 A fourth flow chart of the courier dynamic monitoring and management method provided by an embodiment of the present invention;

[0027] Figure 5 A fifth flow chart of the courier dynamic monitoring and management method provided by an embodiment of the present invention;

[0028] Figure 6 A sixth flow chart of the courier dynamic monitoring and management method provided by an embodiment of the present invention;

[0029] Figure 7 A schematic diagram of the structure of a courier dynamic monitoring and management device provided by an embodiment of the present invention;

[0030] Figure 8 A schematic diagram of the structure of a courier dynamic monitoring and management device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0031] Embodiments of the present invention provide a method, apparatus, device, and storage medium for dynamic monitoring and management of couriers, the method being used to implement dynamic monitoring and management of couriers. The method comprises: obtaining order information, traffic conditions, and weather data, and constructing a spatiotemporal feature matrix based on the order information, traffic conditions, and weather data, wherein rows of the spatiotemporal feature matrix represent time slices and columns represent geographic regions; dynamically adjusting the pickup and delivery fence boundaries of each geographic region based on the spatiotemporal feature matrix; obtaining the courier's real-time geographic location, comparing the courier's real-time geographic location with the adjusted pickup and delivery fence boundaries, and triggering an alert when the distance between the courier's real-time geographic location and the adjusted pickup and delivery fence boundaries is less than a preset distance threshold, and generating an alert report; obtaining the courier's pickup and delivery trajectory for the day, analyzing and calculating the courier's pickup and delivery trajectory for the day and the order information to obtain the courier's residence time in each geographic region and the pickup and delivery task completion rate, and generating a pickup and delivery analysis report; and analyzing the courier's abnormal conditions and the transportation capacity of each region based on the alert report and the pickup and delivery analysis report, and generating a summary report.

[0032] The terms "first," "second," "third," "fourth," and the like (if any) in the description and claims of the present invention and in the accompanying drawings are used to distinguish similar objects and are not necessarily used to describe a particular order or precedence. It should be understood that the terms used in this manner are interchangeable where appropriate so that the embodiments described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "including" or "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product, or apparatus that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units that are not explicitly listed or that are inherent to these processes, methods, products, or apparatus.

[0033] For ease of understanding, the specific process of the embodiment of the present invention is described below. Figure 1 A first embodiment of a method for dynamic monitoring and management of couriers in an embodiment of the present invention includes:

[0034] S101. Obtain order information, traffic conditions, and weather data, and construct a spatiotemporal feature matrix based on the order information, traffic conditions, and weather data. The rows of the spatiotemporal feature matrix represent time slices, and the columns represent geographical areas.

[0035] In this embodiment, order information, including order number, order time, shipping address, receiving address, and item weight, is obtained from the express order management system. Real-time traffic condition data, such as road congestion, accident information, and road construction status, is obtained through the traffic data platform interface. Weather data, such as weather conditions (sunny, rainy, etc.), temperature, and wind speed, is collected through the meteorological data interface.

[0036] In this embodiment, the acquired order information, traffic conditions, and weather data are cleaned to remove duplicate, erroneous, and incomplete data. Data in different formats are converted to a format that is easy to process, and missing data is filled or deleted.

[0037] In this embodiment, for each time slice and geographical region, the number of orders is counted, the average traffic congestion index is calculated, and the weather conditions are coded (e.g., sunny day is 1, rainy day is 2, etc.). A spatiotemporal feature matrix is constructed with time slices as rows and geographical regions as columns, and the extracted eigenvalues are filled into the corresponding matrix elements.

[0038] It is understandable that the execution subject of the present invention can be a courier dynamic monitoring and management device, or a terminal or a server, which is not limited here. The embodiment of the present invention is described by taking the server as the execution subject as an example.

[0039] S102. Dynamically adjust the pickup and delivery fence boundaries of each geographical area based on the spatiotemporal feature matrix.

[0040] In this example, a data analysis algorithm is used to analyze the spatiotemporal feature matrix to uncover the changing patterns and interrelationships between factors such as order volume, traffic conditions, and weather at different times and spaces. For example, this allows analysis of which regions are most affected by traffic congestion at specific times, and which regions experience order volume growth related to weather changes.

[0041] Develop rules for adjusting the pickup and delivery perimeter based on data analysis. If a region experiences a significant increase in order volume and severe traffic congestion during peak hours, the perimeter will be appropriately expanded to provide couriers with more room to operate. If order volume in a region remains low, the perimeter will be narrowed to improve courier pickup and delivery efficiency.

[0042] Finally, using geographic information system (GIS) technology, the boundaries of the collection and delivery fence are adjusted according to the adjustment rules.

[0043] S103. Obtain the real-time geographic location of the courier, and compare the real-time geographic location of the courier with the adjusted fence boundary for collection and delivery. When the distance between the real-time geographic location of the courier and the adjusted fence boundary for collection and delivery is less than a preset distance threshold, trigger an early warning and generate an early warning report.

[0044] In this embodiment, the courier's geographic location information, including latitude and longitude coordinates, can be obtained in real time through the positioning function of the courier's handheld device (such as GPS, base station positioning).

[0045] In this embodiment, the courier's real-time geographic location is compared with the adjusted delivery fence boundary, and a distance calculation method (such as Euclidean distance or a distance calculation method that accounts for the curvature of the earth) is used to calculate the shortest distance between the courier and the fence boundary. When the distance between the courier and the fence boundary falls below a preset distance threshold, an early warning mechanism is triggered.

[0046] S104. Obtain the courier's collection and delivery trajectory for the day, analyze and calculate the courier's collection and delivery trajectory and order information for the day, obtain the courier's stay time in each geographical area and the collection and delivery task completion rate, and generate a collection and delivery analysis report.

[0047] In this embodiment, the courier's collection and delivery trajectory data for the day is obtained, the collection and delivery trajectory data is cleaned, abnormal points and duplicate points are removed, and missing data is interpolated to ensure the continuity and accuracy of the trajectory.

[0048] In this embodiment, the courier's entry and exit times for each area are determined based on the delivery trajectory, combined with geographic area division information. The dwell time in each area is calculated. For example, when a courier's trajectory point enters and exits from one area, the entry and exit times are recorded, and the difference between the two times is the dwell time in that area.

[0049] In this embodiment, the number of total collection and delivery tasks of the courier on that day is obtained from the order information, the number of completed collection and delivery orders is counted through system records, and then the completion rate of the collection and delivery tasks is calculated.

[0050] In this example, the calculated data on courier dwell time and task completion rates in various geographic regions is collated and analyzed to understand the underlying reasons. For example, long dwell times may be due to difficulty finding the customer's address or traffic congestion, while low task completion rates may be related to irrational task allocation. A task completion analysis report is generated using a combination of charts (bar charts showing comparisons of dwell time in each region, and line charts showing trends in task completion rates) and text. The report includes an assessment of courier work efficiency, an analysis of the business situation in each region, existing problems, and suggestions for improvement.

[0051] S105. Analyze the courier's abnormal situation and the transportation capacity of each region based on the early warning report and the collection and delivery analysis report, and generate a summary report.

[0052] In this embodiment, the courier's abnormal behavior is analyzed based on the early warning report and the pickup and delivery analysis report. For example, if the courier frequently triggers early warnings and has a low completion rate for pickup and delivery tasks, it may be due to illegal operations or unfamiliarity with the work area. If the courier stays in a certain area for an extended period of time and has a low completion rate for pickup and delivery tasks, it may be due to special difficulties in that area.

[0053] In this embodiment, the order demand and transportation capacity matching situation of each region is analyzed, the ratio of the order volume to the number of couriers in each region is calculated, and it is determined which regions have insufficient transportation capacity (the ratio of the order volume to the number of couriers is too high) and which regions have excess transportation capacity (the ratio is too low). The average collection and delivery efficiency of each region is evaluated, and the overall collection and delivery efficiency of the region is determined by combining the courier's stay time in each region and the completion rate of the collection and delivery tasks. The dynamic transportation capacity changes of each region are analyzed, and future changes in transportation capacity demand are predicted by comparing the order volume, number of couriers and completion rate of collection and delivery tasks in different time periods.

[0054] This embodiment provides a method for dynamic monitoring and management of couriers. It constructs a spatiotemporal feature matrix through order information, traffic conditions and weather data to achieve dynamic adjustment of the boundaries of the collection and delivery fence. At the same time, it monitors the courier's location in real time and issues timely warnings, deeply analyzes the collection and delivery data to generate a collection and delivery analysis report, and then comprehensively grasps the courier's abnormal situation and the transportation capacity of each region and generates a summary report, so that the express operation management can accurately grasp the business dynamics, respond to problems in advance, reasonably allocate resources, effectively improve the efficiency and quality of express services, and enhance the company's operation management capabilities and market competitiveness.

[0055] See also Figure 2 The second embodiment of the courier dynamic monitoring management method in the embodiment of the present invention includes:

[0056] S201. Obtain order information, traffic conditions, and weather data, analyze the distribution of shipping addresses and receiving addresses based on the order information to determine a service area, divide the service area into several geographical areas, and assign a geocode to each geographical area.

[0057] In this embodiment, the express delivery system is used to obtain order information such as order number, order time, shipping address, and item weight; real-time traffic information such as road congestion level and construction sections are obtained through the traffic data platform; and weather data such as weather conditions, temperature, and wind speed are obtained from the meteorological department interface.

[0058] In this embodiment, Geographic Information System (GIS) technology and data analysis algorithms are used to analyze the shipping and receiving addresses of orders. Cluster analysis is used to identify areas with concentrated orders. This is combined with the actual coverage of the express delivery service to determine the service area. The service area is divided into several geographic regions based on its geographical characteristics (such as administrative divisions, road distribution, and population density). A unique geocode is generated for each geographic region to facilitate subsequent data association and analysis.

[0059] S202: Divide a day into multiple time slices, and count the number of orders, average traffic congestion index, and weather data code in each time slice and each geographical area.

[0060] In this embodiment, according to the busyness of the express delivery business and the needs of data analysis, a day is divided into multiple time slices, such as 15 minutes, 30 minutes or 1 hour as a time slice.

[0061] In this embodiment, within each time slice, the number of orders is counted for each geographical area, and the order information recorded in the order management system is used to count the orders. The average traffic congestion index is calculated, and the weighted average is performed according to the road weights within the area, combining the values corresponding to different congestion levels in the traffic road condition data. The weather data is encoded, and different weather conditions (such as sunny days are set to 1, rainy days are set to 2, etc.) and meteorological elements (such as temperature, humidity and other data are normalized and then encoded).

[0062] S203: Construct a two-dimensional matrix, and fill the order quantity, average traffic congestion index, and weather data code in each time slice and each geographical area as characteristic values into corresponding elements of the two-dimensional matrix to obtain a spatiotemporal characteristic matrix.

[0063] In this example, a two-dimensional matrix is created, with rows representing time slices and columns representing geographic regions. The number of orders, average traffic congestion index, and weather data encodings for each time slice and geographic region are used as eigenvalues and filled into the corresponding element positions of the two-dimensional matrix.

[0064] In this embodiment, if data for a certain time slice-geographical area combination is missing, it is filled in according to the specific situation (eg, using an average value, a predicted value, or a special mark).

[0065] In this embodiment, by obtaining order information, traffic conditions and weather data, a systematic analysis and integration is carried out. First, the service area is accurately determined and divided into geographical areas, then the time slices are finely divided, key data are counted and encoded, and finally a spatiotemporal feature matrix is constructed and filled. This method organically combines multi-source data according to time and space dimensions, providing a comprehensive, intuitive and in-depth data analysis foundation for the management and decision-making of express delivery services.

[0066] See also Figure 3 A third embodiment of a method for dynamic monitoring and management of couriers in an embodiment of the present invention includes:

[0067] S301. Input the spatiotemporal feature matrix into the pre-trained spatiotemporal graph convolutional network model to obtain the fence adjustment coefficient for the next N hours of collection and delivery output by the spatiotemporal graph convolutional network.

[0068] In this example, the spatiotemporal feature matrix is normalized to ensure that all eigenvalues are within the same numerical range, thus preventing model performance from being affected by differences in feature scale. For example, for features of different magnitudes, such as the number of orders and the average traffic congestion index, the minimum-maximum normalization method is used to scale them to the interval [0, 1].

[0069] The normalized spatiotemporal feature matrix is sliced according to a certain time step to meet the input requirements of the spatiotemporal graph convolutional network model.

[0070] In this example, a pre-trained spatiotemporal graph convolutional network model is loaded. This model is trained on a large amount of historical data and learns the mapping between spatiotemporal features and the adjustment of pickup and delivery fences. The processed spatiotemporal feature matrix is input into the model, which then deeply mines and analyzes the spatiotemporal features using its internal convolutional and recurrent structures.

[0071] The spatiotemporal graph convolutional network model outputs the fence adjustment coefficient for the next N hours of collection and delivery. This coefficient reflects the changing trend of collection and delivery demand in different regions in the future.

[0072] S302 , counting the order demand probability of each geographical area, and simulating the randomness of order distribution in each geographical area within the next N hours through Monte Carlo sampling to generate a probability heat map.

[0073] In this embodiment, the order frequency within each geographical area is counted based on historical order data, and can be classified and counted according to different time periods (such as weekdays, weekends, daytime, nighttime, etc.) to more accurately reflect the temporal pattern of order demand.

[0074] Calculate the order demand probability for each geographic region, which is the frequency of orders in that geographic region divided by the total number of orders.

[0075] In this embodiment, the number of Monte Carlo sampling runs is determined, for example, 1,000 or 10,000. During each sampling run, an order distribution is randomly generated based on the order demand probability for each geographic region, simulating the randomness of order distribution over the next N hours. Statistical analysis is performed on the order distributions generated from these multiple sampling runs, for example, calculating the average number of orders for each geographic region across all sampling runs.

[0076] Based on the results of Monte Carlo sampling, a heat value is assigned to each grid. The higher the heat value, the greater the possibility that orders will appear in the grid in the next N hours. Drawing tools (such as Python's Matplotlib library) are used to visualize the heat value of the grid in the form of a heat map, intuitively presenting the probability of future order distribution.

[0077] S303. Based on the fence adjustment coefficients and probability heat maps for the next N hours, determine the fence boundary adjustment direction and magnitude for each geographic area through weighted fusion. Based on the fence boundary adjustment direction and magnitude, use GIS topological operations to generate new fence boundaries for the collection and delivery of parcels corresponding to each geographic area.

[0078] In this example, appropriate weights are assigned to the pickup and delivery fence adjustment coefficient and the probability heat map for the next N hours. The weightings can be adjusted based on actual business needs and experience. For example, if historical data trend forecasting is more important, a higher weight can be assigned to the adjustment coefficient; if the randomness of order distribution is more important, a higher weight can be assigned to the probability heat map. The adjustment coefficient and the heat map's heat values are weighted and combined to produce a comprehensive score for each geographic region.

[0079] In this embodiment, the direction of the fence boundary adjustment is determined based on the comprehensive score of each geographic region. If a geographic region has a high comprehensive score, it indicates that the demand for pickup and delivery in that region may increase, and the fence boundary can be expanded to that region; conversely, if the score is low, the fence boundary can be appropriately contracted.

[0080] In this embodiment, the adjustment range of the fence boundary is determined by setting a certain threshold or calculating the rate of change of the score. For example, if the comprehensive score of a certain geographical area exceeds a threshold, the fence boundary is moved a certain distance toward the grid.

[0081] In this embodiment, the topological calculation function of the GIS software is used to modify the existing collection and delivery fence boundaries of each geographical area according to the determined adjustment direction and amplitude, generate new collection and delivery fence boundaries corresponding to each geographical area, and store them in the geographic information database for subsequent courier scheduling and task allocation.

[0082] In this embodiment, the spatiotemporal graph convolutional network model and Monte Carlo sampling method are used, combined with the spatiotemporal feature matrix and historical order data, to predict and analyze future collection and delivery demand from different perspectives. By weightedly fusing the adjustment coefficient output by the spatiotemporal graph convolutional network model with the probability heat map, the historical trends and the randomness of order distribution are fully considered, making the adjustment of the fence boundary more scientific and reasonable. In addition, the new fence boundary is generated using GIS topological operations to ensure the continuity and rationality of the boundary.

[0083] See also Figure 4 A fourth embodiment of a method for dynamic monitoring and management of couriers in an embodiment of the present invention includes:

[0084] S401. Obtain the real-time geographic location of the courier, and use the Euclidean distance formula to calculate the shortest distance between the real-time geographic location of the courier and the adjusted delivery fence boundary.

[0085] In this embodiment, the courier's real-time geographic location information is obtained with the help of the GPS positioning system, base station positioning technology and indoor positioning technology (such as Wi-Fi positioning and Bluetooth positioning).

[0086] In this embodiment, the received real-time geographic location data of the courier is stored in the database, and for the accuracy and consistency of subsequent calculations, the data is processed as necessary, such as converting the latitude and longitude coordinates into a geographic space coordinate system suitable for distance calculation.

[0087] In this embodiment, the Euclidean distance formula is used to calculate the shortest distance between the courier's current geographic location (point) and the boundary of the delivery fence (polygon). Specifically, this can be achieved by traversing each edge of the polygon, calculating the distance from the point to each edge, and then taking the minimum value as the shortest distance.

[0088] S402: Compare the shortest distance with a preset distance threshold to determine whether the shortest distance is less than the preset distance threshold.

[0089] In this embodiment, the preset distance threshold can be flexibly adjusted based on factors such as the pickup and delivery area, business hours, or the courier's work tasks. For example, for busy commercial areas, the preset distance threshold can be set relatively low; for remote areas, the preset distance threshold can be appropriately increased.

[0090] S403. If yes, an early warning is triggered and an early warning report is generated. The early warning report includes the courier's basic information, current geographical location, actual distance from the fence boundary, early warning triggering time and the fence boundary involved in the delivery and collection.

[0091] In this embodiment, when the shortest distance is determined to be less than a preset distance threshold, an early warning mechanism is immediately triggered. Various early warning methods can be used, including pop-up notifications within the system, sound alarms, text message notifications, or push messages sent to mobile devices of relevant managers to ensure timely attention.

[0092] In this embodiment, all the information required to generate an early warning report is collected. The courier's basic information (such as name, work number, and courier station) can be obtained from the employee information database; the current geographic location directly uses the previously acquired and stored latitude and longitude coordinates, which can also be converted into a specific address through a geocoding service; the actual distance to the fence boundary is the shortest distance calculated previously; the warning trigger time is recorded by the system at the current timestamp; and the detailed description and coordinate data of the fence boundary related to the delivery and collection fence are extracted from the GIS database.

[0093] In this embodiment, by obtaining the courier's real-time geographic location and accurately calculating the shortest distance between it and the adjusted collection and delivery fence boundary, and comparing it with the preset threshold, it is possible to promptly and accurately detect the courier's approach to the fence boundary. Once an early warning is triggered, an early warning report containing detailed information is automatically generated, providing managers with a comprehensive and clear decision-making basis. This real-time monitoring and early warning mechanism helps to improve the management efficiency of express delivery services, ensure that couriers work within the specified collection and delivery area, reduce business chaos and resource waste caused by crossing the boundary, and at the same time respond to emergencies in a timely manner to ensure the quality and stability of express delivery services.

[0094] See also Figure 5 A fifth embodiment of a method for dynamic monitoring and management of couriers in an embodiment of the present invention includes:

[0095] S501. Obtain the courier's collection and delivery trajectory for the day, and pre-process the courier's collection and delivery trajectory for the day to obtain a pre-processed collection and delivery trajectory.

[0096] In this embodiment, preprocessing the courier's daily delivery trajectory includes inspecting the trajectory data and removing abnormal data caused by factors such as signal interference, such as records with sudden, large jumps in location or chaotic timestamps. Preprocessing the courier's daily delivery trajectory also includes matching the trajectory data's latitude and longitude coordinates with the actual map road network to improve the accuracy of trajectory analysis.

[0097] In this embodiment, when there are missing parts in the trajectory data, a suitable interpolation method (such as linear interpolation) is used to fill the missing parts to ensure the continuity of the trajectory.

[0098] In this embodiment, pre-processing the courier's daily delivery trajectory also includes smoothing the trajectory using a filtering algorithm (such as a Kalman filter) to remove jitter caused by positioning errors and make the trajectory more consistent with the actual driving path. For example, in urban areas with tall buildings, where GPS signals are susceptible to interference and fluctuations, filtering algorithms can make the trajectory closer to the actual route.

[0099] S502: Analyze and calculate the pre-processed delivery trajectory and order information to obtain the courier's stay time in each area and the delivery task completion rate.

[0100] In this embodiment, the courier's stay time in each area is determined based on the timestamp and location information of the pre-processed collection and delivery trajectory; the total number of collection and delivery tasks assigned to the courier on that day, the number of collected orders, and the number of delivered orders are counted based on the order information; and the collection and delivery task completion rate is calculated based on the total number of collection and delivery tasks assigned to the courier on that day, the number of collected orders, and the number of delivered orders.

[0101] In this embodiment, the completion rate of the collection and delivery tasks = (the number of orders collected + the number of orders delivered) ÷ the total number of collection and delivery tasks × 100%.

[0102] S503. Present the courier's residence time in each area and the completion rate of the collection and delivery task in the form of a chart, and insert the chart into a preset collection and delivery analysis report template to generate a collection and delivery analysis report.

[0103] In this embodiment, the distribution of couriers' dwell time in various areas is presented in the form of a table or chart (such as a bar chart or pie chart). The collection and delivery analysis report can analyze the reasons for longer dwell times in areas, such as whether there are difficulties in customer communication or inconvenience in address retrieval. The collection and delivery analysis report can also list the courier's collection and delivery task completion rate for the day, compare it with other couriers or historical data, and analyze the reasons for high and low completion rates, such as whether the task allocation is reasonable and whether there are differences in work efficiency.

[0104] In this embodiment, the courier's collection and delivery trajectory on the day is obtained and carefully pre-processed to ensure data accuracy and reliability. The dwell time and collection and delivery task completion rate are then analyzed and calculated in combination with order information to provide a quantitative basis for express business evaluation. Finally, the results are presented in intuitive charts and standardized reports are generated, allowing managers to quickly understand the courier's work status, accurately locate problem areas and business links, and then optimize resource allocation, reasonably adjust task allocation, plan delivery routes, improve express service efficiency and quality, and enhance the company's operational management capabilities and market competitiveness.

[0105] See also Figure 6 A sixth embodiment of a method for dynamic monitoring and management of couriers in an embodiment of the present invention includes:

[0106] S601. Obtain the ID of each courier, use the courier ID as the associated field, integrate the data related to the same courier in the early warning report and the collection and delivery analysis report, and construct a comprehensive data set.

[0107] In this example, the courier number is used as a unique identifier to traverse the data records of the two reports. When a courier record with the same number is found in the early warning report and the collection and delivery analysis report, the relevant data in these records is merged to form a comprehensive record containing multi-dimensional information. For example, all early warning information for a courier can be combined with the corresponding collection and delivery analysis data to construct a comprehensive data set.

[0108] S602. Analyze the courier's abnormal crossing of boundaries, abnormal efficiency, and abnormal behavior patterns based on the comprehensive data set to generate a summary of abnormal situations. Analyze the order demand and capacity matching, average collection and delivery efficiency, and dynamic capacity changes in each region based on the comprehensive data set to generate a summary of capacity in each region.

[0109] In this example, the comprehensive dataset is traversed to select records where the warning time field is not empty. These records represent couriers who have triggered warnings. For these couriers, information such as the number of warnings, the regional distribution of warnings, and the interval between warnings is collected. A reasonable threshold is set. For example, if a courier triggers more than three warnings in a certain area within a day, it is determined to be an out-of-bounds anomaly. Information about these abnormal couriers is recorded in a summary table of out-of-bounds anomalies, including the courier number, the abnormal area, and the number of warnings.

[0110] In this embodiment, the average stay time and delivery task completion rate of each courier are calculated based on the residence time and delivery task completion rate data of each area in the comprehensive data set. By comparing with the industry average or the standard value set within the company, it is determined whether the courier's efficiency is abnormal. For example, if the average stay time of a courier is 50% longer than the average stay time of other couriers in the same area, and the delivery task completion rate is lower than 70%, it will be marked as an efficiency abnormality and recorded in the efficiency abnormality summary table, which contains information such as courier number, main abnormal area, average stay time, delivery task completion rate, etc.

[0111] In this embodiment, data mining algorithms such as cluster analysis and sequential pattern mining are used to analyze the comprehensive data set. Cluster analysis can group couriers with similar collection and delivery trajectories, dwell time, and task completion rate patterns into one category. By observing the characteristics of each category, groups of couriers with behavioral patterns that differ significantly from those of most couriers can be identified. Sequential pattern mining is used to discover frequent patterns in the collection and delivery behaviors of couriers. If a courier's collection and delivery behavior does not conform to these common patterns, there may be abnormal behavior patterns. The information of couriers with abnormal behavior patterns is organized into corresponding summary tables, including courier numbers, descriptions of abnormal behavior, etc.

[0112] In this embodiment, the number of orders and the number of couriers are counted by region based on the comprehensive data set. The order-to-courier ratio is calculated for each region and compared with the set reasonable ratio range. If the order-to-courier ratio of a region is higher than the upper limit, it means that the region has a large order demand but relatively insufficient transportation capacity; if it is lower than the lower limit, it indicates excess transportation capacity. The number of orders, the number of couriers, the order-to-courier ratio, and the transportation capacity matching status (shortage, surplus, or balance) of each region are recorded in the order demand and transportation capacity matching summary table.

[0113] In this embodiment, for each region, the average delivery task completion rate and average residence time of all couriers in the region are calculated to evaluate the average delivery efficiency of the region. The higher the average delivery task completion rate and the shorter the average residence time, the higher the average delivery efficiency of the region. The average delivery task completion rate, average residence time, and average delivery efficiency evaluation results (high, medium, and low) of each region are recorded in the average delivery efficiency summary table.

[0114] In this embodiment, the data on the number of orders, the number of couriers, and the completion rate of pick-up and delivery tasks in each region in different time periods (such as every hour) are extracted from the comprehensive data set. Time series analysis methods, such as the moving average method, exponential smoothing method, etc., are used to analyze the changing trends of these data over time. By analyzing the trends, the changes in the capacity demand in each region in the future are predicted. For example, if the number of orders in a certain area has shown a gradual upward trend in the past few hours, and the completion rate of pick-up and delivery tasks has gradually decreased, it can be predicted that the area may face a capacity shortage problem in the future. The capacity data, change trends, and future forecast results of each region in different time periods are recorded in the dynamic capacity change summary table.

[0115] S603. Generate a summary report based on the summary of abnormal situations and the summary of transportation capacity in each area.

[0116] In this embodiment, the data in the exception summary and the regional capacity summary are populated according to the report design format. For courier exceptions, the data in the cross-border exception, efficiency exception, and behavior pattern exception summary tables are sorted and merged, and the courier number is used as the index to clearly present the detailed exception information of each abnormal courier. For regional capacity, the data in the order demand and capacity matching, average collection and delivery efficiency, and dynamic capacity change summary tables are integrated, and the region is used as the index to display the comprehensive capacity of each region.

[0117] In this embodiment, by integrating the early warning report and the collection and delivery analysis report data with the courier number as the link, a comprehensive data set is constructed. On this basis, the courier's abnormal situation is deeply analyzed from multiple dimensions, and the problem courier and his abnormal behavior can be accurately located. At the same time, the transportation capacity of each region is carefully evaluated to grasp the dynamic changes in transportation capacity supply and demand. The final summary report converts complex data into intuitive and easy-to-understand information, which is convenient for managers to quickly grasp the overall operation status of the express business, discover potential problems in time and take targeted measures, realize the refined management of the express business, and improve operational efficiency and service quality.

[0118] The above describes the courier dynamic monitoring management method in the embodiment of the present invention. The following describes the device in the embodiment of the present invention. Figure 7 , the implementation of the courier dynamic monitoring and management device in the embodiment of the present invention includes:

[0119] Construction module 701 is used to obtain order information, traffic conditions and weather data, and construct a spatiotemporal feature matrix based on the order information, traffic conditions and weather data, where the rows of the spatiotemporal feature matrix represent time slices and the columns represent geographical areas;

[0120] An adjustment module 702 is configured to dynamically adjust the pickup and delivery fence boundaries of each of the geographical areas based on the spatiotemporal feature matrix;

[0121] An early warning module 703 is configured to obtain the courier's real-time geographic location and compare it with the adjusted delivery and collection fence boundary. When the distance between the courier's real-time geographic location and the adjusted delivery and collection fence boundary is less than a preset distance threshold, an early warning is triggered and an early warning report is generated.

[0122] The first analysis module 704 is used to obtain the courier's daily collection and delivery trajectory, analyze and calculate the courier's daily collection and delivery trajectory and the order information, obtain the courier's stay time in each geographical area and the collection and delivery task completion rate, and generate a collection and delivery analysis report;

[0123] The analysis module 705 is used to analyze the abnormal situation of the courier and the transportation capacity of each region based on the early warning report and the collection and delivery analysis report, and generate a summary report.

[0124] In this embodiment, the construction module 701 includes: an acquisition unit 7011, which is used to obtain order information, traffic conditions and weather data, analyze the distribution of shipping addresses and receiving addresses based on the order information to determine the service area, and divide the service area into several geographical areas, and assign a geographical code to each of the geographical areas; a division unit 7012, which is used to divide a day into multiple time slices, and count the number of orders, average traffic congestion index, and weather data code in each time slice and each geographical area; a construction unit 7013, which is used to construct a two-dimensional matrix, and fill the number of orders, average traffic congestion index, and weather data code in each time slice and each geographical area as eigenvalues into the corresponding elements of the two-dimensional matrix to obtain a spatiotemporal feature matrix, where the rows of the spatiotemporal feature matrix represent time slices and the columns represent geographical areas.

[0125] In this embodiment, the adjustment module 702 includes: a prediction unit 7021, which is used to input the spatiotemporal feature matrix into the pre-trained spatiotemporal graph convolutional network model to obtain the next N hours' collection and delivery fence adjustment coefficient output by the spatiotemporal graph convolutional network; a statistical unit 7022, which is used to count the order demand probability of each of the said geographical areas, and simulate the randomness of the order distribution of each of the said geographical areas in the next N hours through Monte Carlo sampling to generate a probability heat map; an adjustment unit 7023, which is used to determine the fence boundary adjustment direction and amplitude of each of the said geographical areas through weighted fusion based on the next N hours' collection and delivery fence adjustment coefficient and the probability heat map, and based on the fence boundary adjustment direction and amplitude, use GIS topology operation to generate a new collection and delivery fence boundary corresponding to each of the said geographical areas.

[0126] In this embodiment, the early warning module 703 includes: a calculation unit 7031, which is used to obtain the real-time geographic location of the courier and call the Euclidean distance formula to calculate the shortest distance between the real-time geographic location of the courier and the adjusted collection and delivery fence boundary; a comparison unit 7032, which is used to compare the shortest distance with a preset distance threshold to determine whether the shortest distance is less than the preset distance threshold; an early warning unit 7033, which is used to trigger an early warning when the shortest distance is less than the preset distance threshold, and generate an early warning report, wherein the early warning report includes the courier's basic information, current geographic location, actual distance from the fence boundary, early warning trigger time, and the collection and delivery fence boundary involved.

[0127] In this embodiment, the first analysis module 704 includes: a preprocessing unit 7041, which is used to obtain the courier's collection and delivery trajectory on the day, and preprocess the courier's collection and delivery trajectory on the day to obtain a preprocessed collection and delivery trajectory; a first analysis unit 7042, which is used to analyze and calculate the preprocessed collection and delivery trajectory and the order information to obtain the courier's residence time in each area and the collection and delivery task completion rate; a first generation unit 7043, which is used to present the courier's residence time in each area and the collection and delivery task completion rate in the form of a chart, and insert the chart into a preset collection and delivery analysis report template to generate a collection and delivery analysis report.

[0128] In this embodiment, the second analysis module 705 includes: an integration unit 7051, which is used to obtain the number of each courier, use the courier's number as the associated field, integrate the data involving the same courier in the early warning report and the collection and delivery analysis report, and construct a comprehensive data set; a second analysis unit 7052, which is used to analyze the courier's cross-border anomalies, efficiency anomalies and behavior pattern anomalies based on the comprehensive data set, generate an anomaly summary, and analyze the order demand and capacity matching, average collection and delivery efficiency and dynamic capacity changes in each region based on the comprehensive data set to generate a capacity summary for each region; a summary unit 7053, which is used to generate a summary report based on the anomaly summary and the capacity summary for each region.

[0129] In this embodiment, it constructs a spatiotemporal feature matrix through order information, traffic conditions and weather data to achieve dynamic adjustment of the collection and delivery fence boundaries, while monitoring the courier's location in real time and issuing timely warnings, deeply analyzing the collection and delivery data to generate a collection and delivery analysis report, and then comprehensively grasping the courier's abnormal situation and the transportation capacity of each region and generating a summary report, so that the express operation management can accurately grasp the business dynamics, respond to problems in advance, reasonably allocate resources, effectively improve the efficiency and quality of express services, and enhance the company's operational management capabilities and market competitiveness.

[0130] Figure 7 The structure of the courier dynamic monitoring and management device shown does not constitute a limitation on the courier dynamic monitoring and management device, and can implement the steps of the courier dynamic monitoring and management method provided by the above-mentioned method embodiments.

[0131] above Figure 7 The courier dynamic monitoring and management device in the embodiment of the present invention is described in detail from the perspective of modular functional entities. The courier dynamic monitoring and management device in the embodiment of the present invention is described in detail from the perspective of hardware processing.

[0132] Figure 8It is a structural diagram of a courier dynamic monitoring and management device provided by an embodiment of the present invention. The device 800 may have relatively large differences due to different configurations or performances, and may include one or more processors (central processing units, CPU) 810 (for example, one or more processors) and a memory 820, and one or more storage media 830 (for example, one or more massive storage devices) storing applications 833 or data 832. Among them, the memory 820 and the storage medium 830 can be short-term storage or persistent storage. The program stored in the storage medium 830 may include one or more modules (not shown), and each module may include a series of instruction operations on the device 800. Furthermore, the processor 810 can be configured to communicate with the storage medium 830 to execute a series of instruction operations in the storage medium on the device 800.

[0133] The device 800 may also include one or more power supplies 840, one or more wired or wireless network interfaces 850, one or more input and output interfaces 860, and / or one or more operating systems 831, such as Windows Server, Mac OS X, Unix, Linux, FreeBSD, etc.

[0134] An embodiment of the present invention also provides a computer-readable storage medium, which may be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium. Instructions are stored in the computer-readable storage medium. When the instructions are executed on a computer, the computer executes the steps of the courier dynamic monitoring and management method.

[0135] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described systems, devices, and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0136] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), magnetic disk or optical disk, etc., various media that can store program code.

[0137] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that the technical solutions described in the above embodiments can still be modified, or some of the technical features thereof can be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for dynamic monitoring and management of couriers, characterized in that: The courier dynamic monitoring and management method includes: Obtaining order information, traffic conditions, and weather data, and constructing a spatiotemporal feature matrix based on the order information, the traffic conditions, and the weather data, wherein rows of the spatiotemporal feature matrix represent time slices and columns represent geographic regions; Dynamically adjust the pickup and delivery fence boundaries of each of the geographical areas based on the spatiotemporal feature matrix; Obtain the courier's real-time geographic location, compare the courier's real-time geographic location with the adjusted delivery fence boundary, and trigger an early warning when the distance between the courier's real-time geographic location and the adjusted delivery fence boundary is less than a preset distance threshold, and generate an early warning report; Obtain the courier's collection and delivery trajectory for the day, analyze and calculate the courier's collection and delivery trajectory for the day and the order information, obtain the courier's stay time in each geographical area and the collection and delivery task completion rate, and generate a collection and delivery analysis report; According to the early warning report and the collection and delivery analysis report, the abnormal situation of the courier and the transportation capacity of each area are analyzed and a summary report is generated.

2. The courier dynamic monitoring and management method according to claim 1, characterized in that: The obtaining of order information, traffic conditions and weather data, and constructing a spatiotemporal feature matrix based on the order information, traffic conditions and weather data, includes: Obtaining order information, traffic conditions, and weather data, analyzing the distribution of shipping addresses and receiving addresses based on the order information to determine a service area, dividing the service area into a plurality of geographic areas, and assigning a geocode to each of the geographic areas; Divide a day into multiple time slices, and count the number of orders, average traffic congestion index, and weather data code in each time slice and each geographical area; A two-dimensional matrix is constructed, and the number of orders, the average traffic congestion index, and the weather data code in each time slice and each geographical area are filled into the corresponding elements of the two-dimensional matrix as characteristic values to obtain a spatiotemporal feature matrix, where the rows of the spatiotemporal feature matrix represent time slices and the columns represent geographical areas.

3. The courier dynamic monitoring and management method according to claim 2, characterized in that: The dynamically adjusting the pickup and delivery fence boundaries of each of the geographical areas based on the spatiotemporal feature matrix includes: Input the spatiotemporal feature matrix into the pre-trained spatiotemporal graph convolutional network model and obtain the fence adjustment coefficient for the next N hours of delivery output by the spatiotemporal graph convolutional network; Counting the order demand probability of each geographic area, and simulating the randomness of order distribution in each geographic area within the next N hours through Monte Carlo sampling to generate a probability heat map; Based on the fence adjustment coefficient for the next N hours of delivery and the probability heat map, the fence boundary adjustment direction and amplitude of each geographic area are determined through weighted fusion, and based on the fence boundary adjustment direction and amplitude, GIS topological operations are used to generate new fence boundaries for delivery corresponding to each geographic area.

4. The courier dynamic monitoring and management method according to claim 1, characterized in that: The courier's real-time geographic location is obtained, and the real-time geographic location of the courier is compared with the adjusted delivery fence boundary. When the distance between the courier's real-time geographic location and the adjusted delivery fence boundary is less than a preset distance threshold, an early warning is triggered, and an early warning report is generated, including: Obtain the courier's real-time geographic location and use the Euclidean distance formula to calculate the shortest distance between the courier's real-time geographic location and the adjusted delivery fence boundary. Compare the shortest distance with a preset distance threshold to determine whether the shortest distance is less than the preset distance threshold; If so, an early warning is triggered and an early warning report is generated. The early warning report includes the courier's basic information, current geographic location, actual distance from the fence boundary, early warning trigger time, and the fence boundary involved in the collection and delivery of parcels.

5. The courier dynamic monitoring and management method according to claim 1, characterized in that: The courier's collection and delivery trajectory for the day is obtained, and the courier's collection and delivery trajectory for the day and the order information are analyzed and calculated to obtain the courier's stay time in each geographical area and the collection and delivery task completion rate, and generate a collection and delivery analysis report, including: Obtaining the courier's collection and delivery trajectory for the day, and preprocessing the courier's collection and delivery trajectory for the day to obtain a preprocessed collection and delivery trajectory; Analyze and calculate the pre-processed delivery trajectory and the order information to obtain the courier's stay time in each area and the delivery task completion rate; The courier's stay time in each area and the completion rate of the collection and delivery task are presented in the form of a chart, and the chart is inserted into the preset collection and delivery analysis report template to generate a collection and delivery analysis report.

6. The courier dynamic monitoring and management method according to claim 5, characterized in that: The pre-processed delivery trajectory and the order information are analyzed and calculated to obtain the courier's stay time in each area and the delivery task completion rate, including: Determine the courier's stay time in each area based on the timestamp and location information of the pre-processed pickup and delivery trajectory; Count the total number of pickup and delivery tasks assigned to the courier on that day, the number of orders collected, and the number of orders delivered based on the order information; The completion rate of delivery tasks is calculated based on the total number of delivery tasks assigned to the courier on that day, the number of orders collected, and the number of orders delivered.

7. The courier dynamic monitoring and management method according to claim 1, characterized in that: The abnormal situation of the courier and the transportation capacity of each region are analyzed based on the early warning report and the collection and delivery analysis report, and a summary report is generated, including: Obtain each courier's ID, use the courier's ID as the correlation field, integrate the data related to the same courier in the early warning report and the collection and delivery analysis report, and construct a comprehensive data set; Analyze courier out-of-bounds anomalies, efficiency anomalies, and behavioral pattern anomalies based on the comprehensive data set to generate an anomaly summary. Analyze the matching of order demand and capacity in each region, average collection and delivery efficiency, and dynamic capacity changes based on the comprehensive data set to generate a capacity summary for each region. Generate a summary report based on the summary of abnormal situations and the transportation capacity of each area.

8. A courier dynamic monitoring and management device, characterized in that: include: A construction module is used to obtain order information, traffic conditions and weather data, and construct a spatiotemporal feature matrix based on the order information, traffic conditions and weather data, wherein the rows of the spatiotemporal feature matrix represent time slices and the columns represent geographical areas; An adjustment module, configured to dynamically adjust the pickup and delivery fence boundaries of each of the geographical areas based on the spatiotemporal feature matrix; An early warning module is used to obtain the courier's real-time geographic location and compare it with the adjusted delivery fence boundary. When the distance between the courier's real-time geographic location and the adjusted delivery fence boundary is less than a preset distance threshold, an early warning is triggered and an early warning report is generated; The first analysis module is used to obtain the courier's collection and delivery trajectory for the day, and analyze and calculate the courier's collection and delivery trajectory for the day and the order information to obtain the courier's stay time in each geographical area and the collection and delivery task completion rate, and generate a collection and delivery analysis report; The second analysis module is used to analyze the courier's abnormal situation and the transportation capacity of each region based on the early warning report and the collection and delivery analysis report, and generate a summary report.

9. A courier dynamic monitoring and management device, characterized in that: comprising a memory and at least one processor, wherein the memory has computer-readable instructions stored therein; The at least one processor calls the computer-readable instructions in the memory to execute each step of the courier dynamic monitoring and management method as described in any one of claims 1-7.

10. A computer-readable storage medium having computer-readable instructions stored thereon, characterized in that: When the computer-readable instructions are executed by a processor, the steps of the courier dynamic monitoring and management method as described in any one of claims 1 to 7 are implemented.

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