Instant lottery ticket intelligent delivery scheduling system and method based on Internet of Things

Abstract

The invention relates to the technical field of delivery scheduling, and particularly discloses an intelligent instant lottery delivery scheduling system and method based on the Internet of Things, and the system achieves the whole-process intelligent scheduling of instant lottery delivery through the cooperation of multiple modules: a path generation module generates a plurality of candidate paths based on an order end point; constructing a time period thermodynamic diagram in combination with historical accident data; the real-time traffic flow, the road condition parameters and the risk thermodynamic diagram are superposed through a dynamic optimization algorithm, a path optimization coefficient is calculated through multi-factor weighting, and an optimal path is screened; the personnel matching mechanism dynamically allocates a candidate set according to the current waybill saturation of the transportation personnel in the optimal path neighborhood, and determines the final delivery personnel in combination with the order receiving response speed; and the intelligent supervision module monitors the positions of the personnel and the intelligent transportation box in real time through GPS positioning, and dynamically assigns a weight to unlock the authority until the signing party completes block chain evidence storage signing. The system realizes closed-loop management of path planning, personnel matching and whole-process monitoring.

Description

Technical Field

[0001] The present invention relates to the technical field of delivery and scheduling, and in particular to an intelligent delivery and scheduling system and method for instant lottery tickets based on the Internet of Things. Background Art

[0002] At present, with the booming lottery industry, instant lottery has become an important part of the lottery market with its characteristics of quick prize drawing and strong fun. With the growing demand for instant lottery among consumers, how to efficiently and accurately deliver instant lottery has become a key link in lottery operation and management. As a cutting-edge technology with great development potential, the Internet of Things technology is gradually penetrating into various industries and fields, bringing opportunities for innovation and change to traditional industries. Applying the Internet of Things technology to the delivery and dispatching system of instant lottery is expected to realize the intelligent and refined management of the delivery process, improve the overall operational efficiency and service quality, and has broad development prospects.

[0003] In the traditional instant lottery delivery dispatch process, delivery route planning often relies on experience or simple map navigation, without fully considering real-time traffic conditions, historical accident data, and dynamic changes in road conditions. This results in the delivery route being suboptimal, which not only increases delivery time and cost, but may also cause delivery delays due to poor road conditions. In terms of the allocation of transport personnel, fixed regional divisions or first-come-first-served principles are usually adopted, lacking comprehensive consideration of the real-time waybill situation of transport personnel, making it difficult to achieve reasonable task allocation. This may cause some transport personnel to be overloaded with tasks, while some personnel are idle, reducing the overall delivery efficiency. Moreover, during the delivery process, it mainly relies on regular reporting and limited logistics information tracking, lacking an effective supervision mechanism. It is impossible to obtain the location information of transport personnel and lottery transport boxes in real time and accurately, making it difficult to detect and handle abnormal situations in the delivery process in a timely manner, and it is also impossible to accurately control the authority of transport personnel, which poses certain security risks, such as lottery ticket loss or mistaken collection.

[0004] Therefore, the present invention proposes an intelligent delivery and dispatching system and method for instant lottery tickets based on the Internet of Things. Summary of the invention

[0005] The present invention provides an instant lottery intelligent delivery scheduling system and method based on the Internet of Things, including: The delivery path and area analysis module generates multiple delivery paths based on the delivery end position, determines the coverage area, and combines historical accident records to obtain the delivery accident heat map within each analysis duration period, providing a comprehensive historical risk reference for path planning. The path optimization analysis module superimposes and analyzes the real-time traffic flow, the latest road condition evaluation parameters, and the delivery accident heat map, obtains the optimization coefficient of each path at the target delivery moment, and screens out the initial optimized delivery path, so that the path selection comprehensively considers the real-time situation and potential risks, improving the delivery efficiency and safety. The transporter dual-selection module assigns an optimized transporter set for the target instant lottery delivery order based on the current order assignment information of all transporters within the neighborhood of the initial optimized delivery path, and determines the final transporter based on the order reply results of the optimized transporter set, realizing the reasonable allocation of transportation resources. The delivery intelligent supervision module unlocks and authorizes the communication device terminal of the transporter in real time by comparing the real-time positioning data of the final transporter and the intelligent lottery transport box with the delivery end position until the receipt information is received, effectively ensuring the safety and controllability of the delivery process and ensuring the accurate and safe delivery of instant lottery tickets. The overall solution can break through the limitations of the traditional mode by integrating functions such as real-time data, intelligent analysis, and remote monitoring. It can use Internet of Things devices to collect multi-dimensional data such as traffic and location in real time, providing comprehensive and accurate information support for delivery scheduling, which is of great significance for improving the efficiency and safety of instant lottery delivery, enhancing the user experience, and promoting the digital transformation of the lottery industry.

[0006] The present invention provides an instant lottery intelligent delivery scheduling system based on the Internet of Things, including: A delivery path and area analysis module, configured to generate multiple delivery paths based on the delivery end position of a target instant lottery delivery order, determine a target delivery path coverage area covering all the delivery paths, and analyze a delivery accident heat map of the target delivery path coverage area within each analysis duration period based on historical delivery accident records; A path optimization analysis module, configured to superimpose and analyze the real-time traffic flow of each delivery path, the latest road condition evaluation parameters, and the delivery accident heat map of the target delivery path coverage area within each analysis duration period, analyze the optimization coefficient of each delivery path at the target delivery moment of the target instant lottery delivery order, and screen out the delivery path with the maximum optimization coefficient as the initial optimized delivery path; A transporter dual-selection module, configured to assign an optimized transporter set for the target instant lottery delivery order based on the current order assignment information of all transporters within the neighborhood of the initial optimized delivery path, and assign a final transporter for the target instant lottery delivery order based on the order reply results of the optimized transporter set; The delivery intelligent supervision module is used to perform real-time unlocking and empowerment for the communication device terminal of the final transporter based on the real-time positioning data of the communication device terminal of the final transporter, the real-time positioning data of the intelligent lottery transport box, and the delivery end position of the target instant lottery delivery order until the receipt information of the recipient of the target instant lottery delivery order is received.

[0007] Optionally, the delivery path and area analysis module includes: The delivery path determination sub-module is used to query the electronic map and determine multiple delivery paths between the delivery start position and the delivery end position of the target instant lottery delivery order; The delivery area division sub-module is used to determine the smallest square geographical area covering all delivery paths as the target delivery path coverage area; The accident heat map generation sub-module is used to analyze the delivery accident heat map of the target delivery path coverage area in each analysis duration period based on the historical delivery accident records.

[0008] Optionally, the path optimization analysis module includes: The relative risk coefficient analysis sub-module is used to analyze the local relative risk coefficient of each delivery path in each analysis duration period based on the delivery accident heat map of the target delivery path coverage area in each analysis duration period; The optimization coefficient calculation sub-module is used to calculate the optimization coefficient of each delivery path at the target delivery time of the target instant lottery delivery order based on the real-time traffic flow and the latest road condition evaluation parameters of each delivery path and the local relative risk coefficient in each analysis duration period; The optimized path screening sub-module is used to screen out the delivery path with the maximum optimization coefficient among all delivery paths as the initial optimized delivery path.

[0009] Optionally, the optimization coefficient calculation sub-module includes: The traffic flow prediction unit is used to predict the traffic flow of each delivery path at the target delivery time based on the real-time traffic flow of each delivery path; The optimization coefficient calculation unit is used to calculate the optimization coefficient of each delivery path at the target delivery time of the target instant lottery delivery order based on the traffic flow of each delivery path at the target delivery time, the latest road condition evaluation parameters, and the local relative risk coefficient in each analysis duration period: ; Wherein, is the optimization coefficient of the currently calculated single delivery path at the target delivery time of the target instant lottery delivery order, is the weight of the real-time traffic flow, is the real-time traffic flow of the currently calculated single delivery route at the target delivery moment, is the weight of the latest road condition evaluation parameter, is the latest road condition evaluation parameter of the currently calculated single delivery route, is the weight of the local relative danger coefficient, is the total number of all analysis duration periods, For the currently calculated single delivery route at the local relative danger coefficient within the analysis duration period, For the duration length of the analysis duration period.

[0010] Optionally, the transporter dual-selection module includes: The cost and busyness evaluation sub-module is used to evaluate the dual-end order-taking cost and order-dispatching busyness of each transporter in the neighborhood of the initial preferred delivery route at the target delivery moment of the target instant lottery delivery order based on the current order assignment information of all transporters in the neighborhood of the initial preferred delivery route; The order-dispatching preference analysis sub-module is used to calculate the order-dispatching preference of each transporter based on the dual-end order-taking cost and order-dispatching busyness of each transporter in the neighborhood of the initial preferred delivery route at the target delivery moment of the target instant lottery delivery order; The preferred transporter primary selection sub-module is used to generate a transporter preference sequence based on the order-dispatching preferences of all transporters in the neighborhood of the initial preferred delivery route, and allocate a preferred transporter set for the target instant lottery delivery order based on the transporter preference sequence; The preferred transporter final selection sub-module is used to send the target instant lottery delivery order to the preferred transporter set, and allocate the final transporter for the target instant lottery delivery order based on the order reply results of the preferred transporter set.

[0011] Optionally, the cost and busyness evaluation sub-module includes: The transporter weight analysis unit is used to determine the transporter-end order-taking cost weight and the unit transportation cost under the preset order cost division unit of each transporter based on the current weight of each transporter in the neighborhood of the initial preferred delivery route; The dual-end order-taking cost evaluation unit is used to calculate the dual-end order-taking cost of each transporter in the neighborhood of the initial preferred delivery route at the target delivery moment of the target instant lottery delivery order based on the transporter-end order-taking cost weight of each transporter: ; In the formula, is the transporter-end order-taking cost weight of the currently calculated single transporter, is the path cost weight at the order-dispatching end, is the length of the initial preferred delivery path, is the transportation cost weight of the order dispatch end, is the unit transportation cost of the currently calculated single transporter under the preset order cost division unit, is the statistical value of the target instant lottery delivery order under the preset order cost division unit, is the path cost weight of the transporter end of the currently calculated single transporter, is the relative order receiving income loss weight of the transporter end of the currently calculated single transporter, is the historical average order receiving income of the currently calculated single transporter at the target delivery moment, is the expected order receiving income when the currently calculated single transporter receives the target instant lottery delivery order; An order dispatch busyness prediction unit, which is used to predict the order dispatch busyness of each transporter in the neighborhood of the initial preferred delivery path at the target delivery moment of the target instant lottery delivery order.

[0012] Optionally, the order dispatch busyness prediction unit includes: A final position determination subunit, which is used to obtain the final order dispatch terminal position of each transporter in the neighborhood of the initial preferred delivery path before the target delivery moment of the target instant lottery delivery order; An order dispatch busyness prediction subunit, which is used to input the final order dispatch terminal position of each transporter before the target delivery moment of the target instant lottery delivery order, the current weight of the transporter, and the target delivery moment of the target instant lottery delivery order into a preset order dispatch busyness prediction model, and obtain the order dispatch busyness of each transporter in the neighborhood of the initial preferred delivery path at the target delivery moment of the target instant lottery delivery order.

[0013] Optionally, the order dispatch preference analysis sub-module includes: A transporter weight acquisition unit, which is used to obtain the current weight of each transporter in the neighborhood of the initial preferred delivery path; An order dispatch preference calculation unit, which is used to calculate the order dispatch preference of each transporter based on the double-end order receiving cost, order dispatch busyness, and current weight of each transporter in the neighborhood of the initial preferred delivery path at the target delivery moment of the target instant lottery delivery order: ; In the formula, is the order dispatch preference of the currently calculated single transporter, is the weight of the double-end order receiving cost, is the weight of the order dispatch busyness, is the order dispatch busyness degree of the single transporter being currently calculated at the target dispatch moment of the target instant lottery delivery order, is the weight of the current weight of the single transporter being currently calculated, is the order dispatch preference degree of the single transporter being currently calculated.

[0014] Optionally, the delivery intelligent supervision module includes: The dual-position monitoring sub-module is used to calculate the error value between the real-time positioning data of the communication device terminal of the final transporter and the real-time positioning data of the intelligent lottery transport box in real time when any of the real-time positioning data of the communication device terminal of the final transporter and the real-time positioning data of the intelligent lottery transport box reaches the delivery end position of the target instant lottery delivery order; The unlocking and empowerment sub-module is used to grant the communication device terminal of the final transporter the permission to unlock the corresponding intelligent lottery transport box until the error value between the real-time positioning data of the communication device terminal of the final transporter and the real-time positioning data of the intelligent lottery transport box is less than the preset error value. At the same time, an unpacking warning message is sent to the recipient of the target instant lottery delivery order, and the duration after unpacking is counted; The order monitoring sub-module is used to mark the target instant lottery delivery order as completed at the total monitoring end when the receipt information of the recipient of the target instant lottery delivery order is received within the duration after unpacking is less than the duration after unpacking threshold, otherwise a three-party alarm message is sent.

[0015] The present invention provides an instant lottery intelligent delivery scheduling method based on the Internet of Things, which is applied to any of the above instant lottery intelligent delivery scheduling systems based on the Internet of Things, and includes: S1: Generate multiple delivery paths based on the delivery end position of the target instant lottery delivery order, determine the target delivery path coverage area covering all delivery paths, and analyze the delivery accident heat map of the target delivery path coverage area in each analysis duration period based on the historical delivery accident records; S2: Perform superposition analysis on the real-time traffic flow and the latest road condition evaluation parameters of each delivery path and the delivery accident heat map of the target delivery path coverage area in each analysis duration period, analyze the preference coefficient of each delivery path at the target delivery moment of the target instant lottery delivery order, and screen out the delivery path with the maximum preference coefficient as the initial preferred delivery path; S3: Based on the current waybill allocation information of all transporters in the neighborhood of the initial preferred delivery path, allocate a preferred transporter set for the target instant lottery delivery order, and allocate a final transporter for the target instant lottery delivery order based on the waybill reply results of the preferred transporter set; S4: Based on the real-time positioning data of the communication device terminal of the final transporter, the real-time positioning data of the intelligent lottery transport box, and the delivery end position of the target instant lottery delivery order, real-time unlocking authorization is performed for the communication device terminal of the final transporter until the receipt information of the recipient of the target instant lottery delivery order is received.

[0016] The beneficial effects of the present invention compared with the prior art are as follows: The delivery path and area analysis module generates multiple delivery paths based on the delivery end position, determines the coverage area, and combines historical accident records to obtain the delivery accident heat map within each analysis cycle, providing a comprehensive historical risk reference for path planning. The path optimization analysis module superimposes and analyzes the real-time traffic flow, the latest road condition evaluation parameters, and the accident heat map to obtain the optimization coefficient of each path at the target delivery time, and screens out the initial optimized delivery paths, enabling the path selection to comprehensively consider the real-time situation and potential risks, and improving the delivery efficiency and safety. The transporter dual-selection module assigns an optimized transporter set for the order according to the waybill information of the transporters within the neighborhood of the initial optimized path, and determines the final transporter based on their reply results, realizing the reasonable allocation of transportation resources. The intelligent delivery supervision module unlocks and authorizes the communication device terminal of the transporter in real time by comparing the real-time positioning data of the final transporter and the intelligent lottery transport box with the delivery end position until the receipt information is received, effectively ensuring the safety and controllability of the delivery process and ensuring the accurate and safe delivery of instant lottery tickets. The overall solution can break through the limitations of the traditional mode by integrating functions such as real-time data, intelligent analysis, and remote monitoring. It can use Internet of Things devices to collect multi-dimensional data such as traffic and location in real time, providing comprehensive and accurate information support for delivery scheduling, which is of great significance for improving the efficiency and safety of instant lottery delivery, enhancing the user experience, and promoting the digital transformation of the lottery industry.

[0017] Other features and advantages of the present invention will be described in the following specification, and part of them will become obvious from the specification or be understood by implementing the present invention. The objectives and other advantages of the present invention can be achieved and obtained through the structures specifically pointed out in this application document.

[0018] The technical solution of the present invention will be further described in detail below through the drawings and embodiments. Description of the Drawings

[0019] The drawings are used to provide a further understanding of the present invention, and constitute a part of the specification. They are used to explain the present invention together with the embodiments of the present invention, and do not constitute a limitation to the present invention. In the drawings: Figure 1 It is a schematic diagram of the instant lottery intelligent delivery scheduling system based on the Internet of Things in the embodiment of the present invention. Detailed Embodiments

[0020] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are only for the purpose of illustrating and explaining the present invention, and are not intended to limit the present invention.

[0021] Embodiment 1 Reference Figure 1 , the present invention provides an instant lottery intelligent delivery scheduling system based on the Internet of Things, including: A delivery path and area analysis module, configured to generate multiple delivery paths based on the delivery end position of the target instant lottery delivery order, determine a target delivery path coverage area covering all the delivery paths, and analyze a delivery accident heat map of the target delivery path coverage area in each analysis duration based on historical delivery accident records; A path optimization analysis module, configured to perform superimposed analysis on the real-time traffic flow and the latest road condition evaluation parameters of each delivery path and the delivery accident heat map of the target delivery path coverage area in each analysis duration, analyze the optimization coefficient of each delivery path at the target delivery time of the target instant lottery delivery order, and screen out the delivery path with the maximum optimization coefficient as the initial optimized delivery path; A transporter dual-selection module, configured to allocate an optimized transporter set for the target instant lottery delivery order based on the current waybill allocation information of all transporters within the neighborhood of the initial optimized delivery path, and allocate a final transporter for the target instant lottery delivery order based on the waybill reply results of the optimized transporter set; A delivery intelligent supervision module, configured to perform real-time unlocking authorization on the communication device terminal of the final transporter based on the real-time positioning data of the communication device terminal of the final transporter, the real-time positioning data of the intelligent lottery transport box, and the delivery end position of the target instant lottery delivery order until the receipt information of the recipient of the target instant lottery delivery order is received.

[0022] In this embodiment, the target instant lottery delivery order refers to a task instruction that needs to deliver instant lottery from the delivery starting point to a specific delivery end point, including various information related to the delivery, and is the core task around which the entire intelligent delivery scheduling system operates. For example, an instant lottery delivery request order received by a lottery supplier from a certain lottery retail outlet.

[0023] In this embodiment, the delivery end position is the final delivery location of the lottery specified in the target instant lottery delivery order, used to clarify the end position of the delivery path, such as the specific address of a lottery retail store.

[0024] In this embodiment, the delivery route is an optional route between the delivery starting position and the delivery ending position, obtained by querying an electronic map or the like. The system will generate multiple routes for subsequent screening and optimization. For example, the routes formed by different road combinations between the lottery warehouse and a certain sales point.

[0025] In this embodiment, the target delivery route coverage area is the smallest square geographical area that can cover all the generated delivery routes, which determines the scope for analyzing the heat map of delivery accidents. For example, all delivery routes are within the square area extending around a certain area.

[0026] In this embodiment, the historical delivery accident records are the relevant records of accidents that occurred during the delivery of instant lottery tickets in the past, including detailed information such as the time and location of the accidents, used to analyze the accident occurrence conditions in different regions and assist in planning safer delivery routes. For example, the record of a lottery delivery vehicle rolling over due to bad weather on a certain road.

[0027] In this embodiment, the multiple analysis duration periods are different time spans set when analyzing the historical delivery accident records, such as daily, weekly, monthly, etc. as the analysis periods, to comprehensively understand the accident distribution laws at different time scales.

[0028] In this embodiment, the heat map of delivery accidents in the target delivery route coverage area for each analysis duration period shows graphically the frequency and hot spot distribution of delivery accidents in the target delivery route coverage area during different analysis duration periods. The darker the color, the higher the accident occurrence frequency, intuitively presenting the accident risk distribution in this area at different time periods. For example, in the heat map with a weekly analysis period, a certain area shows dark red due to frequent accidents.

[0029] In this embodiment, the real-time traffic flow is the traffic volume status on each delivery route at the current moment, which reflects the congestion degree of the road in real time and is one of the key factors affecting route optimization. For example, the number of vehicles passing through a certain road per minute at this moment.

[0030] In this embodiment, the latest road condition evaluation parameter is a quantitative evaluation value of the current road conditions of each delivery route, obtained by comprehensively considering factors affecting traffic such as road construction and pavement damage degree, and is used to measure the traffic quality of the route. For example, if the road is impassable due to maintenance, this situation will be reflected in the road condition evaluation parameter.

[0031] In this embodiment, the target delivery time is the time point when it is planned to deliver the target instant lottery ticket delivery order. Operations such as route optimization analysis are carried out around the road conditions, risks and other factors at this time point. For example, it is planned to deliver the lottery tickets to the designated sales point at 10 am, and 10 am is the target delivery time.

[0032] In this embodiment, the preference coefficient of each delivery route at the target delivery time of the target instant lottery delivery order is a value calculated by comprehensively considering factors such as real-time traffic flow, the latest road condition assessment parameters, and the local relative risk coefficient within different analysis duration periods. It is used to measure the comprehensive advantage degree of each delivery route at the target delivery time, and the higher the value, the more preferentially it is selected. For example, after formula calculation, the preference coefficient of a certain route is 0.75.

[0033] In this embodiment, the current order assignment information of the transportation personnel refers to the details of the delivery tasks currently undertaken by each transportation personnel, including the number of assigned orders, the estimated completion time, etc. It is used to evaluate the work saturation degree of the transportation personnel, so as to reasonably allocate new orders. For example, a certain transportation personnel currently has 2 delivery orders at hand and is expected to complete them in 1.5 hours.

[0034] In this embodiment, the preferred transportation personnel set is a group of transportation personnel selected as the candidate group for determining the final transportation personnel, which has a high potential to undertake the target instant lottery delivery order. It is calculated based on factors such as the double-end order receiving cost and order dispatching busyness degree of the transportation personnel within the neighborhood of the initial preferred delivery route.

[0035] In this embodiment, the order reply result is the response information of whether to receive the order given by the transportation personnel in the preferred transportation personnel set for the target instant lottery delivery order. The system determines the final transportation personnel based on this result. For example, a certain transportation personnel replies to agree to undertake this order.

[0036] In this embodiment, the final transportation personnel is the person who actually undertakes the delivery of the target instant lottery delivery order determined from the preferred transportation personnel set through a series of screening processes based on the order reply result.

[0037] In this embodiment, the communication device terminal of the final transportation personnel is a communication tool with real-time positioning function used by the final transportation personnel, such as a mobile phone or a dedicated positioning device, which is used to real-time feedback the location information of the transportation personnel for operations such as system monitoring and unlocking authorization.

[0038] In this embodiment, the real-time positioning data is the geographical location information of the communication device terminal of the final transportation personnel and the intelligent lottery transportation box at each moment obtained through positioning technologies such as GPS, which is used to real-time track their locations. For example, the longitude and latitude coordinates of the location where the transportation personnel is at a certain moment.

[0039] In this embodiment, unlocking and empowerment are carried out when the real-time positioning data of the communication device terminal of the final transporter and the intelligent lottery transportation box meet specific conditions (the error value between the two is less than the preset error value), and the communication device terminal of the final transporter is given the permission to open the corresponding intelligent lottery transportation box to ensure that the lottery is delivered at the correct location. For example, when the transporter arrives near the delivery destination and the position error from the lottery transportation box is within the allowable range, their mobile phone obtains the permission to open the box.

[0040] In this embodiment, the receipt information of the recipient is the feedback information that the recipient of the target instant lottery delivery order confirms the receipt of the lottery, marking the completion of the delivery task. For example, the information record generated when the recipient clicks the confirm receipt button in the system.

[0041] The beneficial effects of the above technologies are as follows: The delivery path and area analysis module generates multiple delivery paths based on the delivery destination location, determines the coverage area, and combines historical accident records to obtain the delivery accident heat map within each analysis duration, providing a comprehensive historical risk reference for path planning. The path optimization analysis module superimposes and analyzes the real-time traffic flow, the latest road condition assessment parameters, and the accident heat map to obtain the optimization coefficients of each path at the target delivery time, and screens out the initial optimized delivery paths, enabling the path selection to comprehensively consider the real-time situation and potential risks, and improving the delivery efficiency and safety. The transporter dual-selection module assigns an optimized transporter set for the order according to the waybill information of the transporters within the neighborhood of the initial optimized path, and determines the final transporter based on their reply results, realizing the reasonable allocation of transportation resources. The delivery intelligent supervision module unlocks and empowers the communication device terminal of the transporter in real time by comparing the real-time positioning data of the final transporter and the intelligent lottery transportation box with the delivery destination location until the receipt information is received, effectively ensuring the safety and controllability of the delivery process and ensuring the accurate and safe delivery of instant lottery tickets. The overall solution can break through the limitations of the traditional mode by integrating functions such as real-time data, intelligent analysis, and remote monitoring. It can use Internet of Things devices to collect multi-dimensional data such as traffic and location in real time, providing comprehensive and accurate information support for delivery scheduling, which is of great significance for improving the delivery efficiency and safety of instant lottery tickets, enhancing the user experience, and promoting the digital transformation of the lottery industry.

[0042] Embodiment 2 Based on Embodiment 1, the delivery path and area analysis module includes: The delivery path determination sub-module is used to query the electronic map to determine multiple delivery paths between the delivery starting point location and the delivery destination location of the target instant lottery delivery order; The delivery area division sub-module is used to determine the smallest square geographical area covering all delivery paths as the target delivery path coverage area; An accident heat map generation sub-module is used to analyze the accident heat map of the area covered by the target delivery route within each analysis duration period based on historical delivery accident records.

[0043] In this embodiment, the electronic map is a digital map containing geographical information such as roads and is used to query delivery routes, such as Gaode Map.

[0044] In this embodiment, the smallest square geographical area covering all delivery routes refers to the smallest square range that can completely contain all delivery routes, which is convenient for accurately analyzing the accident heat map.

[0045] In this embodiment, the accident heat map of the area covered by the target delivery route within each analysis duration period is analyzed based on historical delivery accident records, that is, the accident frequencies are counted according to different periods (such as weekly and monthly), and the heat map is used to display the accident risk distribution in the area.

[0046] The beneficial effects of the above technologies are as follows: The delivery route determination sub-module quickly and accurately determines multiple delivery routes between the delivery starting point and the ending point by querying the electronic map, making full use of the comprehensiveness and real-time nature of the electronic map data, providing rich choices for subsequent route optimization. The delivery area division sub-module determines the smallest square geographical area covering all delivery routes as the target delivery route coverage area. This way of delimitation is simple and efficient, and can accurately circle the possible delivery scope, clarifying the spatial boundary for subsequent analysis of the accident heat map, and helping to centrally analyze the risk situation in this area. The accident heat map generation sub-module generates the accident heat map of the area covered by the target delivery route within different analysis duration periods based on historical delivery accident records, intuitively presenting the frequency of accidents and the distribution hotspots, helping the dispatching system to grasp the potential risk points in this area in advance, making the route planning and risk prevention and control more targeted, thereby improving the delivery efficiency and safety, and ensuring the smooth completion of the instant lottery delivery task.

[0047] Embodiment 3 Based on Embodiment 1, the path optimization analysis module includes: A relative risk coefficient analysis sub-module is used to analyze the local relative risk coefficient of each delivery route within each analysis duration period based on the accident heat map of the area covered by the target delivery route within each analysis duration period; An optimization coefficient calculation sub-module is used to calculate the optimization coefficient of each delivery route at the target delivery time of the target instant lottery delivery order based on the real-time traffic flow and the latest road condition evaluation parameters of each delivery route and the local relative risk coefficient within each analysis duration period; An optimized path screening sub-module is used to screen out the delivery route with the maximum optimization coefficient among all delivery routes as the initial optimized delivery route.

[0048] In this embodiment, based on the delivery accident heat map of the target delivery path coverage area within each analysis duration period, the local relative risk coefficient of each delivery path within each analysis duration period is analyzed. For example, a possible implementation method is to first divide the target delivery path coverage area into multiple sub-regions corresponding to the analysis duration period, and count the number of accidents occurring in each sub-region within the corresponding period. For each delivery path, calculate the sum of the number of accidents occurring in each sub-region it passes through, and divide it by the length of the path to obtain an accident density value. Then divide the accident density value of this path by the average accident density value of all paths, and the resulting value is the local relative risk coefficient of this delivery path within this analysis duration period. If the accident density of a certain path is 1.5 times the average accident density, its local relative risk coefficient is 1.5, indicating that this path is relatively more dangerous.

[0049] In this embodiment, the local relative risk coefficient of each delivery path within each analysis duration period is a quantitative value, used to indicate the accident risk degree of this path compared with other paths within a specific analysis period. It is obtained through the above similar algorithm. The larger its value, the higher the potential risk of an accident occurring on this path within this period, and more careful consideration is required during path planning.

[0050] The beneficial effects of the above technical solutions are as follows: By refining the path optimization analysis module, the scientificity and rationality of delivery path selection are significantly improved. The relative risk coefficient analysis sub-module uses the delivery accident heat map to obtain the local relative risk coefficient of each path within each analysis duration period, which carefully depicts the potential accident risks of different paths at different times and regions, providing an accurate risk assessment basis for subsequent decision-making. The optimization coefficient calculation sub-module calculates the optimization coefficient by integrating the real-time traffic flow, the latest road condition assessment parameters, and the local relative risk coefficient, comprehensively integrating the key factors affecting path selection, fully considering the comprehensive impact of traffic conditions, road conditions, and accident risks on delivery, so that the calculated optimization coefficient can more accurately reflect the actual advantages of the path at the target delivery moment. The optimized path screening sub-module determines the initial optimized delivery path based on the maximum optimization coefficient. Based on the accurate analysis results, it ensures that the selected path can not only ensure smooth traffic and good road conditions, but also minimize the accident risk to the greatest extent, thereby effectively improving the delivery efficiency, ensuring the safe and timely delivery of instant lottery tickets, optimizing the performance of the entire intelligent delivery scheduling system, and providing strong support for efficient and safe delivery services.

[0051] Embodiment 4 Based on Embodiment 3, the optimization coefficient calculation sub-module includes: A traffic flow prediction unit, used to predict the traffic flow of each delivery path at the target delivery moment based on the real-time traffic flow of each delivery path; An optimal coefficient calculation unit, configured to calculate an optimal coefficient for each delivery path at the target delivery time of the target instant lottery delivery order based on the traffic flow and the latest road condition evaluation parameters at the target delivery time of each delivery path and the local relative risk coefficient within each analysis duration period: ; wherein, is the optimal coefficient of the currently calculated single delivery path at the target delivery time of the target instant lottery delivery order, is the weight of the real-time traffic flow, is the real-time traffic flow of the currently calculated single delivery path at the target delivery time, is the weight of the latest road condition evaluation parameter, is the latest road condition evaluation parameter of the currently calculated single delivery path, is the weight of the local relative risk coefficient, is the total number of all analysis duration periods, is the local relative risk coefficient of the currently calculated single delivery path within the th analysis duration period, is the th analysis duration period's duration length.

[0052] In this embodiment, to predict the traffic flow of each delivery path at the target delivery time based on the real-time traffic flow of each delivery path, a time series analysis method can be used. For example, collect the traffic flow data of a certain path at different times in the past period, combine with the real-time traffic flow, and construct an ARIMA model to predict the traffic flow at the target delivery time. Machine learning algorithms can also be used, such as training a regression model using historical traffic flow data, real-time traffic data, and related influencing factors (such as date, time period, etc.) to predict the traffic flow at the target time.

[0053] In this embodiment, the weight of the real-time traffic flow is a value given to the degree of influence of the real-time traffic flow on the final result when calculating the path optimal coefficient. For example, if more attention is paid to the impact of traffic smoothness on path selection, its weight can be set to a relatively high value of 0.3, indicating that the real-time traffic flow accounts for a relatively large proportion in determining the path preference degree.

[0054] In this embodiment, the weight of the latest road condition evaluation parameter is a value that measures the importance of the latest road condition evaluation parameter for path selection when calculating the path optimal coefficient. If the road condition (such as road construction, pothole situation) has a significant impact on delivery, its weight can be set to 0.3 to reflect the role of the road condition in the overall path evaluation.

[0055] In this embodiment, the weight of the local relative risk coefficient is a value used to reflect the importance of the local relative risk coefficient in the path selection decision when calculating the path preference coefficient. If great importance is attached to the delivery safety, its weight can be set to 0.4 to highlight the impact of the potential accident risk of the path on path preference.

[0056] The beneficial effects of the above technical solutions are as follows: The traffic flow prediction unit predicts the traffic flow of each delivery path at the target delivery time based on the real-time traffic flow. This measure fully takes into account the dynamic characteristics of the traffic conditions. Since the traffic flow is changing all the time, relying only on the real-time traffic flow may lead to the disconnection between the path selection and the actual situation. By predicting the traffic flow at the target delivery time, it is possible to respond to traffic changes in advance, provide traffic information that conforms to the future actual situation for subsequent calculations, and ensure that the path selection is more forward-looking and reasonable. The preference coefficient calculation unit calculates the preference coefficient by comprehensively considering the traffic flow at the target delivery time, the latest road condition evaluation parameters, and the local relative risk coefficients within different analysis durations using a scientific calculation formula. Weights are set for each key factor, enabling the system to flexibly adjust the influence degree of each factor on the preference coefficient according to the focus requirements of the actual business scenario. For example, if more attention is paid to the delivery safety, the weight of the local relative risk coefficient can be increased. The local relative risk coefficients within different analysis durations and their duration lengths are incorporated into the formula, comprehensively considering the differences and influence durations of the potential risks of the paths at different times, so that the calculated preference coefficient can accurately reflect the comprehensive advantages of each path at the target delivery time. This helps the system to more scientifically and accurately screen out the optimal delivery path, significantly improve the efficiency and safety of instant lottery delivery, and further optimize the overall operation efficiency of the intelligent delivery scheduling system.

[0057] Embodiment 5 On the basis of Embodiment 1, the transporter double-selection module includes: The cost and busyness evaluation sub-module is used to evaluate the double-end order receiving cost and order delivery busyness of each transporter in the neighborhood of the initial preferred delivery path at the target delivery time of the target instant lottery delivery order based on the current order assignment information of all transporters in the neighborhood of the initial preferred delivery path. The order delivery preference analysis sub-module is used to calculate the order delivery preference of each transporter based on the double-end order receiving cost and order delivery busyness of each transporter in the neighborhood of the initial preferred delivery path at the target delivery time of the target instant lottery delivery order. The preferred transporter primary selection sub-module is used to generate a transporter preference sequence based on the order delivery preferences of all transporters in the neighborhood of the initial preferred delivery path, and allocate a preferred transporter set for the target instant lottery delivery order based on the transporter preference sequence. The preferred transporter final selection sub-module is used to send the target instant lottery delivery order to the set of preferred transporters, and allocate the final transporter for the target instant lottery delivery order based on the waybill reply results of the set of preferred transporters.

[0058] In this embodiment, the two-end order receiving cost and order dispatching busyness degree of each transporter at the target delivery moment of the target instant lottery delivery order within the initial preferred delivery path neighborhood are considered. The two-end order receiving cost considers the order receiving costs from the order dispatching end and the transporter end, such as the order dispatching path cost, transportation cost, and relative income loss of the transporter, etc.; the order dispatching busyness degree estimates the business saturation degree of the transporter at the target moment based on the current waybill situation, estimated completion time, etc., and evaluates its ability to receive new orders.

[0059] In this embodiment, the order dispatching preference degree of the transporter is an index calculated by a specific formula in combination with the two-end order receiving cost, order dispatching busyness degree, and the current weight of the transporter, which measures the suitability of the transporter to receive the target order. A higher value indicates a more suitable candidate to receive the order.

[0060] In this embodiment, a transporter preference sequence is generated based on the order dispatching preference degrees of all transporters within the initial preferred delivery path neighborhood, that is, the transporters within the neighborhood are sorted according to the order dispatching preference degree to form a sequence reflecting the priority order of receiving orders, providing a basis for order allocation.

[0061] In this embodiment, a set of preferred transporters is allocated for the target instant lottery delivery order based on the transporter preference sequence. The front part of the personnel is selected from the transporter preference sequence to form a set, and these personnel are potential suitable candidates to receive the target order.

[0062] In this embodiment, the final transporter for the target instant lottery delivery order is allocated based on the waybill reply results of the set of preferred transporters. The order is sent to the set of preferred transporters, and according to their responses of whether to receive the order or not, the final transporter actually performing the delivery task is determined from the set.

[0063] The beneficial effects of the above technical solutions are as follows: The cost and busyness evaluation sub-module evaluates the dual-end order receiving cost and order dispatching busyness at the target delivery time based on the current order assignment information of the transportation personnel, accurately grasps the current business status of the transportation personnel, and provides a realistic basis for subsequent order dispatching. The dual-end order receiving cost reflects the potential cost for the transportation personnel to undertake new orders, and the order dispatching busyness reflects the degree of their business saturation. The combination of the two can comprehensively measure the ability and willingness of the transportation personnel to undertake new tasks. The order dispatching preference analysis sub-module calculates the order dispatching preference based on the dual-end order receiving cost and order dispatching busyness, and comprehensively evaluates the transportation personnel through quantitative indicators. This calculation method provides an objective and scientific reference standard for order dispatching, enabling the system to screen out more suitable personnel to undertake the target order from multiple transportation personnel and improving the rationality of order dispatching. The preliminary selection sub-module of preferred transportation personnel generates a preferred sequence of transportation personnel according to the order dispatching preference, and allocates a set of preferred transportation personnel accordingly, ensuring that the transportation personnel entering the candidate set have high potential in undertaking orders, narrowing the scope for finding a suitable transportation personnel for the order, and improving the order dispatching efficiency. The final selection sub-module of preferred transportation personnel sends the order to the set of preferred transportation personnel, and determines the final transportation personnel based on the order reply result, fully respecting the right of the transportation personnel to make independent choices, and realizing the two-way selection between the transportation personnel and the order. This method not only ensures that the transportation personnel can decide whether to receive the order according to their own situation, but also enables the order to be finally assigned to the transportation personnel who are willing and capable of completing the task, improving the success rate of order execution, optimizing the immediate lottery delivery scheduling process, and ensuring the smooth progress of the delivery task.

[0064] Embodiment 6 Based on Embodiment 5, the cost and busyness evaluation sub-module includes: The transportation personnel weight analysis unit is used to determine the order receiving cost weight of each transportation personnel at the transportation personnel end and the unit transportation cost under the preset order cost division unit based on the current weight of each transportation personnel within the neighborhood of the initial preferred delivery path. The dual-end order receiving cost evaluation unit is used to calculate the dual-end order receiving cost of each transportation personnel within the neighborhood of the initial preferred delivery path at the target delivery time of the target immediate lottery delivery order based on the order receiving cost weight of each transportation personnel at the transportation personnel end: ; In the formula, is the order receiving cost weight of the currently calculated single transportation personnel at the transportation personnel end, is the path cost weight at the order dispatching end, is the length of the initial preferred delivery path, is the transportation cost weight at the order dispatching end, is the unit transportation cost of the currently calculated single transportation personnel under the preset order cost division unit, is the statistical value of the target instant lottery delivery order under the preset order cost division unit. is the path cost weight of the current calculated single transporter at the transporter side. is the relative order-receiving income loss weight of the current calculated single transporter at the transporter side. is the historical average order-receiving income of the current calculated single transporter at the target delivery moment. is the expected order-receiving income of the current calculated single transporter when receiving the target instant lottery delivery order. The order assignment busyness prediction unit is used to predict the order assignment busyness of each transporter at the target delivery moment of the target instant lottery delivery order within the neighborhood of the initial preferred delivery path.

[0065] In this embodiment, the current weight of the transporter is a value assigned after comprehensively considering various factors of the transporter, which is used to reflect the comprehensive importance or priority of the transporter in the system and may be determined based on factors such as the transporter's experience, reputation, and transportation capacity.

[0066] In this embodiment, the order-receiving cost weight at the transporter side reflects the degree of influence of the transporter's own factors on the order acceptance cost, and through it, the proportion of the cost borne by the transporter himself when receiving an order in the total cost can be measured.

[0067] In this embodiment, the preset order cost division unit is a cost measurement unit preset for facilitating the calculation and analysis of transportation costs. For example, using per kilometer, per order, etc. as the division unit makes the cost calculation more standardized and comparable.

[0068] In this embodiment, the unit transportation cost under the preset order cost division unit refers to the transportation cost value corresponding to each unit calculated based on the preset cost division unit. For example, the transportation cost per kilometer is X yuan.

[0069] In this embodiment, based on the current weight of each transporter within the neighborhood of the initial preferred delivery path, the order-receiving cost weight at the transporter side and the unit transportation cost under the preset order cost division unit of each transporter are determined. That is, according to the current weight of the transporter, combined with relevant rules or algorithms (such as the preset current weight - order-receiving cost weight at the transporter side, unit transportation cost under the preset order cost division unit corresponding list), the influence weight of the transporter's order acceptance cost and the unit transportation cost under a specific cost division unit are determined to evaluate the cost situation of the transporter's order acceptance.

[0070] In this embodiment, the path cost weight at the order dispatching end is used to measure the importance of the costs related to the order dispatching path in the total cost at the order dispatching end. The path cost includes the path length, and this weight reflects the proportion of the impact of the path factor on the total cost at the order dispatching end.

[0071] In this embodiment, the transportation cost weight at the order dispatching end reflects the proportion of the transportation costs generated during the transportation process in the total cost at the order dispatching end when the corresponding transporter is selected at the order dispatching end. The transportation costs cover the labor cost expenses that the order dispatching end needs to pay.

[0072] In this embodiment, the target is the statistical value of the instant lottery delivery order under the preset order cost division unit. It is the value obtained by statistically calculating the relevant costs of the target order according to the preset order cost division unit, so as to conduct unified comparison and analysis with other cost data. For example, when the division unit is per kilometer, the order transportation distance is its corresponding statistical value.

[0073] In this embodiment, the path cost weight at the transporter end measures the proportion of the costs generated by the transporter due to the delivery path in its own order receiving cost, considering the impact of the path on the transporter's cost.

[0074] In this embodiment, the relative order receiving income loss weight at the transporter end reflects the proportion of the possible loss degree relative to the normal income of the transporter when undertaking the target order in the order receiving cost, and is used to evaluate the impact of order receiving on the transporter's income.

[0075] In this embodiment, the historical average order receiving income of the transporter at the target delivery moment refers to the income obtained by the transporter on average each time when receiving orders during a period of time before the target delivery moment, reflecting the income level of its past order receiving, and serving as a reference basis for evaluating the current order receiving cost and benefits.

[0076] In this embodiment, the expected order receiving income of the transporter when receiving the target instant lottery delivery order is the income that the transporter expects to obtain after undertaking the target instant lottery delivery order, and is used to compare with the historical average order receiving income to evaluate the income situation of this order receiving.

[0077] The beneficial effects of the above technical solutions are as follows: The transportation personnel weight analysis unit determines key cost parameters based on the current weight of the transportation personnel, making the dual-end order receiving cost assessment more targeted and reasonable. The dual-end order receiving cost assessment unit uses a comprehensive formula to calculate the cost by integrating multiple factors at the order dispatching end and the transportation personnel end, accurately reflecting the cost of the transportation personnel to undertake orders, providing an accurate reference for reasonable order dispatching, and improving the resource utilization efficiency. The order dispatching busyness prediction unit anticipates in advance the busyness degree of the transportation personnel at the target moment, avoids over-concentration of orders, ensures the balanced distribution of delivery tasks, and prevents affecting the delivery efficiency and quality. By accurately evaluating the dual-end order receiving cost and the order dispatching busyness, the system can more scientifically select suitable transportation personnel for instant lottery delivery orders, optimize the dispatching process, and ensure the efficient and orderly development of the delivery work.

[0078] Embodiment 7 Based on Embodiment 6, the order dispatching busyness prediction unit includes: The final position determination subunit is used to obtain the final order dispatching terminal position of each transportation personnel within the neighborhood of the initial preferred delivery path before the target delivery moment of the target instant lottery delivery order; The order dispatching busyness prediction subunit is used to input the final order dispatching terminal position of each transportation personnel before the target delivery moment of the target instant lottery delivery order, the current weight of the transportation personnel, and the target delivery moment of the target instant lottery delivery order into a preset order dispatching busyness prediction model to obtain the order dispatching busyness degree of each transportation personnel within the neighborhood of the initial preferred delivery path at the target delivery moment of the target instant lottery delivery order.

[0079] In this embodiment, the final order dispatching terminal position of the transportation personnel before the target delivery moment of the target instant lottery delivery order refers to the location where the transportation personnel are when they complete the previous order dispatching task before about to execute the target instant lottery delivery task. This position information helps to infer the current state of the transportation personnel, as well as the distance and time for them to reach the target delivery location, etc., and thus assist in judging their busyness degree in undertaking new orders. For example, if the transportation personnel were located far away from the target delivery point at the end of the previous order, it may mean that he needs to spend more time coming over and has a higher busyness degree.

[0080] In this embodiment, the preset order dispatching busyness prediction model is a pre-constructed mathematical model or algorithm. It takes some relevant information of the transportation personnel (such as the final order dispatching terminal position, the current weight, the target delivery moment of the target instant lottery delivery order, etc.) as inputs, and through the analysis and calculation of these data, outputs the predicted value of the order dispatching busyness degree of the transportation personnel at the target delivery moment. This model may be trained based on historical data and use methods such as machine learning and statistical analysis to more accurately estimate the business busyness degree of the transportation personnel at a specific moment and provide a basis for reasonable order distribution.

[0081] The beneficial effects of the above technical solutions are as follows: The final position determination subunit obtains the final order dispatch terminal position of the transportation personnel before the target delivery moment, which provides a key basis for evaluating the work itinerary and status of the transportation personnel. Knowing the final order dispatch terminal position can directly understand the location where the transportation personnel completed the previous order task, which helps to speculate on their subsequent work arrangements and the relationship between their spatial position and the new order. The order dispatch busyness prediction subunit inputs the final order dispatch terminal position, the current weight of the transportation personnel, and the target delivery moment into a preset model to predict the order dispatch busyness by integrating multi-dimensional information. The current weight of the transportation personnel reflects comprehensive factors such as their business ability and reputation. Combining with the target delivery moment, the dynamic changes in the business volume in the time dimension can be accurately considered. The preset order dispatch busyness prediction model integrates these key information, making the prediction result more in line with the actual situation. Through such settings, the busyness degree of the transportation personnel at a specific moment can be evaluated more accurately, which helps the delivery scheduling system to fully consider the actual working status of the transportation personnel when allocating instant lottery delivery orders, avoid overloading the transportation personnel due to unreasonable order dispatch, thereby optimizing the allocation of delivery resources, improving the delivery efficiency, ensuring the timely and accurate delivery of instant lottery, and enhancing the quality and reliability of the entire delivery service.

[0082] Example 8 Based on Example 5, the order dispatch preference analysis sub-module includes: The transportation personnel weight acquisition unit is used to acquire the current weight of each transportation personnel within the neighborhood of the initial preferred delivery path. The order dispatch preference calculation unit is used to calculate the order dispatch preference of each transportation personnel based on the two-end order acceptance cost and order dispatch busyness of each transportation personnel at the target delivery moment of the target instant lottery delivery order within the neighborhood of the initial preferred delivery path and the current weight of each transportation personnel within the neighborhood of the initial preferred delivery path: ; In the formula, is the order dispatch preference of the currently calculated single transportation personnel, is the weight of the two-end order acceptance cost, is the weight of the order dispatch busyness, is the order dispatch busyness of the currently calculated single transportation personnel at the target delivery moment of the target instant lottery delivery order, is the weight of the current weight of the currently calculated single transportation personnel, is the order dispatch preference of the currently calculated single transportation personnel.

[0083] In this embodiment, the weight of the double - end order receiving cost is the importance value assigned to the factor of double - end order receiving cost when calculating the order - assignment preference of the transportation staff. This weight determines the proportion of the double - end order receiving cost in the comprehensive evaluation of whether the transportation staff is suitable to undertake an order. For example, if the weight of the double - end order receiving cost is set to 0.4, it means that when calculating the order - assignment preference, the influence of the double - end order receiving cost on the final result accounts for 40%. The higher the weight, the greater the influence of the double - end order receiving cost on the order - assignment preference.

[0084] In this embodiment, the weight of the order - assignment busyness is the value that measures the importance of the factor of order - assignment busyness when calculating the order - assignment preference of the transportation staff. It reflects the degree of influence of the business saturation of the transportation staff at the target delivery time on the suitability of undertaking an order. For example, if the weight of the order - assignment busyness is set to 0.3, it indicates that the influence of the order - assignment busyness in determining the order - assignment preference accounts for 30%. A higher weight means that the order - assignment busyness is more crucial in evaluating the order - receiving ability of the transportation staff.

[0085] In this embodiment, the weight of the current weight of a single transportation staff being calculated is the weight value set for the current weight of a single transportation staff during the calculation of the order - assignment preference. The current weight of the transportation staff comprehensively reflects various characteristics of the transportation staff, and this weight further adjusts the role of the current weight in calculating the order - assignment preference. For example, if this weight is set to 0.3, it means that the influence of the current weight in determining the order - assignment preference accounts for 30%. By adjusting this weight, according to the actual business needs, the influence of the current weight of the transportation staff on the order - assignment preference can be flexibly controlled.

[0086] The beneficial effects of the above technical solutions are as follows: The transportation staff weight acquisition unit obtains the current weight of the transportation staff, providing important basic data for comprehensively evaluating the suitability of the transportation staff to undertake an order. This weight comprehensively reflects various traits of the transportation staff, such as work experience, credit rating, etc., making the subsequent analysis more targeted. The order - assignment preference calculation unit accurately calculates the order - assignment preference by taking into account the double - end order receiving cost, order - assignment busyness, and the current weight of the transportation staff through a scientific calculation formula. The weights of the double - end order receiving cost weight, order - assignment busyness weight, and current weight can be flexibly adjusted according to actual business needs, highlighting the importance of different factors in the order - assignment decision. For example, during the business peak period, the weight of the order - assignment busyness can be appropriately increased to preferentially select relatively idle transportation staff to ensure efficient order allocation. In this way, the system can more accurately measure the advantage degree of each transportation staff in undertaking the target instant lottery delivery order, providing a more scientific decision - making basis for the delivery scheduling system. Reasonable calculation of the order - assignment preference helps to optimize order allocation, improve the utilization efficiency of transportation resources, ensure the smooth completion of the instant lottery delivery task, and enhance the quality and efficiency of the entire delivery service.

[0087] Example 9 Based on Example 1, a smart supervision module is dispatched, including: A dual-position monitoring sub-module, which is used to calculate the error value between the real-time positioning data of the communication device terminal of the final transporter and the real-time positioning data of the smart lottery transport box in real time when any of the real-time positioning data reaches the delivery end position of the target instant lottery delivery order; An unlocking authorization sub-module, which is used to grant the communication device terminal of the final transporter the permission to unlock the corresponding smart lottery transport box until the error value between the real-time positioning data of the communication device terminal of the final transporter and the real-time positioning data of the smart lottery transport box is less than the preset error value. At the same time, an unpacking warning message is sent to the recipient of the target instant lottery delivery order, and the duration after unpacking is counted; An order monitoring sub-module, which is used to mark the completion of the target instant lottery delivery order at the total monitoring end when the receipt information of the recipient of the target instant lottery delivery order is received within the duration after unpacking is less than the threshold of the duration after unpacking, otherwise a three-party alarm message is sent.

[0088] In this embodiment, any real-time positioning data reaching the delivery end position of the target instant lottery delivery order means that the real-time positioning data of either the communication device terminal of the final transporter or the smart lottery transport box shows that it has reached the delivery location specified in the order, indicating that the delivery entity is approaching or has reached the destination.

[0089] In this embodiment, calculating the error value between the real-time positioning data of the communication device terminal of the final transporter and the real-time positioning data of the smart lottery transport box means obtaining the location information of both through positioning technology and calculating the position deviation between them using a specific algorithm to judge the spatial distance difference between the transporter and the lottery transport box.

[0090] In this embodiment, the preset error value is a pre-set standard distance value, which is used to compare with the above calculated error value to determine whether the positions of the transporter and the smart lottery transport box are close enough to decide whether to grant the unlocking permission.

[0091] In this embodiment, the smart lottery transport box is a box with intelligent functions such as positioning for transporting instant lottery tickets, which can feedback location information in real time to ensure the safety and monitorability of the lottery transportation process.

[0092] In this embodiment, granting the communication device terminal of the final transporter the permission to unlock the corresponding smart lottery transport box means giving the transporter the permission to open the transport box through the communication device when the position error between the transporter and the smart lottery transport box meets the conditions, so as to deliver the lottery tickets.

[0093] In this embodiment, the unpacking warning message is a notification message sent to the recipient while granting the transportation personnel the permission to unlock the intelligent lottery transportation box, informing the other party that the lottery box is about to be opened.

[0094] In this embodiment, the duration after unpacking refers to the length of time elapsed after the intelligent lottery transportation box is opened, and is used to monitor the time progress of the lottery delivery process.

[0095] In this embodiment, the duration after unpacking threshold is a preset time standard used to determine whether the lottery delivery process is completed within the specified time.

[0096] In this embodiment, otherwise, a tripartite alarm message is sent. If the recipient's signature information has not been received when the duration after unpacking exceeds the threshold, the system will send an alarm to the transportation personnel, the recipient, and the general management monitoring terminal, prompting that there is an abnormality in the delivery.

[0097] The beneficial effects of the above technical solutions are as follows: The dual-position monitoring sub-module real-time tracks the positioning data of the communication device terminal of the final transportation personnel and the intelligent lottery transportation box, calculates the error value between the two when one party arrives at the delivery destination, accurately grasps the transportation status, and provides a reliable basis for subsequent operations. The unlocking authorization sub-module takes the error value being less than the preset value as the condition for granting the communication device terminal the permission to unlock the intelligent lottery transportation box, and at the same time sends an unpacking warning message to the recipient and counts the duration after unpacking, ensuring the safety of lottery delivery and standardizing the unpacking process. The order monitoring sub-module determines the order status based on the comparison between the duration after unpacking and the preset threshold and whether the signature information is received, processes the abnormality in a timely manner, ensures the smooth end of the delivery task, improves the order management efficiency. This series of operations constructs a complete supervision system, enhances the reliability of the instant lottery intelligent delivery scheduling system, improves the transparency and security of the delivery process, reduces potential risks, improves the service quality, ensures the lottery is delivered on time, accurately and safely, enhances the user experience, and maintains a good image of the system.

[0098] Embodiment 10 The present invention provides an instant lottery intelligent delivery scheduling method based on the Internet of Things, which is applied to any of the above instant lottery intelligent delivery scheduling systems based on the Internet of Things, and includes: S1: Generate multiple delivery paths based on the delivery destination location of the target instant lottery delivery order, determine the target delivery path coverage area covering all the delivery paths, and analyze the delivery accident heat map of the target delivery path coverage area in each analysis duration period based on the historical delivery accident records; S2: Superimpose and analyze the real-time traffic flow and the latest road condition assessment parameters of each delivery route, as well as the delivery accident heat map in the coverage area of the target delivery route within each analysis duration period, analyze the optimization coefficient of each delivery route at the target delivery moment of the target instant lottery delivery order, and screen out the delivery route with the maximum optimization coefficient as the initial preferred delivery route; S3: Based on the current waybill allocation information of all transportation personnel within the neighborhood of the initial preferred delivery route, allocate a preferred transportation personnel set for the target instant lottery delivery order, and allocate the final transportation personnel for the target instant lottery delivery order based on the waybill reply results of the preferred transportation personnel set; S4: Based on the real-time positioning data of the communication device terminal of the final transportation personnel, the real-time positioning data of the intelligent lottery transportation box, and the delivery end position of the target instant lottery delivery order, perform real-time unlocking and empowerment on the communication device terminal of the final transportation personnel until the receipt information of the recipient of the target instant lottery delivery order is received.

[0099] The beneficial effects of the above technologies are as follows: S1 generates multiple delivery routes based on the delivery end position, determines the coverage area, and combines the historical accident records to obtain the delivery accident heat map within each analysis duration period, providing a comprehensive historical risk reference for route planning. S2 superimposes and analyzes the real-time traffic flow, the latest road condition assessment parameters, and the accident heat map, obtains the optimization coefficient of each route at the target delivery moment, and screens out the initial preferred delivery route, enabling the route selection to comprehensively consider the real-time situation and potential risks, and improving the delivery efficiency and safety. S3 allocates a preferred transportation personnel set for the order based on the waybill information of the transportation personnel within the neighborhood of the initial preferred route, and determines the final transportation personnel based on their reply results, realizing the reasonable allocation of transportation resources. S4 performs real-time unlocking and empowerment on the communication device terminal of the transportation personnel by comparing the real-time positioning data of the final transportation personnel and the intelligent lottery transportation box with the delivery end position until the receipt information is received, effectively ensuring the safety and controllability of the delivery process and ensuring the accurate and safe delivery of instant lottery tickets. The overall solution can break through the limitations of the traditional mode by integrating functions such as real-time data, intelligent analysis, and remote monitoring. It can use Internet of Things devices to collect multi-dimensional data such as traffic and location in real time, providing comprehensive and accurate information support for delivery scheduling, which is of great significance for improving the efficiency and safety of instant lottery delivery, enhancing the user experience, and promoting the digital transformation of the lottery industry.

[0100] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the present invention and its equivalent technologies, the present invention also intends to include these changes and modifications.

Claims

1. The intelligent delivery and dispatching system of instant lottery tickets based on the Internet of Things is characterized by: include: The delivery path and area analysis module is used to generate multiple delivery paths based on the delivery destination location of the target instant lottery delivery order, determine the target delivery path coverage area covering all delivery paths, and analyze the delivery accident heat map of the target delivery path coverage area in each analysis duration period based on the historical delivery accident records; The route optimization analysis module is used to perform superposition analysis on the real-time traffic flow and the latest road condition evaluation parameters of each delivery route and the delivery accident heat map of the target delivery route coverage area within each analysis duration period, analyze the optimization coefficient of each delivery route at the target delivery time of the target instant lottery delivery order, and select the delivery route with the maximum optimization coefficient as the initial optimization delivery route; The transport personnel double selection module is used to allocate a set of preferred transport personnel for the target instant lottery delivery order based on the current waybill allocation information of all transport personnel in the neighborhood of the initial preferred delivery path, and allocate a final transport personnel for the target instant lottery delivery order based on the waybill reply result of the preferred transport personnel set; The delivery intelligent supervision module is used to unlock and empower the communication device terminal of the final transportation personnel in real time based on the real-time positioning data of the communication device terminal of the final transportation personnel, the real-time positioning data of the intelligent lottery transport box, and the delivery destination position of the target instant lottery delivery order until the receipt information of the recipient of the target instant lottery delivery order is received.

2. The instant lottery intelligent delivery and dispatching system based on the Internet of Things according to claim 1 is characterized in that: Delivery route and area analysis module, including: A delivery path determination submodule is used to query the electronic map to determine multiple delivery paths between the delivery starting point and the delivery end point of the target instant lottery delivery order; The delivery area division submodule is used to determine the smallest square geographical area covering all delivery routes as the target delivery route coverage area; The accident heat map generation submodule is used to analyze the delivery accident heat map of the target delivery path coverage area within each analysis duration period based on historical delivery accident records.

3. The instant lottery intelligent delivery and dispatching system based on the Internet of Things according to claim 1 is characterized in that: Path optimization analysis module, including: The relative risk factor analysis submodule is used to analyze the local relative risk factor of each delivery path in each analysis duration period based on the delivery accident heat map of the target delivery path coverage area in each analysis duration period; A preference coefficient calculation submodule, for calculating the preference coefficient of each delivery route at a target delivery time of a target instant lottery delivery order based on the real-time traffic flow and the latest road condition evaluation parameters of each delivery route and the local relative risk coefficient in each analysis duration period; The preferred path screening submodule is used to screen out the delivery path with the maximum preferred coefficient from all delivery paths as the initial preferred delivery path.

4. The instant lottery intelligent delivery and dispatching system based on the Internet of Things according to claim 3 is characterized in that: The optimal coefficient calculation submodule includes: A traffic flow prediction unit, used to predict the traffic flow of each delivery route at a target delivery time based on the real-time traffic flow of each delivery route; The optimization coefficient calculation unit is used to calculate the optimization coefficient of each delivery path at the target delivery time of the target instant lottery delivery order based on the traffic flow and the latest road condition evaluation parameters of each delivery path at the target delivery time and the local relative risk coefficient in each analysis duration period: ； In the formula, is the optimization coefficient of the currently calculated single delivery path at the target delivery time of the target instant lottery delivery order, is the weight of real-time traffic flow, is the real-time traffic flow of the currently calculated single delivery route at the target delivery time, is the weight of the latest road condition evaluation parameter, The latest road condition evaluation parameter for the currently calculated single delivery route. is the weight of the local relative risk coefficient, is the total number of categories for all analysis duration periods, The single delivery path currently calculated is The local relative risk factor within the duration of the analysis is For the The duration of the analysis period.

5. The instant lottery intelligent delivery and dispatching system based on the Internet of Things according to claim 1 is characterized in that: Transport personnel double selection module, including: The cost and busyness evaluation submodule is used to evaluate the double-end order receiving cost and dispatch busyness of each transporter in the neighborhood of the initial preferred delivery path at the target delivery time of the target instant lottery delivery order based on the current waybill allocation information of all transporters in the neighborhood of the initial preferred delivery path; The dispatch priority analysis submodule is used to calculate the dispatch priority of each transport personnel based on the double-end order receiving cost and dispatch busyness of each transport personnel at the target delivery time of the target instant lottery delivery order in the neighborhood of the initial preferred delivery path; The preferred transport personnel preliminary selection submodule is used to generate a preferred sequence of transport personnel based on the dispatching priority of all transport personnel in the neighborhood of the initial preferred delivery path, and to allocate a set of preferred transport personnel to the target lottery delivery order based on the preferred sequence of transport personnel; The preferred transport personnel final selection submodule is used to send a target instant lottery delivery order for the preferred transport personnel set, and allocate a final transport personnel for the target instant lottery delivery order based on the waybill reply result of the preferred transport personnel set.

6. The instant lottery intelligent delivery and dispatching system based on the Internet of Things according to claim 5 is characterized in that: Cost and busyness evaluation submodules include: A transporter weight analysis unit, for determining a transporter terminal order cost weight of each transporter and a unit transport cost under a preset order cost division unit based on a current weight of each transporter in the neighborhood of the initial preferred delivery path; The double-end order-pickup cost evaluation unit is used to calculate the double-end order-pickup cost of each transporter at the target delivery time of the target instant lottery delivery order in the neighborhood of the initial preferred delivery path based on the transporter-end order-pickup cost weight of each transporter: ； In the formula, The transporter-end order cost weight of the currently calculated single transporter. is the path cost weight of the dispatch end, is the length of the initial preferred delivery path, is the transportation cost weight of the dispatching end, The unit transportation cost of a single transporter currently calculated under the preset order cost division unit, The statistical value of the target instant lottery delivery order under the preset order cost division unit, is the path cost weight of the transporter side of the currently calculated single transporter, is the relative order income loss weight of a single transporter currently calculated. is the historical average order income of a single transporter at the target delivery time. The expected order revenue of a single transporter currently calculated when delivering orders to the order target lottery; The dispatch busyness prediction unit is used to predict the dispatch busyness of each transporter in the neighborhood of the initial preferred delivery path at the target delivery time of the target instant lottery delivery order.

7. The instant lottery intelligent delivery and dispatching system based on the Internet of Things according to claim 6 is characterized in that: The dispatch busyness prediction unit includes: The final position determination subunit is used to obtain the final dispatch terminal position of each transporter in the neighborhood of the initial preferred delivery path before the target delivery time of the target instant lottery delivery order; The dispatch busyness prediction subunit is used to input the final dispatch terminal position of each transport personnel before the target delivery time of the target instant lottery delivery order, the current weight of the transport personnel, and the target delivery time of the target instant lottery delivery order into a preset dispatch busyness prediction model to obtain the dispatch busyness of each transport personnel at the target delivery time of the target instant lottery delivery order in the neighborhood of the initial preferred delivery path.

8. The instant lottery intelligent delivery and dispatching system based on the Internet of Things according to claim 5 is characterized in that: The dispatch optimization analysis submodule includes: A transport personnel weight acquisition unit, used to acquire the current weight of each transport personnel in the neighborhood of the initial preferred delivery path; The dispatch priority calculation unit is used to calculate the dispatch priority of each transport personnel based on the double-end order receiving cost and dispatch busyness of each transport personnel in the neighborhood of the initial preferred delivery path at the target delivery time of the target instant lottery delivery order and the current weight of each transport personnel in the neighborhood of the initial preferred delivery path: ； In the formula, is the currently calculated dispatch preference of a single transporter, is the weight of the cost of double-ended order, is the weight of dispatch busyness, is the currently calculated dispatch busyness of a single transporter at the target delivery time of the target instant lottery delivery order, is the weight of the current weight of the single transport personnel currently calculated, The dispatch preference of a single transporter currently calculated.

9. The instant lottery intelligent delivery and dispatching system based on the Internet of Things according to claim 1 is characterized in that: Delivery intelligent supervision module, including: The dual positioning monitoring submodule is used to calculate the error value between the real-time positioning data of the communication device terminal of the final transporter and the real-time positioning data of the smart lottery transport box in real time when any of the real-time positioning data reaches the delivery destination of the target instant lottery delivery order; The unlocking authorization submodule is used to grant the communication device terminal of the final transporter the authority to unlock the corresponding smart lottery transport box until the error value between the real-time positioning data of the communication device terminal of the final transporter and the real-time positioning data of the smart lottery transport box is less than the preset error value. At the same time, an unpacking warning message is sent to the recipient of the target instant lottery delivery order, and the duration after unpacking is counted; The order monitoring submodule is used to mark the target instant lottery delivery order as completed at the general monitoring end when the signing information of the signing party of the target instant lottery delivery order is received when the duration after unpacking is less than the duration threshold after unpacking, otherwise a three-party alarm message is issued.

10. A method for intelligent delivery and dispatching of instant lottery tickets based on the Internet of Things, characterized in that: The instant lottery intelligent delivery and dispatching system based on the Internet of Things applied to any one of claims 1 to 9 comprises: S1: Generate multiple delivery routes based on the delivery destination location of the target instant lottery delivery order, determine the target delivery route coverage area covering all delivery routes, and analyze the delivery accident heat map of the target delivery route coverage area in each analysis duration period based on the historical delivery accident records; S2: Superimpose and analyze the real-time traffic flow and the latest road condition evaluation parameters of each delivery route and the delivery accident heat map of the target delivery route coverage area within each analysis duration period, analyze the optimization coefficient of each delivery route at the target delivery time of the target instant lottery delivery order, and select the delivery route with the maximum optimization coefficient as the initial optimization delivery route; S3: Based on the current waybill allocation information of all transport personnel in the neighborhood of the initial preferred delivery path, a preferred transport personnel set is allocated to the target instant lottery delivery order, and based on the waybill reply result of the preferred transport personnel set, a final transport personnel is allocated to the target instant lottery delivery order; S4: Based on the real-time positioning data of the communication device terminal of the final transportation personnel, the real-time positioning data of the smart lottery transport box, and the delivery destination location of the target instant lottery delivery order, the communication device terminal of the final transportation personnel is unlocked and authorized in real time until the receipt information of the recipient of the target instant lottery delivery order is received.

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