Intelligent logistics scheduling method, system and device

Abstract

The invention discloses a logistics intelligent scheduling method, system and device, and the method comprises an operation front end, an operation middle end and an operation rear end, and the method based on the device and system comprises the steps: S1, building a logistics intelligent scheduling system, S2, data collection, S3, publishing and intelligent matching, S4, carrying out and process monitoring, and S5, carrying out the payment confirmation and settlement. Exclusive waybill recommendation is intelligently customized for each driver through multi-dimensional information such as historical order receiving behavior data, order receiving time preference, working habits, normal receiving areas and real-time positions of the drivers, and then intelligent matching is performed through a screening module not only based on distance, but also in combination with the multi-dimensional information such as waybill types, cargo priorities and driver habits, so that a waybill recommendation result is obtained. In addition, screening can be carried out through multiple conditions, it is ensured that the waybills received by the drivers better meet the actual requirements, real-time waybill information monitoring and online settlement can be achieved through the intelligent scheduling system, and the problems that vehicle sources and goods sources cannot be matched and freight settlement is caused due to information asymmetry are solved.

Description

Technical Field

[0001] The present invention relates to the field of port logistics, and in particular to a logistics intelligent scheduling method, system and device. Background Art

[0002] At present, with the development of port logistics and transportation industry, there are many existing logistics platforms. The vehicle-cargo matching and logistics market management of the basic Internet of Things logistics market are still in the stage of exploration. The existing relatively large-scale logistics platforms basically focus on domestic trunk truck transportation, mainly targeting large logistics companies and logistics platforms, while the competition among truck drivers of existing non-logistics companies and platforms is becoming more and more serious, and the existing logistics platforms mainly have the following problems:

[0003] 1. Vehicle orders are scattered, routes are complex, and the needs of each shipping customer are different, such as delivery time and truck arrival time, which makes it difficult for drivers to choose routes and match goods, resulting in low efficiency and high transportation costs.

[0004] 2. The transportation industry has a low threshold and many practitioners. There is no unified service standard and charging standard. Each order is negotiated, there is no standardization, and the platform takes a high commission.

[0005] 3. The payment period is long, the payment is slow, there is a risk that the freight cannot be recovered, and you also have to bear the transportation burden.

[0006] 4. The industry has a serious tidal demand phenomenon and supply and demand information is not smooth. For example, during the peak season, customers cannot find cars, or there are idle vehicles but cannot find goods due to information asymmetry, and a match cannot be made. During the off-season, cars are idle and no goods can be found. Due to information asymmetry, the source of cars and goods cannot be matched, making the overall efficiency of the industry low and unable to achieve a perfect match. Summary of the invention

[0007] The purpose of the present invention is to establish a logistics intelligent scheduling method, system and device based on Internet + logistics + finance to solve the problem of vehicle source and cargo source matching and freight settlement caused by information asymmetry, and optimize resource allocation while improving logistics transportation efficiency.

[0008] In order to achieve the above object, the present invention adopts the following technical scheme:

[0009] A logistics intelligent scheduling method, applied to lightning logistics, includes the following steps:

[0010] S1: Establish a logistics intelligent dispatching system, including the front-end, middle-end and back-end operations;

[0011] S2: Data collection, collecting customer and driver data from the client and freight end of the operation front end respectively. The client and freight end need to register and authenticate first, and then collect data through the first collection module and the second collection module, establish a NoSQL relational database, and pass it to the business processing module of the platform end;

[0012] S3: Release and intelligent matching. The first processing module generates a waybill list from the successfully approved waybill system information, and sends the waybill list to the acquisition module through the first sending module. After the acquisition module receives the information, the second processing module analyzes and processes the NoSQL relational database and generates a push list, which is then filtered through the filtering module and pushed to the waybill processing module for the driver to choose.

[0013] S4: Implementation and process monitoring. After the driver confirms the selection, the third sending module transmits the confirmation information to the second receiving module, the second receiving module transmits the confirmation information to the second sending module, and the second sending module transmits the confirmation information to the first receiving module to reach the client. After the customer confirms, the implementation begins, and the implementation process can be fully monitored;

[0014] S5: Confirmation and settlement of payment. When the order is completed, the driver uploads the waybill information through the financial module on the freight side. After the financial module confirms the payment information, it is passed to the settlement module on the platform side. The platform confirms and reviews it. If it fails the review, it will be uploaded again. After the review is successful, the information will be sent to the client's management module for confirmation. After the review is passed, the online settlement is completed.

[0015] Preferably, the screening module includes primary screening and multi-condition screening, wherein the primary screening includes but is not limited to route, distance, urgency, waybill preparation time, and cut-off time.

[0016] Preferably, the steps of the multi-condition screening are as follows:

[0017] Step 1: According to the push list, assign different levels according to the degree of urgency, including but not limited to A, B, C, and D:

[0018] Step 2: Then perform internal range screening for each level, giving priority to matching within the regional range;

[0019] Step 3: After the range matching is completed, the routes that drivers like or often transport are screened based on historical driver preference data, and dynamic data such as traffic, weather, and port congestion are screened through the real-time processing module;

[0020] Step 4: Based on the route matching results, use the real-time GPS data to calculate the distance from the driver's location to the loading and unloading location using the distance calculation formula, and select the driver closest to the loading and unloading location;

[0021] Step 5: Based on step 4, assign different weights to the evaluation scores of different dimensions of the driver's performance according to historical data for comprehensive scoring. The driver with the highest comprehensive score will have priority in getting push notifications.

[0022] Preferably, the distance is calculated as follows:

[0023]

[0024] d=R·c

[0025] in:

[0026] · is the latitude difference between the two points

[0027] Δλ is the difference in longitude between the two points (λ2-λ1)

[0028] R is the radius of the Earth, which is about 6371 kilometers on average

[0029] a and c are intermediate variables used to simplify calculations

[0030] d is the final spherical distance in kilometers

[0031] Preferably, the comprehensive score includes customer satisfaction, fulfillment rate, standard operation rate and punctuality rate, wherein the weight proportion and calculation formula of each weight are as follows:

[0032] Comprehensive score = (fulfillment rate × 0.4) + (punctuality rate × 0.25) + (customer satisfaction × 0.2) + (operation standardization rate × 0.15)

[0033] Preferably, the present invention also provides a system based on the logistics intelligent scheduling method, including an operation front end, an operation mid-end and an operation back end, the operation front end includes a client, a platform end and a freight end, the client includes a first acquisition module, an approval module, a first processing module, a first sending module, a management module and a first receiving module; the platform end includes a display module, a business module, a basic module, a basic component module, a system resource module and a security operation and maintenance module; the freight end includes a second acquisition module, a waybill processing module, a supervision module, a financial module, a third sending module and a third receiving module; the business module includes a business processing module and a business data center, wherein the business processing module includes an acquisition module, a screening module, a query module, a real-time processing module, a second processing module, a second sending module, a storage module, a settlement module and a second receiving module, wherein the second receiving module is connected to the first sending module and the third sending module respectively through signals, and the second sending module is connected to the first receiving module and the third receiving module respectively through signals.

[0034] Preferably, the first collection module collects waybill data, including but not limited to cargo type, cargo quantity / weight, waybill container making time and container cut-off time, urgency, freight, and waybill status. After data collection, it is reviewed by the approval module. After the review, order information is generated by the first processing module and sent to the second receiving module through the first sending module signal, wherein the management module is used for real-time update, viewing of waybill status and payment services.

[0035] Preferably, the second collection module mainly collects driver data, including but not limited to work status, real-time location, historical order records, and driver preferences. After collection, it is sent to the second receiving module through the third sending module and stored in the storage module. The supervision module mainly monitors the driver in real time during the transportation process, and feeds back to the client management module through the storage module. The financial module is used for settlement after the waybill is completed. After the driver submits the settlement, it is confirmed by the settlement module and the management module before settlement.

[0036] Preferably, the acquisition module mainly receives information from the client and the freight end, and analyzes and processes the NoSQL relational database through the second processing module, and then pushes the final list to the waybill processing module through the screening module for the driver to choose, wherein the query module is mainly used for query on the platform side, and the settlement module is used for the platform side to verify the driver's waybill fee.

[0037] Preferably, a device based on a logistics intelligent scheduling system includes an operation front end, an operation mid-end and an operation back end, wherein the operation front end includes a client end, a platform end and a freight end; the operation mid-end includes at least one operation node, a customer node and a driver interface service node, and the operation back end includes a gateway, a switch and a plurality of servers with different functions, wherein the customer node is used to receive, process and send freight information, the driver interface service node transmits the information received and processed by the driver to the operation node, and the operation node connects the customer node and the driver interface service node together, and transmits and dispatches business instructions.

[0038] The beneficial effects of the present invention are:

[0039] 1. Through the driver's historical order acceptance behavior data, order acceptance time preference, work habits, frequently accepted areas, real-time location and other multi-dimensional information, we can intelligently customize exclusive waybill recommendations for each driver. Secondly, through the screening module, we can intelligently match based not only on distance, but also on waybill type, cargo priority, driver habits and other multi-dimensional information. We can also screen through multiple conditions to ensure that the waybill received by the driver is more in line with his actual needs.

[0040] 2. The real-time processing module can comprehensively consider dynamic data such as real-time traffic, weather, port congestion, etc., and recommend the best route and waybill for drivers, reducing the time and cost waste caused by changes in the external environment. In addition, this intelligent dispatching system can realize real-time monitoring of waybill information and online settlement, solving the problem of vehicle source and cargo source matching and freight settlement caused by information asymmetry. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 is a flow chart of the method of the present invention;

[0042] Figure 2 is a system flow chart of the present invention;

[0043] Figure 3 It is a system flow chart of the client of the present invention;

[0044] Figure 4 It is a system flow chart of the business module of the present invention;

[0045] Figure 5 This is a system flow chart of the freight terminal of the present invention;

[0046] Figure 6 It is a schematic diagram of the steps of multi-condition screening of the present invention;

[0047] Figure 7 It is a structural diagram of the logistics intelligent scheduling device;

[0048] Figure 8 It is a schematic diagram of the interface of the platform end of the present invention. DETAILED DESCRIPTION

[0049] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0050] In the description of the present invention, it should be understood that the terms "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside" and "outside" etc., indicating directions or positional relationships, are based on the directions or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific direction, be constructed and operated in a specific direction, and therefore cannot be understood as a limitation on the present invention. In the description of the present invention, "multiple" means two or more, unless otherwise clearly and specifically defined.

[0051] Example 1, please refer to Figure 1, a logistics intelligent scheduling method, applied to lightning logistics, includes the following steps:

[0052] S1: Establish a logistics intelligent dispatching system, including the front-end, middle-end and back-end operations;

[0053] S2: Data collection, collect customer and driver data from the client and freight end of the operation front end respectively, where the client and freight end need to register and authenticate first, and then collect data through the first collection module and the second collection module. Driver data includes but is not limited to: driver preferences (such as common routes, favorite time periods), historical order records (including the time, location, price of each order, whether the waybill is received), real-time location (obtain the driver's current location through GPS), work status (online order acceptance, offline rest, etc.); customer data mainly refers to waybill data including but not limited to: loading location, unloading location, distance, freight, urgency, waybill cabinet time and cabinet cut-off time, waybill status (pending, already grabbed, completed, etc.) of each waybill, establish a NoSQL relational database, and pass it to the business processing module on the platform side;

[0054] S3: Release and intelligent matching. The first processing module generates a waybill list from the successfully approved waybill system information, and sends the waybill list to the acquisition module through the first sending module. After the acquisition module receives the information, the second processing module analyzes and processes the NoSQL relational database and generates a push list, which is then filtered through the filtering module and pushed to the waybill processing module for the driver to choose.

[0055] S4: Implementation and process monitoring. After the driver confirms the selection, the third sending module transmits the confirmation information to the second receiving module, the second receiving module transmits the confirmation information to the second sending module, and the second sending module transmits the confirmation information to the first receiving module to reach the client. After the customer confirms, the implementation begins, and the implementation process can be fully monitored;

[0056] S5: Confirmation and settlement of payment. When the order is completed, the driver uploads the waybill information (cargo weight, freight information, settlement approval receipt, etc.) through the financial module on the freight side. After the financial module confirms the payment information, it is passed to the settlement module on the platform side. The platform confirms and reviews it. If it fails the review, it will be uploaded again. After the review is successful, the information will be sent to the client's management module for confirmation. After the review is passed, the online settlement is completed.

[0057] The screening module includes primary screening and multi-condition screening, wherein the primary screening includes but is not limited to route, distance, urgency, waybill processing time, and cut-off time.

[0058] The query module can perform intelligent query on NoSQL relational databases. In the database, the SQL WHERE condition is used to perform preliminary screening based on the driver's real-time location and preferences, filtering out waybills that do not meet the conditions (such as the driver's order acceptance area does not match the range). Secondly, geographic spatial query is used, such as the ST_Distance_Sphere() function in MySQL, to filter out waybills that meet the distance conditions.

[0059] See also Figure 6 , the steps of multi-condition screening are as follows:

[0060] Step 1: According to the push list, assign different levels according to the degree of urgency, including but not limited to A, B, C, and D:

[0061] Step 2: Then perform internal range screening for each level, giving priority to matching within the regional range;

[0062] Step 3: After the range matching is completed, the routes that drivers like or often transport are screened based on historical driver preference data, and dynamic data such as traffic, weather, and port congestion are screened through the real-time processing module;

[0063] Step 4: Based on the route matching results, use the real-time GPS data to calculate the distance from the driver's location to the loading and unloading location using the distance calculation formula, and select the driver closest to the loading and unloading location;

[0064] Step 5: Based on step 4, assign different weights to the evaluation scores of different dimensions of the driver's performance according to historical data for comprehensive scoring. The driver with the highest comprehensive score will be given priority to receive the push plan.

[0065] The distance is calculated as follows:

[0066]

[0067] d=R·c

[0068] in:

[0069] · is the latitude difference between the two points

[0070] Δλ is the difference in longitude between the two points (λ2-λ1)

[0071] R is the radius of the Earth, which is about 6371 kilometers on average

[0072] a and c are intermediate variables used to simplify calculations

[0073] d is the final spherical distance in kilometers

[0074] The distance includes the time when the driver arrives at the pickup location and the time when the driver arrives at the delivery address. The distance data is updated in real time:

[0075] Given the latitude and longitude of two points:

[0076] The longitude and latitude of point 1 are: (lat1, lon1)

[0077] The longitude and latitude of point 2 are: (lat2, lon2)

[0078] First, we calculate the latitude difference between the two points and longitude difference (Δλ), and then introduce the distance calculation formula, the shortest distance is d 总 =d1+d2, d1 is the distance the driver needs to travel to the pickup address, and d2 is the distance the driver needs to travel to the delivery address.

[0079] The multi-condition screening provided by this embodiment overcomes the drawback of primary screening that only filters and queries single data. Primary screening can only include specific single data, such as route, range, urgency, etc. If tasks are assigned only for single data, drivers can only obtain single information. This will increase the risk for individual drivers. For example, only the route is displayed, but there is no urgency, cabinet making time, and cabinet closing time. In this way, if the driver is delayed or the delivery time is delayed due to information asymmetry, the driver can only bear the loss.

[0080] Multi-condition screening enables intelligent recommendations:

[0081] Step 1: According to the push list, different levels are assigned according to the degree of urgency, including but not limited to A, B, C, and D: The urgency of the cargo order is preferably set, and different levels are set. Then, each level is internally screened, and internal matching is prioritized within the region. The delivery range is determined based on the waybill information provided by the customer. For example, in a certain city, after the range matching is completed, the routes that the driver likes or often transports are screened based on the historical driver preference data, and dynamic data such as traffic, weather, and port congestion are screened through the real-time processing module. Using GPS real-time data, the distance from the driver's location to the loading and unloading location is calculated through the distance calculation formula, and the driver closest to the loading and unloading location is screened. After the driver is screened, the driver's performance in different dimensions is evaluated and scored according to the driver's historical data, and different weights are assigned for comprehensive scoring. The driver with the highest comprehensive score will be given priority in getting pushed.

[0082] The comprehensive score includes customer satisfaction, fulfillment rate, standard operation rate and punctuality rate, where the weight ratio and calculation formula of each are as follows:

[0083] Comprehensive score = (fulfillment rate × 0.4) + (punctuality rate × 0.25) + (customer satisfaction × 0.2) + (operation standardization rate × 0.15)

[0084] Weight setting:

[0085] The weight setting will be based on the customer's credit rating of the driver, and the driver's work performance will be evaluated through different dimensions. The scoring dimensions mainly include the following four points:

[0086] 1. Customer satisfaction (30% weight): Based on the feedback from the shippers, the driver's performance in terms of communication with the customer and service quality during transportation is evaluated. For drivers with high customer satisfaction, the system will give priority to recommending high-quality waybills to them.

[0087] Scoring mechanism: After the waybill is completed, the shipper can rate the driver, with a maximum score of 5. The system will average all the scores and convert them into credit points.

[0088]

[0089] 2. Compliance rate (30% weight): refers to the driver's completion of the waybill, including the timely completion rate of the waybill, breach of contract, etc. Drivers with a high compliance rate indicate that they are more reliable, so the system will match them with better waybill. Drivers who often maliciously cancel waybill and have low credibility will be punished by the system (such as canceling the order acceptance authority, limiting the order acceptance time limit, etc.)

[0090] Order completion rate: The actual completion rate of the driver after accepting the order. Cancellation or rejection of the order will reduce the score. On-time completion rate: If the driver completes the order within the specified time, the fulfillment rate score will increase.

[0091]

[0092] 3. Operation standardization rate (20% weight): including whether the driver's operation during transportation complies with the specifications, whether it is in accordance with the platform requirements, whether the correct container information is uploaded, and whether it is operated in accordance with the platform requirements.

[0093] Data source: Through GPS and waybill execution monitoring data, the system can automatically determine whether the driver's operation is standard.

[0094]

[0095] 4. Punctuality (20% weight): The driver's ability to arrive at the loading and unloading locations on time. The system will evaluate the driver based on his punctuality performance. The higher the punctuality, the higher the priority of the matching waybill.

[0096] Calculation logic: The on-time rate is calculated based on the driver's historical on-time arrival records. The number of late arrivals and the duration of late arrivals will significantly affect the score.

[0097]

[0098] See also Figure 2-8 , a system based on a logistics intelligent scheduling method, including an operation front end, an operation mid-end and an operation back end, the operation front end includes a client, a platform end and a freight end, the client includes a first acquisition module, an approval module, a first processing module, a first sending module, a management module and a first receiving module; the platform end includes a display module, a business module, a basic module, a basic component module, a system resource module and a security operation and maintenance module; the freight end includes a second acquisition module, a waybill processing module, a supervision module, a financial module, a third sending module and a third receiving module; the business module includes a business processing module and a business data center, wherein the business processing module includes an acquisition module, a screening module, a query module, a real-time processing module, a second processing module, a second sending module, a storage module, a settlement module and a second receiving module, wherein the second receiving module is connected to the first sending module and the third sending module respectively through signals, and the second sending module is connected to the first receiving module and the third receiving module respectively through signals.

[0099] Among them, the first acquisition module collects waybill data, including but not limited to cargo type, cargo quantity / weight, waybill container making time and container cut-off time, urgency, freight, waybill status, and after data collection, it is reviewed by the approval module, and after review, the order information is generated by the first processing module, and sent to the second receiving module through the first sending module signal, wherein the management module is used for real-time update, viewing of waybill status and payment services, the second acquisition module mainly collects driver data, including but not limited to work status, real-time location, historical order records, driver preferences, and after collection, it is sent to the second receiving module through the third sending module and stored in the storage module, the supervision module mainly monitors the driver in real time during the transportation process, and feeds back to the client management module through the storage module, the financial module is used for settlement after the waybill is completed, and the settlement is carried out after the driver's settlement submission is confirmed by the settlement module and the management module.

[0100] The acquisition module mainly receives information from the client and the freight end, and analyzes and processes the NoSQL relational database through the second processing module, and then pushes the final list to the waybill processing module through the screening module for the driver to choose. The query module is mainly used for query on the platform side, and the settlement module is used for the platform side to verify the driver's waybill fees.

[0101] See also Figure 7, a device based on a logistics intelligent scheduling system, including an operation front end, an operation middle end and an operation back end, wherein the operation front end includes a client end, a platform end and a freight end; the operation middle end includes at least an operation node, a customer node and a driver interface service node, and the operation back end includes a gateway, a switch and a plurality of servers with different functions, wherein the customer node is used to receive, process and send freight information, the driver interface service node transmits the information received and processed by the driver to the operation node, and the operation node connects the customer node and the driver interface service node together, and transmits and dispatches business instructions.

[0102] The above are only preferred embodiments of the present invention and are not intended to limit the present invention in other forms. Any technician familiar with the profession may use the technical contents disclosed above to change or modify them into equivalent embodiments with equivalent changes and apply them to other fields. However, any simple modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention without departing from the technical solution of the present invention still falls within the protection scope of the technical solution of the present invention.

Claims

1. A logistics intelligent scheduling method, applied to port logistics, characterized by: The steps include: S1: Establish a logistics intelligent dispatching system, including the front-end, middle-end and back-end operations; S2: Data collection, collecting customer and driver data from the client and freight end of the operation front end respectively. The client and freight end need to register and authenticate first, and then collect data through the first collection module and the second collection module, establish a NoSQL relational database, and pass it to the business processing module of the platform end; S3: Release and intelligent matching. The first processing module generates a waybill list from the successfully approved waybill system information, and sends the waybill list to the acquisition module through the first sending module. After the acquisition module receives the information, the second processing module analyzes and processes the NoSQL relational database and generates a push list, which is then filtered through the filtering module and pushed to the waybill processing module for the driver to choose. S4: Implementation and process monitoring. After the driver confirms the selection, the third sending module transmits the confirmation information to the second receiving module, the second receiving module transmits the confirmation information to the second sending module, and the second sending module transmits the confirmation information to the first receiving module to reach the client. After the customer confirms, the implementation begins, and the implementation process can be fully monitored; S5: Confirmation and settlement of payment. When the order is completed, the driver uploads the waybill information through the financial module on the freight side. After the financial module confirms the payment information, it is passed to the settlement module on the platform side. The platform confirms and reviews it. If it fails the review, it will be uploaded again. After the review is successful, the information will be sent to the client's management module for confirmation. After the review is passed, the online settlement is completed.

2. A logistics intelligent scheduling method according to claim 1, characterized in that: The screening module includes primary screening and multi-condition screening, wherein the primary screening includes but is not limited to route, distance, urgency, waybill processing time, and cut-off time.

3. A logistics intelligent scheduling method according to claim 2, characterized in that: The steps of multi-condition screening are as follows: Step 1: According to the push list, assign different levels according to the degree of urgency, including but not limited to A, B, C, and D: Step 2: Then perform internal range screening for each level, giving priority to matching within the regional range; Step 3: After the range matching is completed, the routes that drivers like or often transport are screened based on historical driver preference data, and dynamic data such as traffic, weather, and port congestion are screened through the real-time processing module; Step 4: Based on the route matching results, use the real-time GPS data to calculate the distance from the driver's location to the loading and unloading location using the distance calculation formula, and select the driver closest to the loading and unloading location; Step 5: Based on step 4, assign different weights to the evaluation scores of different dimensions of the driver's performance according to historical data for comprehensive scoring. The driver with the highest comprehensive score will have priority in getting push notifications.

4. A logistics intelligent scheduling method according to claim 3, characterized in that: The distance is calculated as follows: d=R. c in: · is the latitude difference between the two points Δλ is the difference in longitude between the two points (λ2-λ1) R is the radius of the Earth, which is about 6371 km on average a and c are intermediate variables used to simplify calculations d is the final spherical distance in kilometers.

5. The intelligent logistics dispatching method according to claim 3 is characterized by: The comprehensive score includes customer satisfaction, fulfillment rate, standard operation rate and punctuality rate, where the weight ratio and calculation formula of each are as follows: Comprehensive score = (fulfillment rate × 0.4) + (punctuality rate × 0.25) + (customer satisfaction × 0.2) + (operation standards × 0.15).

6. A system based on the logistics intelligent scheduling method according to any one of claims 1 to 5, characterized in that: It includes an operation front end, an operation mid-end and an operation back end, the operation front end includes a client, a platform end and a freight end, the client includes a first acquisition module, an approval module, a first processing module, a first sending module, a management module and a first receiving module; the platform end includes a display module, a business module, a basic module, a basic component module, a system resource module and a security operation and maintenance module; the freight end includes a second acquisition module, a waybill processing module, a supervision module, a financial module, a third sending module and a third receiving module; the business module includes a business processing module and a business data center, wherein the business processing module includes an acquisition module, a screening module, a query module, a real-time processing module, a second processing module, a second sending module, a storage module, a settlement module and a second receiving module, wherein the second receiving module is connected to the first sending module and the third sending module respectively through signals, and the second sending module is connected to the first receiving module and the third receiving module respectively through signals.

7. The intelligent logistics dispatching system according to claim 6, characterized in that: The first collection module collects waybill data, including but not limited to cargo type, cargo quantity / weight, waybill container making time and container cut-off time, urgency, freight, and waybill status. After data collection, it is reviewed by the approval module. After the review, the first processing module generates order information and sends it to the second receiving module through the first sending module signal, where the management module is used for real-time update, viewing of waybill status and payment services.

8. The intelligent logistics dispatching system according to claim 6, characterized in that: The second collection module mainly collects driver data, including but not limited to work status, real-time location, historical order records, and driver preferences. After collection, it is sent to the second receiving module through the third sending module and stored in the storage module. The supervision module mainly monitors the driver's transportation process in real time, and feeds back to the client management module through the storage module. The financial module is used for settlement after the waybill is completed. After the driver submits the settlement, it is confirmed by the settlement module and the management module before settlement.

9. The intelligent logistics dispatching system according to claim 6, characterized in that: The acquisition module mainly receives information from the client and the freight end, and analyzes and processes the NoSQL relational database through the second processing module, and then pushes the final list to the waybill processing module through the screening module for the driver to choose. The query module is mainly used for query on the platform side, and the settlement module is used for the platform side to verify the driver's waybill fees.

10. A logistics intelligent dispatching device, comprising an operation front end, an operation middle end and an operation back end, characterized in that: The operation front end includes a client, a platform and a freight end; the operation middle end includes at least an operation node, a customer node and a driver interface service node; the operation back end includes a gateway, a switch and a plurality of servers with different functions, wherein the customer node is used to receive, process and send freight information; the driver interface service node transmits the information received and processed by the driver to the operation node; the operation node connects the customer node and the driver interface service node together, and transmits and dispatches business instructions.

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