Visual logistics scheduling method, server, storage medium and program product

Abstract

The invention discloses a visual logistics scheduling method, a server, a storage medium and a program product, and relates to the field of logistics, and the method comprises the steps: obtaining a cargo position and a vehicle position when a logistics cargo is loaded to a logistics vehicle; comparing the cargo position with the vehicle position in real time to obtain a distance difference; when the distance difference between the cargo position and the vehicle position is out of a preset distance range, generating a cargo state abnormity prompt; when the distance difference between the cargo position and the vehicle position is within a preset distance range, the committed delivery time of the logistics cargo is determined according to the identification information of the logistics cargo; determining predicted arrival time according to the cargo position and / or the vehicle position; monitoring a time difference between the committed arrival time and the predicted arrival time; generating a logistics scheduling scheme according to the time difference; and carrying out visual display on the logistics scheduling scheme, the predicted delivery time and the committed delivery time. By implementing the method, the logistics scheduling efficiency is improved.

Description

Technical Field

[0001] The present application relates to the field of logistics, and in particular to a visual logistics scheduling method, server, storage medium and program product. Background Art

[0002] With the rapid development of e-commerce, the demand for logistics and distribution services has risen sharply. Effective logistics scheduling not only directly affects the distribution efficiency, but also affects the operating costs and customer satisfaction. Therefore, how to achieve accurate logistics scheduling has become the key to improving the quality and efficiency of logistics services.

[0003] At present, the logistics dispatching technology solution mainly divides the delivery orders of logistics goods into different delivery areas according to the receipt information of logistics goods, and assigns the delivery orders to the delivery vehicles in the corresponding delivery areas according to the preset delivery routes. By tracking the location of logistics vehicles, the logistics center monitors the specific logistics delivery situation.

[0004] However, due to the large scale of logistics and distribution business, and the large number of distribution routes and distribution points, the relevant technologies have some shortcomings in actual operation. For example, they can only passively display the location of the vehicle, while the status monitoring of the goods themselves is relatively weak. If the goods accidentally leave the vehicle during transportation, it may be difficult to detect this abnormal situation in time, thus delaying the response time. Summary of the invention

[0005] The present application provides a visual logistics scheduling method, server, storage medium and program product for improving the efficiency of logistics scheduling.

[0006] In a first aspect, the present application provides a visual logistics scheduling method, which is applied to a server, and the method includes: when logistics goods are loaded onto a logistics vehicle, obtaining the cargo position and the vehicle position; comparing the cargo position with the vehicle position in real time to obtain a distance difference; when the distance difference between the cargo position and the vehicle position is outside a preset distance range, generating an abnormal cargo status reminder; when the distance difference between the cargo position and the vehicle position is within the preset distance range, determining the promised delivery time of the logistics goods according to the identification information of the logistics goods; determining an expected delivery time according to the cargo position and / or the vehicle position; monitoring the time difference between the promised delivery time and the expected delivery time; generating a logistics scheduling plan according to the time difference; and visually displaying the logistics scheduling plan, the expected delivery time, and the promised delivery time.

[0007] By adopting the above technical solution, the server monitors the distance difference between the cargo location and the vehicle location in real time, and promptly detects abnormal situations such as cargo leaving the transport vehicle and issues an early warning. At the same time, the server determines the promised delivery time based on the identification information of the logistics cargo, and determines the estimated delivery time based on the real-time location data, and dynamically generates a logistics scheduling plan by comparing the time difference between the two. The visual display of this solution enables logistics personnel to intuitively grasp the logistics status and respond to possible delay risks in a timely manner, significantly improving the safety, punctuality and scheduling efficiency of goods during logistics transportation, and reducing the risk of cargo loss and delays.

[0008] In combination with some embodiments of the first aspect, in some embodiments, the cargo position is compared with the vehicle position in real time to obtain a distance difference, which specifically includes: collecting first time information of the cargo position and second time information of the vehicle position; when the time difference between the first time information and the second time information is less than a preset first time difference, comparing the cargo position with the vehicle position to obtain the distance difference between the cargo position and the vehicle position.

[0009] By adopting the above technical solution, the server collects the time information of the cargo location and the vehicle location, and compares the location according to the preset first time difference threshold, ensuring the timeliness and accuracy of the location data. Distance calculation is performed only when the cargo location and the vehicle location are collected in the same time period (the time difference between the first time information and the second time information is less than the preset first time difference), avoiding misjudgment caused by asynchronous information update, greatly improving the accuracy of abnormal situation judgment, reducing the false alarm rate, and making logistics monitoring more accurate and reliable.

[0010] In combination with some embodiments of the first aspect, in some embodiments, before the step of obtaining the cargo location and the vehicle location when the logistics cargo is loaded onto the logistics vehicle, the method also includes: determining the specifications, destination and time urgency of the logistics cargo based on the identification information of the logistics cargo; based on the specifications, the destination and the time urgency, determining the optimal logistics transportation plan, the optimal logistics transportation plan including a logistics vehicle, a logistics distribution route and a logistics time schedule.

[0011] By adopting the above technical solutions, before the logistics goods are loaded, the server will pre-plan the best logistics transportation plan based on the specifications, destination and time urgency of the logistics goods. This advance planning mechanism takes into account multiple key factors, including selecting suitable transportation vehicles, optimizing delivery routes and reasonably arranging delivery time. It not only improves the utilization efficiency of transportation resources, but also provides a benchmark reference for subsequent real-time monitoring and scheduling, thereby better balancing delivery efficiency and cost and improving the overall logistics service quality.

[0012] In combination with some embodiments of the first aspect, in some embodiments, the estimated delivery time is determined based on the cargo location and / or the vehicle location, specifically including: obtaining multiple candidate delivery routes from the cargo location and / or the vehicle location to the destination; based on historical traffic data, performing road condition scoring on the multiple candidate delivery routes, the road condition score being used to represent a comprehensive value of a congestion index, an accident risk index, and a road condition index; determining the candidate delivery route with the highest road condition score as a recommended delivery route; and determining the estimated delivery time of the logistics cargo based on the recommended delivery route and the cargo location and / or the vehicle location.

[0013] By adopting the above technical solution, the server obtains multiple candidate delivery routes and comprehensively scores these candidate delivery routes based on historical traffic data. The scoring criteria include key indicators such as congestion index, accident risk index and road condition index. This multi-dimensional evaluation method not only takes into account conventional traffic congestion, but also takes into account road safety and road condition quality. The server selects the route with the highest road condition score as the recommended delivery route, so that the estimated delivery time can be determined more accurately, avoiding the deviation that may be caused by considering only distance or congestion factors, and significantly improving delivery efficiency and punctuality.

[0014] In combination with some embodiments of the first aspect, in some embodiments, the logistics scheduling plan is generated based on the time difference, specifically including: when the time difference is less than a preset second time difference, an expedited delivery logistics vehicle is selected from idle logistics vehicles according to the specifications and time urgency of the logistics goods; and an expedited delivery route of the expedited delivery logistics vehicle is determined according to the location of the goods and the destination.

[0015] By adopting the above technical solution, when the server detects that the time difference between the expected delivery time and the promised delivery time is less than the preset second time difference, the expedited delivery mechanism will be activated. This intelligent emergency response mechanism can intervene in time at the early stage of possible delays in logistics goods, and catch up with the delivery progress by allocating additional transportation capacity. It not only improves the server's ability to respond to emergencies, but also ensures the quality of delivery services to the greatest extent, effectively reducing customer complaints and compensation risks caused by delays.

[0016] In combination with some embodiments of the first aspect, in some embodiments, the logistics scheduling plan is generated based on the time difference, specifically including: when the time difference is greater than or equal to the preset second time difference, sending a delivery delay notification to the recipient of the logistics goods; obtaining the recipient's feedback on the delivery delay notification.

[0017] By adopting the above technical solution, when the server detects that the time difference between the expected delivery time and the promised delivery time is greater than or equal to the preset second time difference, it will proactively send a delivery delay notification to the recipient and collect feedback. This proactive communication mechanism informs the recipient of possible delays in advance, allowing the recipient to adjust the delivery arrangements in a timely manner. At the same time, by collecting the recipient's feedback on the delivery delay notification, the logistics company can better understand customer needs and acceptance, and provide a basis for subsequent service improvements. This transparent delay handling mechanism can not only improve customer satisfaction, but also help logistics companies establish a more humane service system and reduce customer complaints caused by poor communication.

[0018] In combination with some embodiments of the first aspect, in some embodiments, after the step of visually displaying the logistics scheduling plan, the estimated delivery time and the promised delivery time, the method also includes: collecting real-time temperature data, real-time humidity data and real-time vibration data of the logistics goods during transportation; when the real-time temperature data exceeds the preset temperature threshold, the real-time humidity data exceeds the preset humidity threshold and / or the real-time vibration data exceeds the preset vibration threshold, it is determined that the logistics goods are in an abnormal state; and the abnormal state of the logistics goods is visually displayed.

[0019] By adopting the above technical solutions, the server collects and monitors the real-time temperature data, real-time humidity data and real-time vibration data of logistics goods during transportation, and establishes a comprehensive cargo status monitoring system. This multi-dimensional environmental monitoring mechanism can not only timely discover abnormal conditions that may affect the quality of logistics goods, but also provide data support for subsequent improvements in logistics service quality.

[0020] In a second aspect, an embodiment of the present application provides a server, comprising: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to enable the server to execute the method described in the first aspect and any possible implementation method of the first aspect.

[0021] In a third aspect, an embodiment of the present application provides a computer program product comprising instructions, which, when executed on a server, enables the server to execute the method described in the first aspect and any possible implementation of the first aspect.

[0022] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, comprising instructions, which, when executed on a server, enable the server to execute the method described in the first aspect and any possible implementation of the first aspect.

[0023] It is understandable that the server provided in the second aspect, the computer program product provided in the third aspect, and the computer storage medium provided in the fourth aspect are all used to execute the method provided in the embodiment of the present application. Therefore, the beneficial effects that can be achieved can refer to the beneficial effects in the corresponding method, which will not be repeated here.

[0024] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: 1. By adopting the above technical solution, the server monitors the distance difference between the cargo location and the vehicle location in real time, and promptly detects abnormal situations such as cargo leaving the transport vehicle and issues early warnings. At the same time, the server determines the promised delivery time based on the identification information of the logistics cargo, and determines the estimated delivery time based on the real-time location data, and dynamically generates a logistics scheduling plan by comparing the time difference between the two. The visual display of this solution enables logistics personnel to intuitively grasp the logistics status and respond to possible delay risks in a timely manner, significantly improving the safety, punctuality and scheduling efficiency of goods during logistics transportation, and reducing the risk of cargo loss and delays.

[0025] 2. By adopting the above technical solution, the server collects the time information of the cargo location and the vehicle location, and compares the location according to the preset first time difference threshold, ensuring the timeliness and accuracy of the location data. Distance calculation is performed only when the cargo location and the vehicle location are collected in the same time period (the time difference between the first time information and the second time information is less than the preset first time difference), avoiding misjudgment caused by asynchronous information update, greatly improving the accuracy of abnormal situation judgment, reducing the false alarm rate, and making logistics monitoring more accurate and reliable.

[0026] 3. By adopting the above technical solution, the server obtains multiple candidate delivery routes and comprehensively scores these candidate delivery routes based on historical traffic data. The scoring criteria include key indicators such as congestion index, accident risk index and road condition index. This multi-dimensional evaluation method not only takes into account conventional traffic congestion, but also takes into account road safety and road condition quality. The server selects the route with the highest road condition score as the recommended delivery route, so that the estimated delivery time can be determined more accurately, avoiding the deviation that may be caused by considering only distance or congestion factors, and significantly improving delivery efficiency and punctuality. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 This is a flow chart of a visual logistics scheduling method in an embodiment of the present application; Figure 2 is another flow chart of the visual logistics scheduling method in the embodiment of the present application; Figure 3It is a schematic diagram of a physical device structure of a server in an embodiment of the present application. DETAILED DESCRIPTION

[0028] The terms used in the following embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to be used as limitations to the present application. As used in the specification of the present application, the singular expressions "one", "a kind of", "above", "the" and "this" are intended to also include plural expressions, unless there is a clear indication to the contrary in the context. It should also be understood that the term "and / or" used in the present application refers to any or all possible combinations comprising one or more of the listed items.

[0029] In the following, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as suggesting or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features, and in the description of the embodiments of the present application, unless otherwise specified, "plurality" means two or more.

[0030] The following is a description of the process of the method provided by this implementation. Figure 1 , which is a flow chart of a visual logistics scheduling method in an embodiment of the present application.

[0031] S101. When the logistics goods are loaded onto the logistics vehicle, the location of the goods and the location of the vehicle are obtained; Among them, logistics goods refer to the goods entities that need to be transported and distributed, which may include parcels, express deliveries and other items, without limitation here; logistics vehicles refer to the means of transportation used to carry and transport logistics goods, including trucks, vans and other vehicles; cargo location refers to the current geographical coordinate location of the logistics goods, which is obtained through GPS positioning or other positioning devices; vehicle location refers to the current geographical coordinate location of the logistics vehicle, which is usually obtained through the on-board GPS device.

[0032] Specifically, the server establishes a communication connection with the positioning devices on the logistics goods (such as RFID tags, GPS trackers, etc.) to obtain the current geographical coordinates of the logistics goods in real time. At the same time, the server also obtains the current geographical coordinates of the logistics vehicle through the vehicle positioning system. These location information is recorded in the form of longitude and latitude, with timestamp information, to provide basic data support for subsequent location matching and abnormal monitoring.

[0033] S102, comparing the cargo position with the vehicle position in real time to obtain a distance difference; Among them, real-time comparison refers to the operation of continuous comparison at preset time intervals; distance difference refers to the straight-line distance or actual distance between the cargo location and the vehicle location, expressed in specific numerical units (such as meters, kilometers, etc.); preset time interval refers to the time difference between two location information collection and comparisons, which can be adjusted according to actual needs.

[0034] Specifically, the server inputs the cargo location and vehicle location into the distance calculation module, and calculates the distance difference between the cargo location and the vehicle location using the spherical distance formula or other distance calculation algorithms. The server will repeat the calculation process at a preset time interval (such as every 5 seconds, every 10 seconds, etc.) to continuously monitor the distance change between the cargo and the vehicle.

[0035] Optionally, under normal circumstances, the cargo location is compared with the vehicle location in real time to obtain the distance difference, which can be achieved in the following manner, which is not limited here: collecting the first time information of the cargo location and the second time information of the vehicle location; when the time difference between the first time information and the second time information is less than the preset first time difference, comparing the cargo location with the vehicle location to obtain the distance difference between the cargo location and the vehicle location.

[0036] S103, when the distance difference between the cargo position and the vehicle position is outside the preset distance range, generating a cargo status abnormality reminder; Among them, the preset distance range refers to the maximum distance threshold allowed between the cargo and the vehicle, which can be set according to different types of transportation scenarios; abnormal cargo status refers to the situation where the cargo may be out of vehicle control or unloaded incorrectly; abnormal cargo status refers to the alarm information generated by the server, including text, sound or other forms of prompt information.

[0037] Specifically, the server compares the calculated distance difference with the preset distance range. When the distance difference exceeds the preset distance range, the server will immediately generate a reminder of abnormal cargo status, including detailed information such as the time, location, and specific distance difference of the abnormal cargo status. At the same time, the server will send the reminder of abnormal cargo status to relevant personnel (such as dispatchers, logistics personnel, etc.) through various channels (such as display screens, mobile phone APP push, text messages, etc.) to ensure that relevant personnel can discover and handle abnormal situations in a timely manner to prevent logistics goods from being lost or delivered incorrectly.

[0038] S104: when the distance difference between the location of the goods and the location of the vehicle is within the preset distance range, determining the promised delivery time of the goods according to the identification information of the goods; Among them, identification information is information used to uniquely identify logistics goods, including waybill number, barcode, RFID tag, etc.; promised delivery time refers to the specific time point when the logistics company promises to deliver the logistics goods to the delivery address; the preset distance range refers to the reasonable distance range allowed between the goods and the vehicle set in advance by the server, usually ranging from a few decimeters to a few meters.

[0039] Specifically, first, the server verifies that the distance difference between the cargo location and the vehicle location is within the preset distance range, confirming that the logistics cargo has been correctly loaded. Then, the server queries the order database through the identification information of the logistics cargo to obtain the order time, delivery address and other information of the logistics cargo. Based on this information, the server calculates the specific promised delivery time according to the preset service timeliness rules (such as the next-day delivery in the same city must be delivered within 24 hours). At the same time, the server will take into account factors such as the current time and holidays to make appropriate adjustments to the promised delivery time to ensure the rationality and feasibility of the promised delivery time.

[0040] S105, determining an estimated delivery time according to the location of the goods and / or the location of the vehicle; Specifically, first, the server calls the path planning module to generate multiple delivery routes based on the current location and destination location of the cargo location and / or vehicle location. Then, the server will obtain the road condition information of each delivery route in real time, including real-time road conditions, historical traffic data, weather conditions, etc., and combine the distance of the delivery route, the expected average driving speed, possible stay time and other factors to calculate the optimal delivery route and its expected driving time through a preset algorithm. Finally, the server adds the calculated estimated driving time to the current time to obtain the estimated delivery time, where the estimated delivery time refers to the actual delivery time of the logistics goods estimated based on the current situation, and the estimated delivery time will be dynamically updated with the actual situation during the transportation process.

[0041] S106. Monitoring the time difference between the promised delivery time and the estimated delivery time; The time difference refers to the time interval between the estimated delivery time and the promised delivery time, which can be a positive value (indicating possible delay) or a negative value (indicating early delivery).

[0042] Specifically, the server regularly calculates the time difference between the estimated delivery time and the promised delivery time according to the preset monitoring frequency (such as every 5 minutes). When the calculated time difference exceeds a certain threshold (such as 2 hours early or 1 hour late), the server will mark the situation as an object that requires attention or intervention. At the same time, the server will record the changing trend of the time difference, such as whether the time difference is continuously expanding or shrinking, and use this information as an important reference for subsequent scheduling decisions.

[0043] S107, generating a logistics scheduling plan according to the time difference; Among them, the logistics scheduling plan refers to the capacity adjustment and route optimization plan formulated to optimize delivery time; the time difference refers to the time interval between the expected delivery time and the promised delivery time.

[0044] Specifically, first, the server classifies and processes the time difference according to the nature (early or late) and degree. For possible delays, the server will analyze from multiple dimensions: first, evaluate whether the current delivery route is optimal and whether there are faster alternative delivery routes; second, check whether there are nearby idle vehicles that can be deployed for support; and third, evaluate whether the logistics goods need to be transferred to other running logistics vehicles. The server will comprehensively consider the feasibility, cost-effectiveness and execution difficulty of various logistics scheduling plans, and select the optimal logistics scheduling plan. For early arrival, the server will evaluate whether more pickup tasks can be arranged to improve vehicle utilization.

[0045] S108: Visually display the logistics scheduling plan, the estimated delivery time, and the promised delivery time.

[0046] Specifically, the server converts logistics information into an intuitive graphical interface through a visual display interface. The current location of the logistics goods, the current location of the logistics vehicle, and the delivery route are marked on the electronic map, and different colors or icons are used to represent different states; the promised delivery time, estimated delivery time, and actual transportation progress are displayed through a timeline; the specific content of the logistics scheduling plan is displayed in the form of a chart, including scheduling vehicle information, route change details, expected results, etc. The server will display information of different granularity according to the permission level of different users: the dispatcher can view all the detailed information and perform logistics scheduling operations, while the customer can only view the logistics delivery progress information related to himself. The visual display interface supports a variety of interactive operations, such as zooming in and out of the map, switching display content, querying historical records, etc., and all displayed information will be updated in real time to ensure the timeliness of logistics information.

[0047] By adopting the above technical solution, the server monitors the distance difference between the cargo location and the vehicle location in real time, and promptly detects abnormal situations such as cargo leaving the transport vehicle and issues an early warning. At the same time, the server determines the promised delivery time based on the identification information of the logistics cargo, and determines the estimated delivery time based on the real-time location data, and dynamically generates a logistics scheduling plan by comparing the time difference between the two. The visual display of this solution enables logistics personnel to intuitively grasp the logistics status and respond to possible delay risks in a timely manner, significantly improving the safety, punctuality and scheduling efficiency of goods during logistics transportation, and reducing the risk of cargo loss and delays.

[0048] The following is a more detailed description of the process of the method provided by this implementation. Figure 2 , is another flow chart of the visual logistics scheduling method in an embodiment of the present application.

[0049] S201, determining the specifications, destination and time urgency of the logistics goods according to the identification information of the logistics goods; Among them, identification information is information used to uniquely identify logistics goods, including waybill number, barcode, RFID tag, etc.; specifications refer to the volume, weight, shape and other physical characteristic parameters of logistics goods; destination refers to the final location where the logistics goods need to be delivered, including detailed address, longitude and latitude coordinates, etc.; time urgency refers to the timeliness requirement level for logistics goods delivery, such as expedited, ordinary, economy, etc.

[0050] Specifically, first, the server queries the order database through the identification information to obtain detailed information about the logistics goods. For specification information, the server reads the specific size data (such as length 50cm, width 30cm, height 20cm), weight data (such as 5kg) and special attributes (such as fragile, waterproof, etc.) of the logistics goods. For destination information, the server not only obtains the specific address, but also parses the attribute characteristics of the address, such as whether it is in a restricted area, whether it is a closed community, whether an appointment is required, etc. For time urgency information, the server will comprehensively consider factors such as the service type selected by the customer (such as expedited items, ordinary items), special time requirements (such as delivery in a specified time period), and the characteristics of the receiving address (such as business district working hours restrictions), and assign the corresponding time urgency to the logistics goods.

[0051] S202: Determine the best logistics and transportation plan based on the specification, the destination and the time urgency, wherein the best logistics and transportation plan includes a logistics vehicle, a logistics distribution route and a logistics time arrangement.

[0052] Among them, the best logistics and transportation plan refers to the optimal distribution plan obtained after comprehensive consideration of various factors; logistics vehicles refer to vehicles used to perform logistics and transportation tasks, including vehicle model, load capacity and other information; logistics distribution routes refer to the optimal driving path from the current location to the destination; logistics time schedule refers to detailed distribution time node planning.

[0053] Specifically, first, the server selects suitable logistics vehicles according to the specifications of the logistics goods: match the vehicle model that meets the transportation requirements according to the volume and weight of the logistics goods; select special vehicles with corresponding functions considering special attributes (such as cold chain requirements); evaluate the distance between the current location of the logistics vehicle and the pickup location. Then, based on the destination information, the server combines real-time traffic data, historical traffic data and spatiotemporal distribution models to generate multiple candidate delivery routes. The server gives a comprehensive score to each candidate delivery route, considering factors including: expected driving time, road stability, distribution of waypoints, road restrictions, etc. Finally, the server formulates a detailed logistics time schedule based on the urgency of time: calculate the optimal departure time window, estimate the time of each key node, and set monitoring and early warning points. The server will verify the feasibility of the generated optimal logistics transportation plan to ensure that the optimal logistics transportation plan meets all constraints and has a certain fault tolerance space.

[0054] S203, when the logistics goods are loaded onto the logistics vehicle, obtaining the location of the goods and the location of the vehicle; For details, please refer to step S101, which will not be described in detail here.

[0055] S204, comparing the cargo position with the vehicle position in real time to obtain a distance difference; For details, please refer to step S102, which will not be described in detail here.

[0056] S205, when the distance difference between the cargo position and the vehicle position is outside the preset distance range, generating a cargo status abnormality reminder; For details, please refer to step S103, which will not be described in detail here.

[0057] S206: When the distance difference between the location of the goods and the location of the vehicle is within the preset distance range, determining the promised delivery time of the logistics goods according to the identification information of the logistics goods; For details, please refer to step S104, which will not be described in detail here.

[0058] S207, obtaining multiple candidate delivery routes from the cargo location and / or the vehicle location to the destination; Specifically, the server calls the path planning engine to generate multiple candidate delivery routes based on electronic map data. The candidate delivery route generation process takes into account a variety of factors: first, the passable road grade is determined based on the vehicle type; then different route preferences are considered, such as the shortest distance route, the shortest time route, and the high-speed priority route; the service requirements of the passing points are also considered, such as whether it is necessary to pass through other pickup points or delivery points. For each generated candidate delivery route, the server will record its detailed information, including the specific road section composition, the estimated driving distance, the road grade of each section, etc., to provide basic data for subsequent route evaluation.

[0059] S208. Based on historical traffic data, the road condition scores of the plurality of candidate delivery routes are scored, where the road condition scores are used to represent a comprehensive value of a congestion index, an accident risk index, and a road condition index; Among them, historical traffic data refers to traffic operation status information collected over a period of time in the past; the congestion index refers to the road's capacity level; the accident risk index refers to the possibility assessment value of a traffic accident occurring on a road section; and the road condition index refers to the assessment result of the physical conditions of the road.

[0060] Specifically, first, the server extracts historical data related to each candidate delivery route from the traffic database, including average vehicle speed, congestion, accident records, etc. at different times. Then, the server calculates three key indexes based on the preset scoring model: the congestion index is calculated based on historical traffic data and road capacity; the accident risk index is comprehensively evaluated through historical accident data, weather impact, road design and other factors; the road condition index considers aspects such as road surface quality, maintenance level, and construction impact. The server uses a weighted calculation method to dynamically adjust the weight of each index according to the characteristics of the current delivery task, and finally obtains the road condition score of each candidate delivery route.

[0061] S209, determining the candidate delivery route with the highest road condition score as the recommended delivery route; Specifically, the server sorts all candidate delivery routes from high to low according to the traffic score, and selects the candidate delivery route with the highest traffic score and exceeding the preset traffic score threshold as the recommended delivery route. If there are multiple routes with similar traffic scores (such as a score difference within 5%), the server will further consider other factors, such as the stability and adaptability of the route, to ensure that the recommended delivery route finally selected has strong reliability. At the same time, the server will save the suboptimal candidate delivery route as an alternative to cope with the need for route adjustment in emergencies.

[0062] S210, determining an estimated delivery time of the logistics goods according to the recommended delivery route and the location of the goods and / or the location of the vehicle; Specifically, first, the server calculates the benchmark driving time based on the distance and standard driving speed of the recommended delivery route. The benchmark driving time refers to the time required to complete the recommended delivery route under normal circumstances. Then, the server will consider multiple time influencing factors for adjustment: time correction based on the real-time road conditions of the current period; consider weather forecast information to assess possible delays; take into account the loading and unloading time and waiting time of the waypoints; and optimize based on the experience values ​​in the historical delivery data. Finally, the server will give an estimated delivery time with an error range, such as "estimated delivery at 14:30-15:00". This estimated delivery time will be dynamically updated as the delivery process progresses and the actual situation changes.

[0063] S211, monitoring the time difference between the promised delivery time and the estimated delivery time; For details, please refer to step S106, which will not be described in detail here.

[0064] S212. When the time difference is less than the preset second time difference, an expedited delivery logistics vehicle is selected from idle logistics vehicles according to the specifications and time urgency of the logistics goods; and an expedited delivery route of the expedited delivery logistics vehicle is determined according to the location of the goods and the destination.

[0065] Among them, the preset second time difference refers to the time threshold set in advance by the server for starting the expedited delivery task; the idle logistics vehicle refers to the logistics vehicle that can currently perform the expedited delivery task; the expedited delivery logistics vehicle refers to the logistics vehicle selected to perform the expedited delivery task; the expedited delivery route refers to the fast delivery path specially optimized for the expedited delivery task.

[0066] Specifically, first, the server confirms whether the time difference is less than the preset second time difference (such as less than 2 hours). After meeting the conditions, the server begins to screen suitable expedited delivery logistics vehicles: first query the status information of all idle logistics vehicles in the current area; screen qualified vehicles according to the specifications of the logistics goods (such as volume, weight, special storage conditions, etc.); consider the current location of the vehicle and the current location of the logistics goods, and give priority to vehicles with a closer distance; evaluate the vehicle's historical expedited delivery success rate. After determining the expedited delivery vehicle, the server will plan a special expedited delivery route: give priority to trunk roads with good traffic; consider whether to enable special access rights (such as using dedicated channels); set fewer waypoints to improve delivery efficiency; and reserve a certain amount of maneuvering time to deal with emergencies.

[0067] S213: When the time difference is greater than or equal to the preset second time difference, sending a delivery delay notification to the recipient of the logistics goods; and obtaining the recipient's feedback on the delivery delay notification; Among them, delivery delay notification refers to the delayed delivery information sent by the server to the recipient; the recipient refers to the recipient of the logistics goods; feedback refers to the recipient's choice of how to deal with the delay; the content of the delivery delay notification includes information such as the cause of the delay and the estimated delay time; the methods of delivery delay notification include SMS, application push, phone call and other forms.

[0068] Specifically, first, the server generates a standardized delivery delay notification, including: description of the current delivery status, estimated delay duration, explanation of the delay reason (such as weather reasons, traffic control, etc.), and a list of optional processing solutions. Then, the server sends it to the recipient through the preset notification channel (the priority is APP push, SMS, phone call, etc.). After the delivery delay notification is sent, the server will wait for the recipient's feedback and provide multiple standardized feedback options: such as accepting the delay and confirming the new delivery time, requesting a change in the delivery address, applying for a refund to cancel the order, etc. The server will trigger the corresponding subsequent processing flow based on the recipient's feedback: such as confirming the new delivery time, generating a refund document, adjusting the delivery route, etc.

[0069] S214, visually displaying the logistics scheduling plan, the estimated delivery time, and the promised delivery time; For details, please refer to step S108, which will not be described in detail here.

[0070] S215, collecting real-time temperature data, real-time humidity data and real-time vibration data of the logistics goods during transportation; Among them, real-time temperature data refers to the temperature monitoring value of the environment in which the logistics goods are located; real-time humidity data refers to the relative humidity value of the environment in which the logistics goods are located; real-time vibration data refers to the vibration and impact intensity to which the logistics goods are subjected.

[0071] Specifically, the server continuously collects environmental parameter data through a network of intelligent sensors installed on logistics vehicles or logistics cargo packaging. Temperature monitoring uses high-precision temperature sensors, which usually record data at intervals of 5 minutes with an accuracy of ±0.5°C; humidity monitoring uses professional humidity sensors to simultaneously record relative humidity values ​​with an error control within ±3%RH; vibration monitoring is achieved through a three-axis acceleration sensor, which can detect the vibration frequency and intensity of logistics cargo during transportation. These sensors transmit the collected data to the server in real time through the Internet of Things, and record the timestamp and geographic location information of the data collection to form a complete environmental parameter monitoring record.

[0072] S216: When the real-time temperature data exceeds a preset temperature threshold, the real-time humidity data exceeds a preset humidity threshold, and / or the real-time vibration data exceeds a preset vibration threshold, it is determined that the logistics goods are in an abnormal state; Among them, the preset temperature threshold refers to the upper and lower limits of the allowable temperature change range; the preset humidity threshold refers to the acceptable humidity fluctuation range; the preset vibration threshold refers to the maximum vibration intensity that the logistics goods can withstand; and the abnormal state refers to the situation where the environmental parameters exceed the safe range.

[0073] Specifically, the server compares the collected real-time data with the preset safety threshold: the preset temperature threshold is usually set according to the type of logistics goods, such as cold chain food may require 2-8°C; the preset humidity threshold takes into account the moisture-proof requirements of logistics goods, such as precision electronic products may require relative humidity to be maintained at 45%-65%; the preset vibration threshold is determined based on the seismic requirements of logistics goods, such as fragile items may set stricter vibration limits. When the real-time temperature data exceeds the preset temperature threshold, the real-time humidity data exceeds the preset humidity threshold, and / or the real-time vibration data exceeds the preset vibration threshold, the server will further analyze the abnormal situation: determine whether it is an instantaneous fluctuation or a continuous abnormality; evaluate the severity of the abnormality; determine the specific location and time point of the abnormality; record the environmental conditions and operation records when the abnormality occurs.

[0074] S217: Visually display the abnormal status of the logistics goods.

[0075] Specifically, the server converts abnormal status into intuitive visual elements: uses eye-catching colors (such as red, yellow, etc.) to identify different levels of abnormalities on the monitoring interface; displays the changing trend of environmental parameters through line graphs, and makes special marks on abnormal points; uses dashboards to display the comparison between real-time data and preset safety thresholds; provides detailed information cards for abnormal status, including information such as abnormality type, occurrence time, duration, and impact.

[0076] The following describes the server in the embodiment of the present invention from the perspective of hardware processing. Figure 3 , is a schematic diagram of a physical device structure of a server in an embodiment of the present application.

[0077] It should be noted that Figure 3 The structure of the server shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0078] like Figure 3 As shown, the server includes a central processing unit (CPU) 301, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 302 or the program loaded from the storage part 308 to the random access memory (RAM) 303, such as executing the method described in the above embodiment. In RAM 303, various programs and data required for system operation are also stored. CPU 301, ROM 302 and RAM 303 are connected to each other through bus 304. Input / output (I / O) interface 305 is also connected to bus 304.

[0079] The following components are connected to the I / O interface 305: an input section 306 including an audio input device, a button switch, etc.; an output section 307 including a liquid crystal display (LCD) and an audio output device, an indicator light, etc.; a storage section 308 including a hard disk, etc.; and a communication section 309 including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication section 309 performs communication processing via a network such as the Internet. A drive 310 is also connected to the I / O interface 305 as needed. A removable medium 311, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 310 as needed so that a computer program read therefrom is installed into the storage section 308 as needed.

[0080] In particular, according to an embodiment of the present invention, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present invention includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a computer program for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through the communication part 309, and / or installed from a removable medium 311. When the computer program is executed by the central processing unit (CPU) 301, various functions defined in the present invention are performed.

[0081] It should be noted that specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in combination with an instruction execution system, apparatus, or device.

[0082] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present invention. Each box in the flowchart or block diagram may represent a module, a program segment, or a part of a code, and the above-mentioned module, program segment, or a part of a code contains one or more executable instructions for implementing the specified logical functions. It should also be noted that in some alternative implementations, the functions marked in the box may also occur in an order different from that marked in the accompanying drawings.

[0083] Specifically, the server of this embodiment includes a processor and a memory. The memory stores a computer program. When the computer program is executed by the processor, the visual logistics scheduling method provided in the above embodiment is implemented.

[0084] As another aspect, the present invention further provides a computer-readable storage medium, which may be included in the server described in the above embodiment; or may exist independently without being assembled into the server. The above storage medium carries one or more computer programs, and when the above one or more computer programs are executed by a processor of the server, the server implements the visual logistics scheduling method provided in the above embodiment.

[0085] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

[0086] As used in the above embodiments, the term "when..." may be interpreted to mean "if..." or "after..." or "in response to determining..." or "in response to detecting...", depending on the context. Similarly, the phrases "upon determining..." or "if (the stated condition or event) is detected" may be interpreted to mean "if determining..." or "in response to determining..." or "upon detecting (the stated condition or event)" or "in response to detecting (the stated condition or event)", depending on the context.

[0087] Those skilled in the art can understand that to implement all or part of the processes in the above-mentioned embodiments, the processes can be completed by computer programs to instruct related hardware, and the programs can be stored in computer-readable storage media. When the programs are executed, they can include the processes of the above-mentioned method embodiments. The aforementioned storage media include: ROM or random access memory RAM, magnetic disk or optical disk and other media that can store program codes.

Claims

1. A visual logistics scheduling method, characterized in that: Applied to a server, the method comprises: When the logistics goods are loaded onto the logistics vehicle, obtain the location of the goods and the vehicle; Comparing the cargo position with the vehicle position in real time to obtain a distance difference; When the distance difference between the cargo position and the vehicle position is outside the preset distance range, generating a cargo status abnormality reminder; When the distance difference between the location of the goods and the location of the vehicle is within the preset distance range, determining the promised delivery time of the logistics goods according to the identification information of the logistics goods; Determine an estimated delivery time based on the cargo location and / or the vehicle location; monitoring the time difference between the promised delivery time and the estimated delivery time; generating a logistics scheduling plan according to the time difference; The logistics scheduling plan, the estimated delivery time and the promised delivery time are displayed visually.

2. The method according to claim 1, characterized in that The real-time comparison of the cargo position with the vehicle position to obtain a distance difference specifically includes: Collecting first time information of the cargo location and second time information of the vehicle location; When the time difference between the first time information and the second time information is less than a preset first time difference, the cargo position is compared with the vehicle position to obtain a distance difference between the cargo position and the vehicle position.

3. The method according to claim 1, characterized in that Before the step of obtaining the cargo position and the vehicle position when the logistics cargo is loaded onto the logistics vehicle, the method further includes: Determining the specifications, destination and time urgency of the logistics goods according to the identification information of the logistics goods; Based on the specifications, the destination and the time urgency, an optimal logistics transportation plan is determined, and the optimal logistics transportation plan includes a logistics vehicle, a logistics distribution route and a logistics time arrangement.

4. The method according to claim 3, characterized in that Determining the estimated delivery time according to the cargo location and / or the vehicle location specifically includes: Acquire multiple candidate delivery routes from the cargo location and / or the vehicle location to the destination; Based on historical traffic data, a road condition score is performed on the plurality of candidate delivery routes, wherein the road condition score is used to represent a comprehensive value of a congestion index, an accident risk index, and a road condition index; Determine the candidate delivery route with the highest road condition score as the recommended delivery route; The estimated delivery time of the logistics goods is determined based on the recommended delivery route and the goods location and / or the vehicle location.

5. The method according to claim 4, characterized in that Generating a logistics scheduling plan according to the time difference specifically includes: When the time difference is less than the preset second time difference, an expedited delivery logistics vehicle is selected from idle logistics vehicles according to the specifications and time urgency of the logistics goods; An expedited delivery route of the expedited delivery logistics vehicle is determined according to the cargo location and the destination.

6. The method according to claim 5, characterized in that Generating a logistics scheduling plan according to the time difference specifically includes: When the time difference is greater than or equal to the preset second time difference, sending a delivery delay notification to the recipient of the logistics goods; Obtain feedback from the recipient regarding the delivery delay notification.

7. The method according to claim 1, characterized in that After the step of visually displaying the logistics scheduling plan, the estimated delivery time, and the promised delivery time, the method further includes: Collecting real-time temperature data, real-time humidity data and real-time vibration data of the logistics goods during transportation; When the real-time temperature data exceeds a preset temperature threshold, the real-time humidity data exceeds a preset humidity threshold, and / or the real-time vibration data exceeds a preset vibration threshold, it is determined that the logistics goods are in an abnormal state; The abnormal status of the logistics goods is visually displayed.

8. A server, characterized in that: The server includes: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to enable the server to execute the method described in any one of claims 1-7.

9. A computer-readable storage medium comprising instructions, characterized in that: When the instructions are executed on a server, the server is caused to execute the method according to any one of claims 1 to 7.

10. A computer program product, characterized in that When the computer program product is run on a server, the server is caused to execute the method according to any one of claims 1 to 7.

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