Intelligent dispensing and dispatching system and method for instant lottery tickets based on internet of things

Abstract

The application relates to the technical field of dispatching, and particularly discloses an instant lottery intelligent dispatching system and method based on the Internet of Things, which realizes intelligent dispatching of the whole process of instant lottery delivery through multi-module cooperation: a path generation module generates multiple candidate paths based on order end points, and constructs a time period heat map in combination with historical accident data; a dynamic optimization algorithm superimposes real-time traffic flow, road condition parameters and a risk heat map, calculates a path optimization coefficient through multi-factor weighted calculation, and screens an optimal path; a personnel matching mechanism dynamically allocates a candidate set in the neighborhood of the optimal path according to the current order saturation of the transportation personnel, and determines the final delivery personnel in combination with order receiving response speed; and an intelligent supervision module realizes real-time monitoring of the positions of the personnel and the intelligent transportation box through GPS positioning, dynamically assigns power to unlock the permission, and until the block chain storage and evidence receiving of the receiving party are completed. The system realizes closed-loop management of path planning, personnel matching and whole-process monitoring.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of dispatching, in particular to an intelligent dispatching system and method for instant lottery tickets based on the Internet of Things. BACKGROUND

[0002] At present, in the booming development of the lottery industry, instant lottery tickets have become an important part of the lottery market due to their rapid opening and strong interest. With the increasing demand for instant lottery tickets from consumers, how to efficiently and accurately deliver instant lottery tickets has become a key link in lottery operation and management. As a cutting-edge technology with great development potential, the Internet of Things is gradually penetrating into various industries and bringing opportunities for innovation and change to traditional industries. The application of Internet of Things technology in the dispatching system of instant lottery tickets is expected to realize intelligent and fine management of the dispatching process, improve overall operational efficiency and service quality, and has broad development prospects.

[0003] In the traditional dispatching process of instant lottery tickets, the dispatching path is often planned based on experience or simple map navigation, without fully considering real-time traffic conditions, historical accident data, and dynamic changes in road conditions. This leads to a non-optimal dispatching path, which not only increases the dispatching time and cost, but also may cause dispatching delays due to poor road conditions. In terms of transportation personnel allocation, fixed regional division or first-come-first-served principle is usually adopted, lacking comprehensive consideration of real-time transportation personnel's order situation, making it difficult to achieve reasonable task allocation. This may cause some transportation personnel to have too much work, while others are idle, reducing the overall dispatching efficiency. Moreover, during the dispatching process, it mainly relies on periodic reporting and limited logistics information tracking, lacking effective supervision mechanism. It is difficult to accurately obtain the location information of transportation personnel and lottery transportation boxes in real time, making it difficult to discover and handle abnormal situations in the dispatching process, and unable to accurately control the authority of transportation personnel, posing certain safety risks such as lottery loss or misappropriation.

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

[0005] The application provides an instant lottery ticket intelligent delivery scheduling system and method based on the Internet of Things, which comprises: a delivery path and area analysis module that generates multiple delivery paths according to a delivery endpoint location, determines a coverage area, and obtains a delivery accident heat map of the target delivery path coverage area in each analysis duration based on historical delivery accident records, thereby providing a comprehensive historical risk reference for path planning; a path optimization analysis module that superimposes and analyzes real-time traffic flow, the latest road condition evaluation parameters, and the delivery accident heat map, obtains an optimal coefficient of each path at the target delivery time of the target instant lottery ticket delivery order, and screens out an initial optimal delivery path, so that the real-time conditions and potential risks are comprehensively considered in path selection, and the delivery efficiency and safety are improved; a transportation personnel double selection module that allocates an optimal transportation personnel set to the target instant lottery ticket delivery order based on the current order allocation information of all transportation personnel in the neighborhood of the initial optimal delivery path, and allocates a final transportation personnel to the target instant lottery ticket delivery order based on the order reply results of the optimal transportation personnel set; and a delivery intelligent supervision module that compares the real-time positioning data of the final transportation personnel and the intelligent lottery transportation box with the delivery endpoint location, and real-time unlocks the terminal of the transportation personnel communication equipment, until the signing information is received, thereby effectively ensuring the safety and controllability of the delivery process and ensuring the accurate and safe delivery of instant lottery tickets.

[0006] The application provides an instant lottery ticket intelligent delivery scheduling system based on the Internet of Things, which comprises:

[0007] A delivery path and area analysis module that generates multiple delivery paths based on the delivery endpoint location of a target instant lottery ticket delivery order, determines a target delivery path coverage area covering all the delivery paths, and analyzes a delivery accident heat map of the target delivery path coverage area in each analysis duration based on historical delivery accident records;

[0008] A path optimization analysis module that superimposes and analyzes 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, analyzes an optimal coefficient of each delivery path at the target delivery time of the target instant lottery ticket delivery order, and screens out a delivery path with the maximum optimal coefficient as an initial optimal delivery path;

[0009] A transportation personnel double selection module that allocates an optimal transportation personnel set to the target instant lottery ticket delivery order based on the current order allocation information of all transportation personnel in the neighborhood of the initial optimal delivery path, and allocates a final transportation personnel to the target instant lottery ticket delivery order based on the order reply results of the optimal transportation personnel set;

[0010] The intelligent delivery supervision module is configured to perform real-time unlocking empowerment for the communication device terminal of the final delivery personnel based on real-time positioning data of the communication device terminal of the final delivery personnel, real-time positioning data of the intelligent lottery ticket delivery box, and a delivery end location of the target instant lottery ticket delivery order.

[0011] Optionally, the delivery path and area analysis module comprises:

[0012] The delivery path determination sub-module is configured to query an electronic map to determine a plurality of delivery paths between a delivery start location and a delivery end location of the target instant lottery ticket delivery order.

[0013] The delivery area division sub-module is configured to determine a minimum square geographic area covering all the delivery paths as a target delivery path coverage area.

[0014] The accident heat map generation sub-module is configured to analyze a delivery accident heat map of the target delivery path coverage area in each analysis duration based on historical delivery accident records.

[0015] Optionally, the path preference analysis module comprises:

[0016] The relative risk coefficient analysis sub-module is configured to analyze a local relative risk coefficient of each delivery path in each analysis duration based on the delivery accident heat map of the target delivery path coverage area in each analysis duration.

[0017] The preferred coefficient calculation sub-module is configured to calculate a preferred coefficient of each delivery path at a target delivery time of the target instant lottery ticket delivery order based on real-time traffic flow and latest road condition evaluation parameters of each delivery path and the local relative risk coefficient in each analysis duration.

[0018] The preferred path screening sub-module is configured to screen a delivery path with a maximum preferred coefficient from all the delivery paths as an initial preferred delivery path.

[0019] Optionally, the preferred coefficient calculation sub-module comprises:

[0020] The traffic flow prediction unit is configured to predict traffic flow of each delivery path at the target delivery time based on real-time traffic flow of each delivery path.

[0021] The preferred coefficient calculation unit is configured to calculate a preferred coefficient of each delivery path at the target delivery time of the target instant lottery ticket delivery order based on traffic flow of each delivery path at the target delivery time and latest road condition evaluation parameters and the local relative risk coefficient in each analysis duration.

[0022] ;

[0023] wherein, is a preferred coefficient of the single delivery path currently calculated at the target delivery time of the target instant lottery delivery order, is a weight of real-time traffic flow, is the real-time traffic flow of the single delivery path currently calculated at the target delivery time, is a weight of the latest road condition evaluation parameter, is the latest road condition evaluation parameter of the single delivery path currently calculated, is a weight of the local relative risk coefficient, is the total number of categories of all analysis duration periods, is the local relative risk coefficient of the single delivery path currently calculated in the analysis duration period, is the duration length of the analysis duration period.

[0024] Optionally, the transportation personnel double selection module comprises:

[0025] The cost and busy degree evaluation submodule is configured to evaluate the double-terminal order cost and order busy degree of each transportation personnel in the initial preferred delivery path neighborhood at the target delivery time of the target instant lottery delivery order based on the current order allocation information of all transportation personnel in the initial preferred delivery path neighborhood.

[0026] The order preference degree analysis submodule is configured to calculate the order preference degree of each transportation personnel based on the double-terminal order cost and order busy degree of each transportation personnel in the initial preferred delivery path neighborhood at the target delivery time of the target instant lottery delivery order.

[0027] The preferred transportation personnel preliminary selection submodule is configured to generate a preferred transportation personnel sequence based on the order preference degrees of all transportation personnel in the initial preferred delivery path neighborhood, and assign a preferred transportation personnel set to the target instant lottery delivery order based on the preferred transportation personnel sequence.

[0028] The preferred transportation personnel final selection submodule is configured to send the target instant lottery delivery order to the preferred transportation personnel set, and assign a final transportation personnel to the target instant lottery delivery order based on the order reply result of the preferred transportation personnel set.

[0029] Optionally, the cost and busy degree evaluation submodule comprises:

[0030] The transportation personnel weight analysis unit is configured to determine the transportation personnel-terminal order cost weight and unit transportation cost of each transportation personnel in a preset order cost division unit based on the current weight of each transportation personnel in the initial preferred delivery path neighborhood.

[0031] a double-terminal order cost evaluation unit configured to calculate a double-terminal order cost of each transport personnel in the initial preferred delivery path neighborhood at a target delivery time of the target instant lottery delivery order based on a transport personnel terminal order cost weight of each transport personnel:

[0032] ;

[0033] wherein, is a transport personnel terminal order cost weight of the single transport personnel currently calculated, is a path cost weight of the order terminal, is a length of the initial preferred delivery path, is a transport cost weight of the order terminal, is a unit transport cost of the single transport personnel currently calculated under a preset order cost division unit, is a statistical value of the target instant lottery delivery order under the preset order cost division unit, is a transport personnel terminal path cost weight of the single transport personnel currently calculated, is a relative order income loss weight of the transport personnel terminal of the single transport personnel currently calculated, is a historical average order income of the single transport personnel at the target delivery time, is an expected order income of the single transport personnel currently calculated when the target instant lottery delivery order is received;

[0034] an order terminal busy degree prediction unit configured to predict an order terminal busy degree of each transport personnel in the initial preferred delivery path neighborhood at a target delivery time of the target instant lottery delivery order.

[0035] Optionally, the order terminal busy degree prediction unit comprises:

[0036] a final position determination subunit configured to obtain a final order terminal position of each transport personnel in the initial preferred delivery path neighborhood before a target delivery time of the target instant lottery delivery order;

[0037] an order terminal busy degree prediction subunit configured to input the final order terminal position of each transport personnel before the target delivery time of the target instant lottery delivery order, a current weight of the transport personnel, and the target delivery time of the target instant lottery delivery order into a preset order terminal busy degree prediction model to obtain the order terminal busy degree of each transport personnel in the initial preferred delivery path neighborhood at the target delivery time of the target instant lottery delivery order.

[0038] Optionally, the order preferred degree analysis sub-module comprises:

[0039] A transportation personnel weight acquisition unit is configured to acquire a current weight of each transportation personnel in the initial preferred delivery path neighborhood;

[0040] A order assignment preference calculation unit is configured to calculate an order assignment preference of each transportation personnel based on a double-terminal order cost of each transportation personnel in the initial preferred delivery path neighborhood at a target delivery time of the target instant lottery delivery order, an order assignment busy degree, and the current weight of each transportation personnel in the initial preferred delivery path neighborhood:

[0041] ;

[0042] In the formula, is the order assignment preference of the single transportation personnel currently calculated, is the weight of the double-terminal order cost, is the weight of the order assignment busy degree, is the order assignment busy degree of the single transportation personnel currently calculated at the target delivery time of the target instant lottery delivery order, is the weight of the current weight of the single transportation personnel currently calculated, is the order assignment preference of the single transportation personnel currently calculated.

[0043] Optionally, the delivery intelligent supervision module comprises:

[0044] A double-positioning monitoring sub-module is configured to calculate an error value between the real-time positioning data of the communication device terminal of the final transportation personnel and the real-time positioning data of the intelligent lottery transportation box in real time when any of the real-time positioning data reaches a delivery end position of the target instant lottery delivery order;

[0045] An unlocking empowerment sub-module is configured to empower the communication device terminal of the final transportation personnel with the permission of unlocking the corresponding intelligent lottery transportation box until the error value between the real-time positioning data of the communication device terminal of the final transportation personnel and the real-time positioning data of the intelligent lottery transportation box is less than a preset error value, while sending an opening box warning information to a signee of the target instant lottery delivery order and counting a post-opening duration.

[0046] An order monitoring sub-module is configured to mark the target instant lottery delivery order as completed on a total monitoring end when receiving a signee information of the signee of the target instant lottery delivery order when the post-opening duration is less than a post-opening duration threshold, or otherwise, sending a three-party alarm information.

[0047] The application provides an instant lottery intelligent delivery scheduling method based on the Internet of Things, which is applied to any one of the instant lottery intelligent delivery scheduling systems based on the Internet of Things, and comprises the following steps:

[0048] S1: based on the delivery end location of the target instant lottery delivery order, generate multiple delivery paths, 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 based on the historical delivery accident record;

[0049] S2: superimpose and analyze 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 optimal 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 optimal coefficient as the initial optimal delivery path;

[0050] S3: based on the current order allocation information of all transport personnel in the neighborhood of the initial optimal delivery path, allocate the optimal transport personnel set for the target instant lottery delivery order, and based on the order reply result of the optimal transport personnel set, allocate the final transport personnel for the target instant lottery delivery order;

[0051] S4: based on the real-time positioning data of the communication equipment terminal of the final transport personnel and the real-time positioning data of the intelligent lottery transport box, and the delivery end location of the target instant lottery delivery order, the communication equipment terminal of the final transport personnel is unlocked and empowered in real time until the signing information of the signing party of the target instant lottery delivery order is received.

[0052] The beneficial effects generated by the present application relative to the prior art are that the delivery path and area analysis module generates multiple delivery paths according to the delivery end position, determines the coverage area and combines the historical accident records to obtain the delivery accident heat map in each analysis duration, thereby 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, obtains the optimization coefficient of each path at the target delivery time, and screens out the initial optimal delivery path, so that the real-time condition and potential risk are comprehensively considered in path selection, thereby improving the delivery efficiency and safety. The transportation personnel double selection module allocates an optimal transportation personnel set to the order according to the shipping order information of the transportation personnel in the neighborhood of the initial optimal path, and determines the final transportation personnel according to the reply result, thereby realizing the reasonable allocation of transportation resources. The delivery intelligent supervision module realizes the real-time unlocking of the transportation personnel communication equipment terminal by comparing the real-time positioning data of the final transportation personnel and the intelligent lottery transportation box with the delivery end position, and the safety and controllability of the delivery process are effectively guaranteed, and the accurate and safe delivery of the instant lottery is ensured. The overall scheme can break through the limitations of the traditional mode by integrating real-time data, intelligent analysis and remote monitoring functions. It can use Internet of Things devices to collect multi-dimensional data such as traffic and location in real time, provide comprehensive and accurate information support for delivery scheduling, and has important significance for improving the efficiency and safety of instant lottery delivery, enhancing user experience and promoting the digital transformation of the lottery industry.

[0053] Other features and advantages of the present application will be set forth in the following description, and in part will become apparent to those skilled in the art from the description, or can be learned by practice of the present application. The objects and other advantages of the present application can be realized and obtained by the structure particularly pointed out in the application.

[0054] The technical solutions of the present application will be further described in detail below with the help of the drawings and examples. BRIEF DESCRIPTION OF DRAWINGS

[0055] The accompanying drawings are included to provide a further understanding of the present application, and constitute a part of the specification, together with the embodiments of the present application, to explain the present application, and do not constitute a limitation on the present application. In the drawings:

[0056] Figure 1 The present application is based on the Internet of Things-based instant lottery intelligent delivery scheduling system in the embodiment. DETAILED DESCRIPTION

[0057] The preferred embodiments of the present application will be described below in conjunction with the drawings, and it should be understood that the preferred embodiments described herein are only used to illustrate and explain the present application, and do not limit the present application.

[0058] Example 1

[0059] Reference Figure 1 The application provides an Internet of Things-based instant lottery intelligent delivery scheduling system, comprising:

[0060] A delivery path and area analysis module is 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.

[0061] A path optimization analysis module is configured to perform superimposed analysis on the real-time traffic flow and the latest road condition evaluation parameter of each delivery path and the delivery accident heat map of the target delivery path coverage area in each analysis duration, analyze an optimal coefficient of each delivery path at the target delivery time of the target instant lottery delivery order, and screen a delivery path with the maximum optimal coefficient as an initial optimal delivery path.

[0062] A transportation personnel double selection module is configured to assign an optimal transportation personnel set to the target instant lottery delivery order based on the current order allocation information of all transportation personnel in the neighborhood of the initial optimal delivery path, and assign a final transportation personnel to the target instant lottery delivery order based on the order reply result of the optimal transportation personnel set.

[0063] A delivery intelligent supervision module is configured to perform real-time unlocking empowerment on the communication device terminal of the final transportation personnel based on the real-time positioning data of the communication device terminal of the final transportation personnel and the real-time positioning data of the intelligent lottery transportation box and the delivery end position of the target instant lottery delivery order, until the signing information of the signing party of the target instant lottery delivery order is received.

[0064] In this embodiment, the target instant lottery delivery order refers to a task instruction for delivering instant lottery from a delivery starting point to a specific delivery end point, contains various types of information related to delivery, and is the core task around which the entire intelligent delivery scheduling system operates. For example, the instant lottery delivery request order received by a lottery supplier from a certain lottery sales outlet.

[0065] In this embodiment, the delivery end position is the final delivery location of the lottery specified in the target instant lottery delivery order, which is used to determine the end position of the delivery path, such as the address of a specific lottery retail store.

[0066] In this embodiment, the delivery path is a route that can be selected between the delivery starting position and the delivery end position, which is obtained by querying an electronic map, etc. The system will generate multiple paths for subsequent screening and optimization. For example, the routes formed by different road combinations between a lottery warehouse and a sales outlet.

[0067] In this embodiment, the target delivery path coverage area is the smallest square geographic area that can cover all the generated delivery paths, and is used to determine the scope for analyzing the delivery accident heat map. For example, all the delivery paths are within the square area that extends outward from a certain area.

[0068] In this embodiment, the historical delivery accident record is a record of past accidents that occurred during the delivery of instant lottery tickets, including detailed information such as the time and location of the accident, which is used to analyze the occurrence of accidents in different areas and assist in planning safer delivery routes. For example, a record of a side-rolling accident of a lottery delivery vehicle due to bad weather on a certain road.

[0069] 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 period, to fully understand the distribution of accidents at different time scales.

[0070] In this embodiment, the delivery accident heat map of the target delivery path coverage area in each analysis duration period is a graphical representation of the frequency and hot spot distribution of delivery accidents in the target delivery path coverage area in different analysis duration periods. The darker the color, the higher the frequency of accidents, and the distribution of accident risk in different time periods is intuitively presented. For example, in a heat map with a weekly analysis period, a certain area is displayed as dark red due to frequent accidents.

[0071] In this embodiment, the real-time traffic flow is the traffic volume on each delivery path at the current time, which reflects the degree of road congestion in real time and is one of the key factors affecting path optimization. For example, the number of vehicles passing through a certain road per minute.

[0072] In this embodiment, the latest road condition evaluation parameter is a quantitative evaluation value of the current road condition of each delivery path, which is derived by considering factors such as road construction and road damage that affect traffic, and is used to measure the traffic quality of the path. For example, if the road is congested due to maintenance, this situation will be reflected in the road condition evaluation parameter.

[0073] In this embodiment, the target delivery time is the time point at which the target instant lottery delivery order is planned to be delivered, and the path optimization analysis and other operations are carried out around the road conditions, risks, and other factors at this time point. For example, the lottery is planned to be delivered to the designated sales point at 10:00 am, and 10:00 am is the target delivery time.

[0074] In this embodiment, the preferred coefficient of each delivery path at the target delivery time of the target instant lottery delivery order is a value calculated by comprehensively considering real-time traffic flow, the latest road condition evaluation parameters, and local relative risk coefficients in different analysis periods, and is used to measure the comprehensive advantage of each delivery path at the target delivery time. The higher the value, the higher the priority. For example, the preferred coefficient of a certain path is 0.75 after formula calculation.

[0075] In this embodiment, the current order allocation information of the transportation personnel refers to the details of the delivery tasks currently undertaken by each transportation personnel, including the number of allocated orders, the estimated completion time, and the like, and 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 orders to be delivered, and is expected to complete them in 1.5 hours.

[0076] In this embodiment, the preferred transportation personnel set is a group of transportation personnel with high potential for undertaking the target instant lottery delivery order, selected based on the double-end order cost and order allocation busy degree of the transportation personnel in the initial preferred delivery path neighborhood, and is used as a candidate group for determining the final transportation personnel.

[0077] In this embodiment, the order reply result is the response information given by the transportation personnel in the preferred transportation personnel set to the target instant lottery delivery order, and the system determines the final transportation personnel according to the result. For example, a certain transportation personnel replies to agree to undertake the order.

[0078] In this embodiment, the final transportation personnel is the actual person responsible for delivering the target instant lottery delivery order, determined from the preferred transportation personnel set according to the order reply result after a series of screening processes.

[0079] In this embodiment, the communication device terminal of the final transportation personnel is a communication tool used by the final transportation personnel, such as a mobile phone or a special positioning device, which has a real-time positioning function, and is used to real-time feedback the position information of the transportation personnel, so as to facilitate the system to perform monitoring and unlocking empowerment operations.

[0080] In this embodiment, the real-time positioning data is the geographic position information of the communication device terminal of the final transportation personnel and the intelligent lottery transportation box at each time point, obtained by positioning technology such as GPS, and is used to real-time track their positions. For example, the latitude and longitude coordinates of the position of the transportation personnel at a certain time.

[0081] In this embodiment, the unlocking authorization is that when the real-time positioning data of the communication device terminal of the final delivery personnel and the smart lottery transport box meet a certain condition (both error values are less than a preset error value), the communication device terminal of the final delivery personnel is authorized to open the corresponding smart lottery transport box, ensuring that the lottery is delivered at the correct location. For example, when the delivery personnel arrives near the delivery endpoint and the error between the location of the lottery transport box and the delivery endpoint is within the allowed range, the mobile phone of the delivery personnel obtains the opening box authorization.

[0082] In this embodiment, the signing information of the signing party is the feedback information of the receiving party of the target instant lottery delivery order confirming receipt of the lottery, indicating the completion of the delivery task. For example, the information record generated by the signing party clicking the confirmation button in the system.

[0083] The beneficial effects of the above technology are as follows: The delivery path and area analysis module generates multiple delivery paths based on the delivery endpoint location, determines the coverage area, and combines historical accident records to obtain the delivery accident heat map in each analysis 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 accident heat map to obtain the optimal coefficient of each path at the target delivery time, and filters out the initial optimal delivery path, so that the path selection comprehensively considers the real-time conditions and potential risks, improving the delivery efficiency and safety. The delivery personnel double selection module assigns an optimal delivery personnel set to the order based on the shipping order information of the delivery personnel in the neighborhood of the initial optimal path, and determines the final delivery personnel based on the reply result, realizing the rational allocation of transportation resources. The delivery intelligent supervision module compares the real-time positioning data of the final delivery personnel and the smart lottery transport box with the delivery endpoint location, and unlocks the communication device terminal of the delivery personnel in real time until the signing information is received, effectively ensuring the safety and controllability of the delivery process, and ensuring that the instant lottery is accurately and safely delivered. The overall scheme can break through the limitations of the traditional mode by integrating real-time data, intelligent analysis, and remote monitoring functions. It can use Internet of Things devices to collect multi-dimensional data such as traffic and location in real time to provide comprehensive and accurate information support for delivery scheduling, which is of great significance for improving the efficiency and safety of instant lottery delivery, enhancing user experience, and promoting the digital transformation of the lottery industry.

[0084] Embodiment 2

[0085] Based on embodiment 1, the delivery path and area analysis module comprises:

[0086] The delivery path determination submodule is configured to query an electronic map to determine multiple delivery paths between the delivery starting point location and the delivery endpoint location of the target instant lottery delivery order;

[0087] The delivery area division submodule is configured to determine a minimum square geographic area covering all the delivery paths as the target delivery path coverage area.

[0088] An accident heat map generation submodule is configured to analyze a delivery accident heat map of the target delivery path coverage area in each analysis duration based on historical delivery accident records.

[0089] In this embodiment, the electronic map is a digital map containing geographic information such as roads, which is used to query the delivery path, like Gaode Map.

[0090] In this embodiment, the minimum square geographic area covering all the delivery paths refers to the minimum square range that can completely contain all the delivery paths, which facilitates accurate analysis of the accident heat map.

[0091] In this embodiment, the accident heat map of the target delivery path coverage area in each analysis duration is analyzed based on historical delivery accident records, that is, the accident frequency is counted according to different periods (such as weeks and months), and the regional accident risk distribution is displayed by a heat map.

[0092] The above-mentioned technology has the following beneficial effects: The delivery path determination submodule quickly and accurately determines multiple delivery paths between the delivery starting point and the delivery ending point by querying the electronic map, fully utilizes the comprehensiveness and real-time nature of the electronic map data, and provides rich choices for subsequent path optimization. The delivery area division submodule determines the minimum square geographic area covering all the delivery paths as the target delivery path coverage area, which is a simple and efficient way to accurately define the possible delivery range and helps to analyze the risk in this area. The accident heat map generation submodule generates the delivery accident heat map of the target delivery path coverage area in different analysis durations based on historical delivery accident records, which intuitively presents the frequency and distribution of accidents, helps the dispatching system to grasp the potential risk points in this area in advance, makes the path planning and risk prevention more targeted, and thus improves the delivery efficiency and safety, and ensures the smooth completion of the instant lottery delivery task.

[0093] Embodiment 3

[0094] Based on the embodiment 1, the path optimization analysis module comprises:

[0095] The relative risk coefficient analysis submodule is configured to analyze the local relative risk coefficient of each delivery path in each analysis duration based on the delivery accident heat map of the target delivery path coverage area in each analysis duration.

[0096] The preferred coefficient calculation submodule is configured to calculate the preferred 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.

[0097] The preferred path screening sub-module is configured to screen a delivery path with the maximum preferred coefficient from all delivery paths as an initial preferred delivery path.

[0098] In this embodiment, based on the delivery accident heat map of the target delivery path coverage area in each analysis duration, the local relative risk coefficient of each delivery path in each analysis duration is analyzed. For example, one possible implementation is to first divide the target delivery path coverage area into a plurality of sub-areas corresponding to the analysis duration, and count the number of accidents in each sub-area in the corresponding period. For each delivery path, the sum of the number of accidents in each sub-area passed by the path is calculated and divided by the length of the path to obtain an accident density value. Then, the accident density value of the path is divided by the average accident density value of all paths, and the result is the local relative risk coefficient of the delivery path in the analysis duration. If the accident density of a path is 1.5 times the average accident density, the local relative risk coefficient of the path is 1.5, which means that the path is relatively more dangerous.

[0099] In this embodiment, the local relative risk coefficient of each delivery path in each analysis duration is a quantitative value, which is used to indicate the accident risk degree of the path compared with other paths in a specific analysis period. Through the above similar algorithm, the larger the value is, the higher the potential risk of the path in the period is, and more careful consideration is needed in path planning.

[0100] The above technical scheme has the beneficial effects that: through the refinement of the path preferred analysis module, the scientificity and rationality of the 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 in each analysis duration, which carefully depicts the potential accident risk of different paths in different periods and regions, and provides accurate risk assessment basis for subsequent decision-making. The preferred coefficient calculation sub-module calculates the preferred coefficient by comprehensively considering the real-time traffic flow, the latest road condition evaluation parameters and the local relative risk coefficient, fully considers the comprehensive influence of traffic conditions, road conditions and accident risks on delivery, and makes the calculated preferred coefficient more accurately reflect the actual advantages of the path at the target delivery time. The preferred path screening sub-module determines the initial preferred delivery path based on the maximum preferred coefficient, ensures that the selected path can guarantee smooth traffic and good road conditions, and can also maximize the reduction of accident risk, thereby effectively improving the delivery efficiency, ensuring the safe and timely delivery of the instant lottery, and optimizing the performance of the entire intelligent delivery scheduling system, providing strong support for efficient and safe delivery services.

[0101] Embodiment 4

[0102] On the basis of Embodiment 3, the preferred coefficient calculation submodule comprises:

[0103] a traffic flow prediction unit configured 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;

[0104] a preferred coefficient calculation unit configured to calculate the preferred 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 parameter, and the local relative risk coefficient in each analysis duration period:

[0105] ;

[0106] wherein, is the preferred coefficient of the single delivery path currently calculated 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 single delivery path currently calculated at the target delivery time, is the weight of the latest road condition evaluation parameter, is the latest road condition evaluation parameter of the single delivery path currently calculated, is the weight of the local relative risk coefficient, is the total number of categories of all analysis duration periods, is the local relative risk coefficient of the single delivery path currently calculated in the analysis duration period, is the duration length of the analysis duration period.

[0107] In this embodiment, the traffic flow of each delivery path at the target delivery time is predicted based on the real-time traffic flow of each delivery path, which can utilize the time series analysis method. For example, the traffic flow data at different times in the past period of a path is collected, combined with the real-time traffic flow, and an ARIMA model is constructed to predict the traffic flow at the target delivery time. A regression model can also be trained using historical traffic flow data, real-time flow data, and related influencing factors (such as date, time period, etc.) to predict the flow at the target time.

[0108] In this embodiment, the weight of the real-time traffic flow is a numerical value that reflects the degree of influence of the real-time traffic flow on the final result when calculating the path preferred coefficient. For example, if more emphasis is placed on the influence of traffic smoothness on path selection, the weight can be set to a higher value of 0.3, indicating that the real-time traffic flow accounts for a larger proportion in determining the preferred degree of the path.

[0109] In this embodiment, the weight of the latest road condition evaluation parameter is a value for measuring the importance of the latest road condition evaluation parameter to path selection when calculating the path preference coefficient. If the road condition (such as road construction, pothole condition) has a significant impact on delivery, the weight can be set to 0.3 to reflect the role of the road condition in the overall path evaluation.

[0110] In this embodiment, the weight of the local relative risk coefficient is a value for reflecting the importance of the local relative risk coefficient in path selection decision when calculating the path preference coefficient. If the safety of delivery is extremely important, the weight can be set to 0.4 to highlight the influence of the potential accident risk of the path on the path preference.

[0111] The beneficial effects of the above technical solutions are: the traffic flow prediction unit predicts the traffic flow of each delivery path at the target delivery time based on real-time traffic flow, which fully considers the dynamic characteristics of the traffic condition. Since the traffic flow changes all the time, relying only on real-time traffic flow may cause the path selection to deviate from the actual situation. By predicting the flow at the target delivery time, the system can respond to traffic changes in advance and provide traffic information that fits the actual situation in the future for subsequent calculations, ensuring that the path selection is more forward-looking and reasonable. The preferred coefficient calculation unit calculates the preferred coefficient by means of a scientific calculation formula, which comprehensively considers the traffic flow at the target delivery time, the latest road condition evaluation parameter, and the local relative risk coefficient in different analysis periods. By setting weights for each key factor, the system can flexibly adjust the influence of each factor on the preferred coefficient according to the focus needs of the actual business scenario. For example, if more attention is paid to delivery safety, the weight of the local relative risk coefficient can be increased. The formula incorporates the local relative risk coefficient and its duration in different analysis periods, fully considering the differences and influence duration of the potential risks of the paths in different periods, so that the calculated preferred coefficient can accurately reflect the comprehensive advantages of each path at the target delivery time. This helps the system to more scientifically and accurately select the optimal delivery path, significantly improves the efficiency and safety of the instant lottery delivery, and further optimizes the overall operation efficiency of the intelligent delivery scheduling system.

[0112] Embodiment 5

[0113] Based on embodiment 1, the transportation personnel double selection module includes:

[0114] The cost and busy degree evaluation submodule is configured to evaluate the double-end order receiving cost and order receiving busy degree of each transportation personnel in the initial preferred delivery path neighborhood at the target delivery time of the target instant lottery delivery order based on the current order allocation information of all transportation personnel in the initial preferred delivery path neighborhood.

[0115] The order assignment preference degree analysis submodule is configured to calculate the order assignment preference degree of each transportation personnel based on the double-terminal order assignment cost and order assignment busy degree of each transportation personnel in the initial preferred delivery path neighborhood at the target delivery time of the target instant lottery delivery order.

[0116] The preferred transportation personnel preliminary selection submodule is configured to generate a transportation personnel preference sequence based on the order assignment preference degrees of all transportation personnel in the initial preferred delivery path neighborhood, and assign a preferred transportation personnel set to the target instant lottery delivery order based on the transportation personnel preference sequence.

[0117] The preferred transportation personnel final selection submodule is configured to send the target instant lottery delivery order to the preferred transportation personnel set, and assign a final transportation personnel to the target instant lottery delivery order based on the order reply result of the preferred transportation personnel set.

[0118] In this embodiment, the double-terminal order assignment cost and order assignment busy degree of each transportation personnel in the initial preferred delivery path neighborhood at the target delivery time of the target instant lottery delivery order are calculated. The double-terminal order assignment cost considers the order assignment cost from the order assignment end and the transportation personnel end, such as order assignment path cost, transportation cost, and relative income loss of the transportation personnel. The order assignment busy degree evaluates the ability of the transportation personnel to accept new orders according to the current order situation, estimated completion time, and other factors.

[0119] In this embodiment, the order assignment preference degree of the transportation personnel is an index calculated by a specific formula based on the double-terminal order assignment cost, order assignment busy degree, and current weight of the transportation personnel. The order assignment preference degree measures the suitability of the transportation personnel to accept the target order, and a higher value indicates that the transportation personnel is more suitable to accept the order.

[0120] In this embodiment, the transportation personnel preference sequence is generated based on the order assignment preference degrees of all transportation personnel in the initial preferred delivery path neighborhood. The transportation personnel in the neighborhood are sorted according to the order assignment preference degrees to form a sequence that reflects the order of priority for accepting orders, providing a basis for order assignment.

[0121] In this embodiment, the preferred transportation personnel set is assigned to the target instant lottery delivery order based on the transportation personnel preference sequence. The set is composed of the top personnel selected from the transportation personnel preference sequence, and these personnel are potential suitable candidates for accepting the target order.

[0122] In this embodiment, the final transportation personnel is assigned to the target instant lottery delivery order based on the order reply result of the preferred transportation personnel set. The order is sent to the preferred transportation personnel set, and the final transportation personnel who actually performs the delivery task is determined from the set based on their responses to the order.

[0123] The beneficial effects of the above technical solutions are: the cost and busy degree evaluation submodule evaluates the double-end order receiving cost and order dispatching busy degree of the target delivery time based on the current order allocation information of the transportation personnel, accurately grasps the current business state of the transportation personnel, and provides a realistic basis for subsequent order dispatching. The double-end order receiving cost reflects the potential cost of the transportation personnel to accept new orders, and the order dispatching busy degree reflects the business saturation degree, and the combination of the two can comprehensively measure the ability and willingness of the transportation personnel to accept new tasks. The order dispatching optimization degree analysis submodule calculates the order dispatching optimization degree based on the double-end order receiving cost and the order dispatching busy degree, and comprehensively evaluates the transportation personnel through quantitative indicators. This calculation method provides an objective and scientific reference standard for order dispatching, so that the system can select more suitable personnel to accept the target order from multiple transportation personnel, and improve the rationality of order dispatching. The preferred transportation personnel preliminary selection submodule generates a transportation personnel optimization sequence according to the order dispatching optimization degree, and allocates a preferred transportation personnel set accordingly, to ensure that the transportation personnel in the candidate set have high potential in accepting orders, narrow the range of finding suitable transportation personnel for orders, and improve the efficiency of order dispatching. The preferred transportation personnel final selection submodule sends the order to the preferred transportation personnel set, and determines the final transportation personnel according to the order reply result, fully respects the right of transportation personnel to make independent choices, and realizes the two-way selection of transportation personnel and orders. This method not only ensures that the transportation personnel can decide whether to accept the order according to their own situation, but also enables the order to be finally allocated to the transportation personnel who have the willingness and ability to complete the task, improves the success rate of order execution, optimizes the lottery ticket delivery dispatching process, and ensures the smooth development of the delivery task.

[0124] Embodiment 6

[0125] Based on embodiment 5, the cost and busy degree evaluation submodule comprises:

[0126] The transportation personnel weight analysis unit is configured to determine the transportation personnel order receiving cost weight of each transportation personnel and the unit transportation cost under the preset order cost division unit based on the current weight of each transportation personnel in the initial preferred delivery path neighborhood.

[0127] The double-end order receiving cost evaluation unit is configured to calculate the double-end order receiving cost of each transportation personnel in the initial preferred delivery path neighborhood at the target delivery time of the target lottery ticket delivery order based on the transportation personnel order receiving cost weight of each transportation personnel.

[0128] ;

[0129] In the formula, is the transportation personnel order receiving cost weight of the single transportation personnel currently calculated, is the path cost weight of the order dispatching end, is the length of the initial preferred delivery path, is the transportation cost weight of the order dispatching end, a unit transportation cost of the current calculated single transportation personnel under a preset order cost division unit, a statistical value of the target instant lottery delivery order under the preset order cost division unit, a path cost weight of the transportation personnel end of the current calculated single transportation personnel, a relative order acceptance income loss weight of the transportation personnel end of the current calculated single transportation personnel, a historical average order acceptance income of the current calculated single transportation personnel at the target delivery time, an expected order acceptance income of the current calculated single transportation personnel when accepting the target instant lottery delivery order;

[0130] an order assignment busy degree prediction unit configured to predict an order assignment busy degree of each transportation personnel in the initial preferred delivery path neighborhood at the target delivery time of the target instant lottery delivery order.

[0131] In this embodiment, the current weight of the transportation personnel is a value determined after comprehensively considering various factors of the transportation personnel, and is used to reflect the comprehensive importance or priority of the transportation personnel in the system. The current weight can be determined based on factors such as experience, reputation, and transportation capacity of the transportation personnel.

[0132] In this embodiment, the transportation personnel end order acceptance cost weight reflects the influence degree of the transportation personnel's own factors on the order acceptance cost. Through the transportation personnel end order acceptance cost weight, the proportion of the cost borne by the transportation personnel in the total cost when accepting an order can be measured.

[0133] In this embodiment, the preset order cost division unit is a cost measurement unit that is preset for the purpose of calculating and analyzing transportation cost. For example, the cost division unit can be per kilometer or per order, so that the cost calculation is more standardized and comparable.

[0134] In this embodiment, the unit transportation cost under the preset order cost division unit refers to the transportation cost value corresponding to each unit based on the preset cost division unit. For example, the transportation cost per kilometer is X yuan.

[0135] In this embodiment, based on the current weight of each transportation personnel in the initial preferred delivery path neighborhood, the transportation personnel end order acceptance cost weight and the unit transportation cost under the preset order cost division unit of each transportation personnel are determined. That is, according to the current weight of the transportation personnel, the influence weight of the transportation personnel end order acceptance cost and the unit transportation cost under a specific cost division unit are determined by combining relevant rules or algorithms (for example, a preset current weight-transportation personnel end order acceptance cost weight, unit transportation cost under a preset order cost division unit corresponding list), so as to evaluate the cost of the transportation personnel to accept an order.

[0136] In this embodiment, the path cost weight of the order assigning end is used to measure the importance of the path-related cost of the order assigning path in the total cost of the order assigning end. The path cost includes the path length, and the weight reflects the proportion of the influence of the path factor on the total cost of the order assigning end.

[0137] In this embodiment, the transportation cost weight of the order assigning end reflects the proportion of the transportation cost generated in the transportation process when the order assigning end selects the corresponding transportation personnel to assign the order in the total cost of the order assigning end. The transportation cost covers the labor cost paid by the order assigning end.

[0138] In this embodiment, the statistical value of the target instant lottery delivery order under the preset order cost division unit is a value obtained by calculating the related cost of the target order according to the preset order cost division unit, so as to uniformly compare and analyze other cost data. For example, when the order transportation distance is divided by kilometers, the order transportation distance is the corresponding statistical value.

[0139] In this embodiment, the path cost weight of the transportation personnel end measures the proportion of the cost generated by the transportation personnel due to the delivery path in the order accepting cost of the transportation personnel, considering the influence of the path on the transportation personnel cost.

[0140] In this embodiment, the relative order accepting income loss weight of the transportation personnel end reflects the proportion of the loss degree of the transportation personnel when accepting the target order relative to the normal income in the order accepting cost, which is used to evaluate the influence of order accepting on the income of the transportation personnel.

[0141] In this embodiment, the historical average order accepting income of the transportation personnel at the target delivery time is the average income obtained by the transportation personnel each time in a period of time before the target delivery time, which reflects the income level of the past order accepting and serves as a reference basis for evaluating the current order accepting cost and benefit.

[0142] In this embodiment, the expected order accepting income of the transportation personnel when accepting the target instant lottery delivery order is the income that the transportation personnel expects to obtain after accepting the target instant lottery delivery order, which is used to compare with the historical average order accepting income to evaluate the benefit of this order accepting.

[0143] The beneficial effects of the above technical solutions are: the transportation personnel weight analysis unit determines the key cost parameters according to the current weight of the transportation personnel, so that the double-end order acceptance cost assessment is more targeted and reasonable. The double-end order acceptance cost assessment unit uses a comprehensive formula to calculate the cost of multiple factors on the order side and the transportation personnel side, accurately reflects the transportation personnel's order acceptance cost, provides accurate reference for reasonable order allocation, and improves resource utilization efficiency. The order allocation busy degree prediction unit predicts the busy degree of the transportation personnel at the target time in advance, avoids excessive concentration of orders, ensures balanced allocation of delivery tasks, and prevents affecting the delivery efficiency and quality. By accurately assessing the double-end order acceptance cost and the order allocation busy degree, the system can more scientifically select suitable transportation personnel for the instant lottery ticket delivery order, optimize the dispatching process, and ensure that the delivery work is carried out efficiently and orderly.

[0144] Embodiment 7

[0145] Based on embodiment 6, the order allocation busy degree prediction unit comprises:

[0146] The final position determination sub-unit is configured to obtain the final order allocation terminal position of each transportation personnel in the initial preferred delivery path neighborhood before the target instant lottery ticket delivery order target delivery time.

[0147] The order allocation busy degree prediction sub-unit is configured to input the final order allocation terminal position of each transportation personnel in the initial preferred delivery path neighborhood before the target instant lottery ticket delivery order target delivery time, the current weight of the transportation personnel, and the target instant lottery ticket delivery order target delivery time into a preset order allocation busy degree prediction model to obtain the order allocation busy degree of each transportation personnel in the initial preferred delivery path neighborhood at the target instant lottery ticket delivery order target delivery time.

[0148] In this embodiment, the final order allocation terminal position of the transportation personnel before the target instant lottery ticket delivery order target delivery time refers to the location of the transportation personnel when completing the last order allocation task before performing the target instant lottery ticket delivery task. This position information helps to predict the current state of the transportation personnel, the distance and time to the target delivery location, and the like, thereby assisting in judging the busy degree of the transportation personnel in accepting new orders. For example, if the transportation personnel is located far away from the target delivery point when the last order ends, it may mean that he needs to spend more time to get there, and the busy degree is high.

[0149] In this embodiment, the preset order dispatching busyness prediction model is a pre-built mathematical model or algorithm. It takes relevant information about the transport personnel (such as the final dispatch terminal location, current weight, and target delivery time for the instant lottery order) as input, and through analysis and calculation of this data, outputs a predicted order dispatching busyness value for the transport personnel at the target delivery time. This model may be trained based on historical data, employing machine learning, statistical analysis, and other methods to accurately predict the workload of transport personnel at a specific time, providing a basis for the rational allocation of orders.

[0150] The beneficial effects of the above technical solution are as follows: The final location determination subunit obtains the final dispatch terminal location of the transport personnel before the target delivery time. This information provides a crucial basis for assessing the transport personnel's work schedule and status. Knowing the final dispatch terminal location allows for a direct understanding of where the transport personnel finished their previous task, helping to predict their subsequent work arrangements and the relationship between their spatial location and new orders. The dispatch busyness prediction subunit inputs the final dispatch terminal location, the transport personnel's current weight, and the target delivery time into a preset model, comprehensively predicting dispatch busyness based on multi-dimensional information. The transport personnel's current weight reflects their business capabilities, reputation, and other comprehensive factors; combined with the target delivery time, it accurately considers the dynamic changes in business volume over time. The preset dispatch busyness prediction model integrates this key information, making the prediction results more closely reflect the actual situation. This setup allows for a more accurate assessment of the workload of delivery personnel at specific times. It helps the delivery dispatch system to fully consider the actual working conditions of delivery personnel when allocating instant lottery delivery orders, avoiding excessive workload for delivery personnel due to unreasonable order assignments. This optimizes the allocation of delivery resources, improves delivery efficiency, ensures timely and accurate delivery of instant lottery tickets, and enhances the quality and reliability of the entire delivery service.

[0151] Example 8

[0152] Based on Example 5, the order dispatch optimization analysis submodule includes:

[0153] The transport personnel weight acquisition unit is used to acquire the current weight of each transport personnel in the neighborhood of the initial preferred delivery path;

[0154] The dispatch optimization calculation unit is used to calculate the dispatch optimization degree of each transporter based on the two-way order acceptance cost and dispatch busyness of each transporter in the neighborhood of the initial optimized delivery path at the target delivery time of the target instant lottery delivery order, as well as the current weight of each transporter in the neighborhood of the initial optimized delivery path:

[0155] ;

[0156] In the formula, the single transportation personnel currently calculated, the weight of the double-terminal order cost, the weight of the order dispatching busy degree, the order dispatching busy degree of the single transportation personnel currently calculated at the target delivery time of the target instant lottery delivery order, the weight of the current weight of the single transportation personnel currently calculated, the order dispatching preference degree of the single transportation personnel currently calculated.

[0157] In this embodiment, the weight of the double-terminal order cost is a value that reflects the importance of the double-terminal order cost in the calculation of the order dispatching preference degree of the transportation personnel. The weight determines the proportion of the double-terminal order cost in the comprehensive evaluation of whether the transportation personnel is suitable for taking the order. For example, if the weight of the double-terminal order cost is set to 0.4, it means that the double-terminal order cost accounts for 40% of the final result in the calculation of the order dispatching preference degree. The higher the weight, the greater the influence of the double-terminal order cost on the order dispatching preference degree.

[0158] In this embodiment, the weight of the order dispatching busy degree is a value that reflects the importance of the order dispatching busy degree in the calculation of the order dispatching preference degree of the transportation personnel. It reflects the influence of the business saturation of the transportation personnel at the target delivery time on the suitability of taking the order. For example, if the weight of the order dispatching busy degree is set to 0.3, it means that the order dispatching busy degree accounts for 30% of the influence in the determination of the order dispatching preference degree. A higher weight indicates that the order dispatching busy degree is more critical in evaluating the ability of the transportation personnel to take the order.

[0159] In this embodiment, the weight of the current weight of the single transportation personnel currently calculated is a weight value set for the current weight of the single transportation personnel in the calculation of the order dispatching preference degree. The current weight of the transportation personnel comprehensively reflects various characteristics of the transportation personnel, and this weight further adjusts the role of the current weight in the calculation of the order dispatching preference degree. For example, if the weight is set to 0.3, it means that the current weight accounts for 30% of the influence in the determination of the order dispatching preference degree. By adjusting this weight, the influence of the current weight of the transportation personnel on the order dispatching preference degree can be flexibly controlled according to actual business needs.

[0160] The beneficial effects of the above technical solutions are: the transportation personnel weight acquisition unit acquires the current weight of the transportation personnel, providing important basic data for comprehensively evaluating the suitability of the transportation personnel to undertake orders. The weight comprehensively reflects various characteristics of the transportation personnel, such as work experience, credit level, etc., making the subsequent analysis more targeted. The order dispatch optimization degree calculation unit considers the double-end order cost, order dispatch busy degree, and current weight of the transportation personnel through a scientific calculation formula, accurately calculating the order dispatch optimization degree. The weights of the double-end order cost, order dispatch busy degree, and current weight can be flexibly adjusted according to actual business needs, highlighting the importance of different factors in order dispatch decision-making. For example, during the business peak period, the weight of the order dispatch busy degree can be appropriately increased to preferentially select relatively idle transportation personnel, ensuring efficient allocation of orders. In this way, the system can more accurately measure the advantage degree of each transportation personnel to undertake the target instant lottery delivery order, providing a more scientific decision basis for the delivery scheduling system. Reasonable order dispatch optimization degree calculation helps to optimize order allocation, improve transportation resource utilization efficiency, ensure the smooth completion of instant lottery delivery tasks, and improve the quality and efficiency of the entire delivery service.

[0161] Embodiment 9

[0162] Based on embodiment 1, the delivery intelligent supervision module comprises:

[0163] The double-position monitoring sub-module is configured to calculate the error value between the real-time positioning data of the communication device terminal of the final transportation personnel and the real-time positioning data of the intelligent lottery transportation box when any of the real-time positioning data reaches the delivery endpoint position of the target instant lottery delivery order;

[0164] The unlocking empowerment sub-module is configured to empower the communication device terminal of the final transportation personnel with the permission to unlock the corresponding intelligent lottery transportation box when the error value between the real-time positioning data of the communication device terminal of the final transportation personnel and the real-time positioning data of the intelligent lottery transportation box is less than the preset error value, and simultaneously send an opening warning information to the recipient of the target instant lottery delivery order and count the duration after opening the box.

[0165] The order monitoring sub-module is configured to mark the target instant lottery delivery order as completed on the total monitoring end when receiving the receipt information of the recipient of the target instant lottery delivery order when the duration after opening the box is less than the threshold value of the duration after opening the box, otherwise, a three-party alarm information is sent.

[0166] In this embodiment, any real-time positioning data reaches the target lottery ticket delivery order delivery end position, which refers to the real-time positioning data of one of the final transportation personnel communication equipment terminal or the intelligent lottery ticket transportation box showing that it has arrived at the designated delivery location of the order, indicating that the delivery subject is approaching or has arrived at the destination.

[0167] In this embodiment, the error value between the real-time positioning data of the final transportation personnel communication equipment terminal and the real-time positioning data of the intelligent lottery ticket transportation box is calculated, that is, the position information of the two is obtained through positioning technology, and a specific algorithm is used to calculate the position deviation between them, which is used to judge the spatial distance difference between the transportation personnel and the lottery ticket transportation box.

[0168] In this embodiment, the preset error value is a standard distance value set in advance, which is used to compare with the above calculated error value to determine whether the positions of the transportation personnel and the intelligent lottery ticket transportation box are close enough to determine whether to grant the unlocking permission.

[0169] In this embodiment, the intelligent lottery ticket transportation box is a box with positioning and other intelligent functions for transporting instant lottery tickets, which can provide real-time position information to ensure the safety and monitorability of the lottery transportation process.

[0170] In this embodiment, the final transportation personnel's communication equipment terminal is given the permission to unlock the corresponding intelligent lottery ticket transportation box, and when the position error between the transportation personnel and the intelligent lottery ticket transportation box meets the conditions, the transportation personnel is given permission to open the transportation box through the communication equipment to deliver the lottery tickets.

[0171] In this embodiment, the opening box warning information is a notification message sent to the recipient when the transportation personnel is given the permission to unlock the intelligent lottery ticket transportation box, informing the other party that the lottery box will be opened.

[0172] In this embodiment, the opening box duration refers to the time duration after the intelligent lottery ticket transportation box is opened, which is used to monitor the time progress of the lottery delivery process.

[0173] In this embodiment, the opening box duration threshold is a pre-set time standard used to determine whether the lottery delivery process is completed within the specified time.

[0174] In this embodiment, if the opening box duration exceeds the threshold and no receipt information is received from the recipient, the system will send an alarm to the transportation personnel, the recipient and the management and monitoring terminal, indicating that the delivery has an abnormal situation.

[0175] The beneficial effects of the above technical scheme are that the double positioning monitoring sub-module tracks the positioning data of the terminal of the communication device of the final transportation personnel and the intelligent lottery transportation box in real time, calculates the error value when one party arrives at the delivery endpoint, accurately grasps the transportation state, and provides a reliable basis for subsequent operation. The unlocking empowerment sub-module takes the condition that the error value is less than the preset value as the condition for empowering the terminal of the communication device to unlock the intelligent lottery transportation box, simultaneously sends an opening box warning information to the receiving party and counts the duration after the opening box, guarantees the safety of lottery delivery, and standardizes the opening box process. The order monitoring sub-module judges the order state according to the comparison of the duration after the opening box and the preset threshold value and whether the receiving information is received, timely handles the exception, 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 safety of the delivery process, reduces potential risks, improves the service quality, ensures the timely, accurate and safe delivery of the lottery, improves the user experience, and maintains the good image of the system.

[0176] Embodiment 10

[0177] The application provides an instant lottery intelligent delivery scheduling method based on Internet of Things, which is applied to any one of the instant lottery intelligent delivery scheduling systems based on Internet of Things, and comprises the following steps:

[0178] S1: generating a plurality of delivery paths based on the delivery endpoint position of the target instant lottery delivery order, determining a target delivery path coverage area covering all the delivery paths, and analyzing a delivery accident heat map of the target delivery path coverage area in each analysis duration based on historical delivery accident records;

[0179] S2: superimposing and analyzing the real-time traffic flow and the latest road condition evaluation parameter of each delivery path and the delivery accident heat map of the target delivery path coverage area in each analysis duration, analyzing the optimal coefficient of each delivery path at the target delivery time of the target instant lottery delivery order, and screening the delivery path with the maximum optimal coefficient as an initial optimal delivery path;

[0180] S3: distributing the optimal transportation personnel set for the target instant lottery delivery order based on the current order distribution information of all the transportation personnel in the neighborhood of the initial optimal delivery path, and distributing the final transportation personnel for the target instant lottery delivery order based on the order reply result of the optimal transportation personnel set;

[0181] S4: performing real-time unlocking empowerment on the terminal of the communication device of the final transportation personnel based on the real-time positioning data of the terminal of the communication device of the final transportation personnel and the real-time positioning data of the intelligent lottery transportation box and the delivery endpoint position of the target instant lottery delivery order, and receiving the receiving information of the receiving party of the target instant lottery delivery order.

[0182] The beneficial effects of the above technology are: S1 generates multiple delivery paths according to the delivery end point position, determines the coverage area and obtains the delivery accident heat map in each analysis duration period combined with the historical accident record, which provides a comprehensive historical risk reference for path planning. S2 superimposes and analyzes the real-time traffic flow, the latest road condition evaluation parameters and the accident heat map to obtain the optimal coefficient of each path at the target delivery time, screens out the initial optimal delivery path, makes the path selection consider the real-time situation and potential risks comprehensively, and improves the delivery efficiency and safety. S3 distributes the optimal transportation personnel set to the order according to the order information of the transportation personnel in the neighborhood of the initial optimal path, and determines the final transportation personnel according to the reply result, realizes the reasonable allocation of transportation resources. S4 compares the real-time positioning data of the final transportation personnel and the intelligent lottery transportation box with the delivery end point position, and realizes the real-time unlocking of the transportation personnel communication equipment terminal, until the signing information is received, which effectively guarantees the safety and controllability of the delivery process, ensures the accurate and safe delivery of the instant lottery. The overall scheme can break through the limitations of the traditional mode by integrating real-time data, intelligent analysis and remote monitoring functions. It can use Internet of Things devices to collect real-time traffic, location and other multi-dimensional data to provide comprehensive and accurate information support for delivery scheduling, which is of great significance to improve the efficiency and safety of instant lottery delivery, enhance user experience and promote the digital transformation of the lottery industry.

[0183] Obviously, those skilled in the art can make various modifications and variations to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application belong to the scope of the present application and its equivalent technology, the present application also intends to include these modifications and variations.

Claims

1. An instant lottery ticket intelligent dispatching and scheduling system based on the Internet of Things, characterized in that, The application comprises the following technical solutions: A delivery path and area analysis module is configured to generate multiple delivery paths based on the delivery end location of a target instant lottery ticket 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 is configured to perform superimposed analysis on real-time traffic flow and the latest road condition evaluation parameters of each delivery path, the delivery accident heat map of the target delivery path coverage area in each analysis duration, analyze an optimization coefficient of each delivery path at the target delivery time of the target instant lottery ticket delivery order, and screen a delivery path with the largest optimization coefficient as an initial optimal delivery path; A transportation personnel double selection module is configured to assign an optimal transportation personnel set to the target instant lottery ticket delivery order based on current order allocation information of all transportation personnel in the neighborhood of the initial optimal delivery path, and assign a final transportation personnel to the target instant lottery ticket delivery order based on order reply results of the optimal transportation personnel set; A delivery intelligent supervision module is configured to perform real-time unlocking empowerment on a communication device terminal of the final transportation personnel based on real-time positioning data of the communication device terminal and real-time positioning data of an intelligent lottery transportation box, and the delivery end location of the target instant lottery ticket delivery order, until receiving a signing information of a signing party of the target instant lottery ticket delivery order; The transportation personnel double selection module comprises: A cost and busy degree evaluation submodule is configured to evaluate a double-end order receiving cost and order assigning busy degree of each transportation personnel in the neighborhood of the initial optimal delivery path at the target delivery time of the target instant lottery ticket delivery order based on current order allocation information of all transportation personnel in the neighborhood of the initial optimal delivery path; An order assigning optimization degree analysis submodule is configured to calculate an order assigning optimization degree of each transportation personnel based on the double-end order receiving cost and order assigning busy degree of each transportation personnel in the neighborhood of the initial optimal delivery path at the target delivery time of the target instant lottery ticket delivery order; An optimal transportation personnel preliminary selection submodule is configured to generate an optimal transportation personnel sequence based on the order assigning optimization degree of all transportation personnel in the neighborhood of the initial optimal delivery path, and assign an optimal transportation personnel set to the target instant lottery ticket delivery order based on the optimal transportation personnel sequence; An optimal transportation personnel final selection submodule is configured to send the target instant lottery ticket delivery order to the optimal transportation personnel set, and assign a final transportation personnel to the target instant lottery ticket delivery order based on order reply results of the optimal transportation personnel set; The cost and busy degree evaluation submodule comprises: A transportation personnel weight analysis unit is configured to determine a transportation personnel end order receiving cost weight and a unit transportation cost in a preset order cost division unit of each transportation personnel based on a current weight of each transportation personnel in the neighborhood of the initial optimal delivery path; A double-end order receiving cost evaluation unit is configured to calculate a double-end order receiving cost of each transportation personnel in the neighborhood of the initial optimal delivery path at the target delivery time of the target instant lottery ticket delivery order based on the transportation personnel end order receiving cost weight of each transportation personnel. ； In the formula, is the transport personnel end termination order cost weight of the single transport personnel currently calculated, is the path cost weight of the order sending end, is the length of the initial preferred delivery path, is the transport cost weight of the order sending end, is the unit transport cost of the single transport personnel currently calculated 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 transport personnel end of the single transport personnel currently calculated, is the relative order receiving income loss weight of the transport personnel end of the single transport personnel currently calculated, is the historical average order receiving income of the single transport personnel at the target delivery time point currently calculated, is the expected order receiving income of the single transport personnel when receiving the target instant lottery delivery order currently calculated; The order distribution busy degree prediction unit is configured to predict an order distribution busy degree of each delivery personnel in the initial preferred delivery path neighborhood at a target delivery time of the target instant lottery ticket delivery order.

2. The IoT-based smart dispensing and dispatching system for instant lottery tickets as claimed in claim 1 wherein, The delivery path and area analysis module comprises: The delivery path determination submodule is configured to query an electronic map to determine a plurality of delivery paths between a delivery starting point and a delivery ending point of the target instant lottery ticket delivery order. The delivery area division submodule is configured to determine a minimum square geographic area covering all the delivery paths as a target delivery path coverage area. The accident heat map generation submodule is configured to analyze a delivery accident heat map of the target delivery path coverage area in each analysis duration based on historical delivery accident records.

3. The IoT-based smart dispensing and dispatching system for instant lottery tickets as claimed in claim 1 wherein, The path preference analysis module comprises: The relative risk coefficient analysis submodule is configured to analyze a local relative risk coefficient of each delivery path in each analysis duration based on the delivery accident heat map of the target delivery path coverage area in each analysis duration. The preferred coefficient calculation submodule is configured to calculate a preferred coefficient of each delivery path at the target delivery time of the target instant lottery ticket delivery order based on 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. The preferred path screening submodule is configured to screen a delivery path with the largest preferred coefficient from all the delivery paths as the initial preferred delivery path.

4. The IoT-based smart dispensing and dispatching system for instant lottery tickets as claimed in claim 3 wherein, The preferred coefficient calculation submodule comprises: The traffic flow prediction unit is configured to predict a traffic flow of each delivery path at the target delivery time based on real-time traffic flow of each delivery path. The preferred coefficient calculation unit is configured to calculate a preferred coefficient of each delivery path at the target delivery time of the target instant lottery ticket 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. ； In the formula, is the preferred coefficient of the current 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 current 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 current calculated single delivery path, is the weight of the local relative risk coefficient, is the total number of categories of all analysis duration periods, is the local relative risk coefficient of the current calculated single delivery path in the analysis duration period, is the duration length of the analysis duration period.

5. The IoT-based intelligent instant lottery ticket dispensing and scheduling system of claim 1, wherein, The order distribution busy degree prediction unit comprises: The final position determination subunit is configured to obtain a final order distribution terminal position of each delivery personnel in the initial preferred delivery path neighborhood before the target delivery time of the target instant lottery ticket delivery order. The order distribution busy degree prediction subunit is configured to input the final order distribution terminal position of each delivery personnel before the target delivery time of the target instant lottery ticket delivery order, a current weight of the delivery personnel and the target delivery time of the target instant lottery ticket delivery order into a preset order distribution busy degree prediction model to obtain the order distribution busy degree of each delivery personnel in the initial preferred delivery path neighborhood at the target delivery time of the target instant lottery ticket delivery order.

6. The IoT-based intelligent instant lottery ticket dispensing and scheduling system of claim 1, wherein, The order distribution preference analysis submodule comprises: The delivery personnel weight acquisition unit is configured to obtain a current weight of each delivery personnel in the initial preferred delivery path neighborhood. The order distribution preference calculation unit is configured to calculate an order distribution preference of each delivery personnel based on a double-terminal order distribution cost and the order distribution busy degree of each delivery personnel in the initial preferred delivery path neighborhood at the target delivery time of the target instant lottery ticket delivery order and the current weight of each delivery personnel in the initial preferred delivery path neighborhood. ； wherein, is the current computed single transporter assignment preference, is the weight of the double ended assignment cost, is the weight of the assignment busy-ness, is the current computed single transporter assignment busy-ness at the target delivery time for the target instant lottery ticket delivery order, is the weight of the current computed single transporter current weight, is the current computed single transporter assignment preference.

7. The IoT-based intelligent instant lottery ticket dispensing and scheduling system of claim 1, wherein, The delivery intelligent supervision module comprises: The double positioning monitoring sub-module is configured to calculate an error value between the real-time positioning data of the communication terminal of the final delivery personnel and the real-time positioning data of the smart lottery transportation box when any of the real-time positioning data reaches a delivery end location of the instant lottery delivery order; The unlocking empowerment sub-module is configured to empower the communication terminal of the final delivery personnel with the permission to unlock the corresponding smart lottery transportation box when the error value between the real-time positioning data of the communication terminal of the final delivery personnel and the real-time positioning data of the smart lottery transportation box is less than a preset error value, and send an opening warning information to the recipient of the instant lottery delivery order, and count the duration after the opening of the box. The order monitoring sub-module is configured to mark the instant lottery delivery order as completed on the total monitoring end when receiving the receipt information of the recipient of the instant lottery delivery order when the duration after the opening of the box is less than a threshold of the duration after the opening of the box, otherwise, a three-party alarm information is sent.

8. An Internet of Things-based instant lottery ticket intelligent dispensing scheduling method, characterized in that, The instant lottery smart delivery scheduling system based on the Internet of Things according to any one of claims 1 to 7, comprising: S1: generating a plurality of delivery paths based on the delivery end location of the instant lottery delivery order, determining a target delivery path coverage area covering all the delivery paths, and analyzing a delivery accident heat map of the target delivery path coverage area in each analysis duration based on historical delivery accident records; S2: superimposing and analyzing 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, analyzing the preferred coefficient of each delivery path at the target delivery time of the instant lottery delivery order, and selecting the delivery path with the maximum preferred coefficient as the initial preferred delivery path; S3: based on the current order allocation information of all delivery personnel in the neighborhood of the initial preferred delivery path, allocating a preferred delivery personnel set for the instant lottery delivery order, and based on the order reply result of the preferred delivery personnel set, allocating a final delivery personnel for the instant lottery delivery order; S4: based on the real-time positioning data of the communication terminal of the final delivery personnel and the real-time positioning data of the smart lottery transportation box, and the delivery end location of the instant lottery delivery order, the communication terminal of the final delivery personnel is unlocked in real time, until the receipt information of the recipient of the instant lottery delivery order is received.

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