Big data logistics management system based on 5G

Abstract

The invention discloses a 5G-based big data logistics management system, and relates to the technical field of logistics management, and the system comprises a main control center which is in communication connection with a database, a classification module, a division module, and a planning module. The database is used for storing carrier information and cargo information, a carrier information sub-library and a cargo information sub-library are arranged in the database, the classification module is used for classifying carriers and cargoes, and a carrier classification unit and a cargo classification unit are arranged in the classification module. The dividing module is used for dividing logistics routes and carrier goods, a route dividing unit and a cargo dividing unit are arranged in the dividing module, the planning module is used for planning the logistics routes and inquiring the carrier goods, and a route planning unit and a cargo inquiring unit are arranged in the planning module; according to the technical scheme, on one hand, the logistics efficiency can be improved, and on the other hand, the logistics cost can be reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of logistics management, and specifically to a 5G-based big data logistics management system. Background Art

[0002] Logistics management refers to the planning, organization, command, coordination, control and supervision of logistics activities in social production activities according to the laws of material flow, applying the basic principles and scientific methods of management, so as to achieve the best coordination and cooperation of various logistics activities, reduce logistics costs, and improve logistics efficiency and economic benefits. In addition to inter-city logistics management, logistics management within cities has also become increasingly important. In the existing technology, logistics management within cities is mostly chaotic and complicated, resulting in high logistics costs and low efficiency. How to improve the efficiency of urban logistics and reduce the cost of urban logistics is an urgent problem to be solved. To this end, the present invention provides a 5G-based big data logistics management system. Summary of the invention

[0003] The purpose of the present invention is to provide a big data logistics management system based on 5G.

[0004] The object of the present invention can be achieved by the following technical solutions: A 5G-based big data logistics management system, comprising a main control center, wherein the main control center is communicatively connected to a database, a classification module, a division module, and a planning module; The database is used to store vehicle information and cargo information. The database is provided with a vehicle information sub-library and a cargo information sub-library. The vehicle information sub-library is used to store vehicle information, and the cargo information sub-library is used to store cargo information. The classification module is used to classify vehicles and goods. The classification module is provided with a vehicle classification unit and a goods classification unit. The vehicle classification unit is used to classify vehicles, and the goods classification unit is used to classify goods. The division module is used to divide logistics routes and carrier cargoes. The division module is provided with a route division unit and a cargo division unit. The route division unit is used to divide logistics routes, and the cargo division unit is used to divide carrier cargoes. The planning module is used to plan the logistics path and query the carrier cargo. The planning module is provided with a path planning unit and a cargo query unit. The path planning unit is used to plan the logistics path, and the cargo query unit is used to query the carrier cargo. Furthermore, the specific process of storing vehicle information in the vehicle information sub-library includes: An input unit is provided, and various basic information of the vehicle is input through the input unit, and various basic information of the vehicle input is reviewed by the main control center, and various basic information of the vehicle that passes the review is uploaded to the vehicle information sub-library for storage; Furthermore, the specific process of storing cargo information in the cargo information sub-library includes: A collection unit is provided to collect various basic information of the goods through the collection unit, the collected basic information of the goods is reviewed through the main control center, and the basic information of the goods that pass the review is uploaded to the goods information sub-library for storage; Furthermore, the specific process of the vehicle classification unit classifying the vehicle includes: According to the basic information of the vehicle obtained, the vehicle load of the vehicle is recorded as G i , and the vehicle volume of the vehicle is recorded as V i ; Set the load threshold G a and volume threshold V a ; When G i ≥G a And V i ≥V a , marking the vehicle as a large vehicle; When G i ≥G a And V i <V a , marking the vehicle as a medium vehicle; When G i <G a And V i ≥V a , marking the vehicle as a medium vehicle; When G i <G a And V i <V a , marking the vehicle as a small vehicle; Furthermore, the specific process of the cargo classification unit classifying the cargo includes: According to the basic information of the goods obtained, the weight of the goods is recorded as G j , and the cargo volume of the cargo is recorded as V j ; Set the weight threshold G b and volume threshold V b ; When G j ≥G b And V j ≥Vb When the cargo is marked as large cargo; When G j ≥G b And V j <V b When the cargo is marked as medium cargo; When G j <G b And V j ≥V b When the cargo is marked as medium cargo; When G j <G b And V j <V b When the cargo is marked as small cargo; Furthermore, the specific process of the route division unit dividing the logistics route includes: A geographical location is randomly selected in the urban area as the initial logistics management station, and the shortest distance between each geographical location and the existing logistics management station is obtained, and the probability value of each geographical location being selected as the next logistics management station is obtained; Select the geographical location corresponding to the maximum probability value as the next logistics management station, and repeat this step until n logistics management stations are selected; Obtain the shortest distance between each logistics management station and other logistics management stations, and at the same time obtain the total distance between each logistics management station and other logistics management stations; Select the logistics management station corresponding to the minimum total distance as the logistics management main station, and use other logistics management stations as logistics management sub-stations. With the logistics management main station as the starting point and the logistics management sub-station as the end point, construct n-1 logistics routes; Furthermore, the specific process of the cargo classification unit classifying the cargo on the carrier includes: Set the statistical period; For vehicles, provide the same number of large vehicles, medium vehicles, and small vehicles to each logistics route, and mark the quantity of each type of vehicle provided as the initial quantity; Obtain the theoretical transportation volume and actual transportation volume of each logistics route in the most recent statistical period, and mark the obtained theoretical transportation volume and actual transportation volume as L and S respectively; When L=S, no operation is performed on it; When L<S, increase the number of various vehicles provided; When L>S, reduce the number of various vehicles provided; For goods, the destination of each piece of goods is obtained, and the distance value between the destination of the goods and each logistics management substation is obtained; Select the logistics management substation corresponding to the minimum distance value, and divide the goods into logistics routes leading to the logistics management substation; Loading the same type of goods into the same type of vehicles, and after the goods are loaded into the vehicles, binding the goods to the vehicles; Furthermore, the specific process of the path planning unit planning the logistics path includes: Set monitoring period; A monitoring unit is provided inside the vehicle, and the road status is detected by the monitoring unit to obtain the road status in the most recent monitoring cycle, wherein the road status includes weather conditions, traffic jam conditions, and maintenance conditions; Replan the logistics route of subsequent vehicles based on the obtained road conditions to avoid traffic jams or road maintenance sections and obtain the shortest logistics route; Furthermore, the specific process of the cargo query unit querying the cargo on the carrier includes: A positioning device is arranged inside the vehicle, and the specific position of the vehicle is monitored in real time by the positioning device to obtain the specific position of the current vehicle; The cargo order number is input into the cargo query unit, and the specific location of the carrier bound to the cargo is queried to obtain the specific location of the queried cargo; When the vehicle leaves the logistics management center, the current time is marked as the departure time, and when the vehicle enters the logistics management substation, the current time is marked as the entry time, the time interval between the departure time and the entry time is obtained, and the obtained time interval is marked as the transportation duration; Obtain the transportation time of different vehicles on the same logistics route in the most recent monitoring cycle, and obtain the transportation degree of the logistics route. According to the specific location of the current vehicle, obtain the distance traveled and the distance not traveled by the vehicle, and obtain the remaining time for the vehicle to arrive.

[0005] Compared with the prior art, the beneficial effects of the present invention are as follows: the various logistics management stations obtained by the present invention can achieve the maximum degree of decentralized arrangement to meet the coverage requirements of the entire urban area. By comparing the theoretical transportation volume with the actual transportation volume, it is helpful to accurately grasp the transportation conditions of various logistics routes, and timely feedback can be given to various logistics routes to achieve optimal supply; By obtaining the cargo destination of each cargo and dividing it into the nearest logistics management substation, it is beneficial to centrally handle the cargo in the same or similar areas, which can not only improve the processing efficiency but also reduce the processing cost. By monitoring the road status and re-planning the logistics route of subsequent vehicles based on the obtained road status, the shortest logistics route can be obtained, which improves the efficiency of transportation on the one hand and reduces the cost of transportation on the other. BRIEF DESCRIPTION OF THE DRAWINGS

[0006] Figure 1 It is a schematic diagram of the present invention. DETAILED DESCRIPTION

[0007] like Figure 1 As shown, a 5G-based big data logistics management system includes a main control center, and the main control center is communicatively connected to a database, a classification module, a division module, and a planning module; The database is used to store vehicle information and cargo information. The database is provided with a vehicle information sub-library and a cargo information sub-library. The vehicle information sub-library is used to store vehicle information, and the cargo information sub-library is used to store cargo information. It should be further explained that, in the specific implementation process, the specific process of storing vehicle information in the vehicle information sub-library includes: An input unit is provided, and various basic information of the vehicle is input through the input unit, and various basic information of the vehicle input is reviewed by the main control center, and various basic information of the vehicle that passes the review is uploaded to the vehicle information sub-library for storage; it should be further explained that in the specific implementation process, various basic information of the vehicle includes vehicle model, vehicle status, vehicle load, vehicle volume, and vehicle driver; The specific process of storing cargo information in the cargo information sub-library includes: A collection unit is provided, through which various basic information of the goods is collected, the collected basic information of the goods is reviewed by the main control center, and the basic information of the goods that pass the review is uploaded to the goods information sub-library for storage; it should be further explained that in the specific implementation process, the basic information of the goods includes the goods order number, the goods type, the goods weight, the goods volume, and the goods destination; The classification module is used to classify vehicles and goods. The classification module is provided with a vehicle classification unit and a goods classification unit. The vehicle classification unit is used to classify vehicles, and the goods classification unit is used to classify goods. It should be further explained that, in a specific implementation process, the specific process of the vehicle classification unit classifying the vehicle includes: Number the vehicles, denoted as i, where i=1, 2, ...; According to the basic information of the vehicle obtained, the vehicle load of the vehicle is recorded as G i , and the vehicle volume of the vehicle is recorded as V i ; Set the load threshold G a and volume threshold V a ; When G i ≥G a And V i ≥V a , marking the vehicle as a large vehicle; When G i ≥G a And V i <V a , marking the vehicle as a medium vehicle; When G i <G a And V i ≥V a , marking the vehicle as a medium vehicle; When G i <G a And V i <V a , marking the vehicle as a small vehicle; The specific process of the cargo classification unit classifying cargo includes: Number the goods, denoted as j, where j = 1, 2, ...; According to the basic information of the goods obtained, the weight of the goods is recorded as G j , and the cargo volume of the cargo is recorded as V j ; Set the weight threshold G b and volume threshold V b ; When G j ≥G b And V j ≥V b When the cargo is marked as large cargo; When G j ≥G b And V j <V b When the cargo is marked as medium cargo; When G j <G b And V j ≥V b When the cargo is marked as medium cargo; When G j <G b And V j <V b When the cargo is marked as small cargo; The division module is used to divide logistics routes and carrier cargoes. The division module is provided with a route division unit and a cargo division unit. The route division unit is used to divide logistics routes, and the cargo division unit is used to divide carrier cargoes. It should be further explained that, in the specific implementation process, the specific process of the route division unit dividing the logistics route includes: A geographical location is randomly selected in the urban area as the initial logistics management station; Obtain the shortest distance between each geographical location and the current logistics management station, and record the obtained shortest distance as Q; Obtain the probability value of each geographical location being selected as the next logistics management station, and record the obtained probability value as P;

[0008] Select the geographical location corresponding to the maximum probability value as the next logistics management station, and repeat this step until n logistics management stations are selected; Obtain the shortest distance between each logistics management station and other logistics management stations, and mark the obtained shortest distances as Q1, Q2, ..., Q n-1 ; Get the total distance between each logistics management station and other logistics management stations, and mark the total distance obtained as Q 总 ;

[0009] Select the logistics management station corresponding to the minimum total distance as the logistics management main station, and use other logistics management stations as logistics management sub-stations; With the logistics management center as the starting point and the logistics management substation as the end point, n-1 logistics routes are constructed; The various logistics management stations obtained by the method of the present invention can achieve the maximum degree of dispersed arrangement to meet the coverage requirements of the entire urban area. The logistics management station corresponding to the minimum total distance is used as the logistics management center, which can reduce the transportation cost to the greatest extent. The specific process of the cargo classification unit classifying the cargo on the carrier includes: Set the statistical period T1; For vehicles, provide the same number of large vehicles, medium vehicles, and small vehicles to each logistics route, and mark the quantity of each type of vehicle provided as the initial quantity; Obtain the theoretical transportation volume and actual transportation volume of each logistics route in the most recent statistical period T1, and mark the obtained theoretical transportation volume and actual transportation volume as L and S respectively; The theoretical transport volume is specifically the sum of the vehicle loads of various types of vehicles provided, and the actual transport volume is specifically the sum of the weights of the transported goods; When L=S, no operation is performed on it; When L<S, increase the number of various vehicles provided; When L>S, reduce the number of various vehicles provided; By comparing the theoretical transport volume with the actual transport volume, it is helpful to accurately grasp the transport situation of each logistics route, and make adjustments based on the comparison results, so as to provide timely feedback to each logistics route and achieve optimal supply; For goods, the destination of each piece of goods is obtained, and the distance value between the destination of the goods and each logistics management substation is obtained; Select the logistics management substation corresponding to the minimum distance value, obtain the logistics route leading to the logistics management substation, and classify the goods into various types of vehicles provided for the logistics route; Load the same type of cargo onto the same type of vehicle, i.e. large cargo on large vehicles, medium cargo on medium vehicles, and small cargo on small vehicles; After the goods are loaded onto the vehicle, the goods are bound to the vehicle. When the vehicle leaves the logistics management center, the goods are marked as shipped. When the vehicle enters the logistics management substation, the goods are marked as arrived. By obtaining the destination of each cargo and assigning it to the nearest logistics management substation, it is beneficial to centrally handle cargo in the same or nearby areas, which can improve the processing efficiency and reduce the processing cost; The planning module is used to plan the logistics path and query the carrier cargo. The planning module is provided with a path planning unit and a cargo query unit. The path planning unit is used to plan the logistics path, and the cargo query unit is used to query the carrier cargo. It should be further explained that, in the specific implementation process, the specific process of the path planning unit planning the logistics path includes: Set monitoring period T2; A monitoring unit is set inside the vehicle, and the road state is detected by the monitoring unit to obtain the road state in the most recent monitoring period T2, wherein the road state includes weather conditions, traffic jam conditions, and maintenance conditions; The weather condition specifically refers to whether there is rain, snow or abnormal weather in the current weather; the traffic jam condition specifically refers to whether there is a traffic jam on the current road section and the duration of the traffic jam; the maintenance condition specifically refers to whether there is maintenance on the current road section and the duration of the maintenance; Replan the logistics route of subsequent vehicles based on the obtained road conditions to avoid traffic jams or road maintenance sections and obtain the shortest logistics route; By monitoring the road status, the actual condition of the current road can be known in time. The logistics route of subsequent vehicles can be replanned according to the obtained road status, which can effectively avoid the road sections with traffic jams or maintenance and obtain the shortest logistics route. On the one hand, it improves the efficiency of transportation and on the other hand, it also reduces the cost of transportation. The specific process of the cargo query unit querying the cargo on the carrier includes: A positioning device is arranged inside the vehicle, and the specific position of the vehicle is monitored in real time by the positioning device to obtain the specific position of the current vehicle; The cargo order number is input into the cargo query unit, and the specific location of the carrier bound to the cargo is queried to obtain the specific location of the queried cargo; Different from the previous positioning methods, the present invention directly sets the positioning device inside the carrier, binds the cargo to the carrier, and obtains the cargo location by querying the carrier location, which is helpful for users to accurately grasp the current cargo location and track it in real time; When the vehicle leaves the logistics management center, the current time is marked as the departure time, and the departure time is recorded as t1; When the vehicle enters the logistics management substation, the current time is marked as the entry time, and the entry time is recorded as t2; Obtaining a time interval between the departure time t1 and the arrival time t2, and marking the obtained time interval as a transportation duration, and recording it as J; Obtain the transportation time of different vehicles on the same logistics route in the most recent monitoring period T2, and number the obtained transportation time, denoted as k, where k = 1, 2, ..., m, and denoted as J k ; Obtain the transportation degree of the logistics route, and record the obtained transportation degree as C;

[0010] According to the specific position of the current vehicle, the distance traveled and the distance not traveled of the vehicle are obtained, and the distance traveled and the distance not traveled obtained are marked as Q respectively. 已 and Q 未, obtain the remaining time for the vehicle to arrive, and record the remaining time obtained as C 余 ;

[0011] By counting the transportation time of different vehicles on the same logistics route, we can obtain the transportation degree of each logistics route. According to the current position of the vehicle, the remaining time for the arrival of the goods can be predicted, which is conducive to accurately grasp the arrival time of the goods and handle them in advance.

[0012] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A 5G-based big data logistics management system, including a main control center, characterized in that: The main control center is communicatively connected to a database, a classification module, a division module, and a planning module; The database is provided with a vehicle information sub-library and a cargo information sub-library, wherein the vehicle information sub-library is used to store vehicle information, and the cargo information sub-library is used to store cargo information; The classification module is provided with a vehicle classification unit and a cargo classification unit, wherein the vehicle classification unit is used to classify vehicles, and the cargo classification unit is used to classify cargo; The division module is provided with a route division unit and a cargo division unit, wherein the route division unit is used to divide the logistics routes, and the cargo division unit is used to divide the carrier cargo; The planning module is provided with a path planning unit and a cargo query unit. The path planning unit is used to plan the logistics path, and the cargo query unit is used to query the carrier cargo.

2. A 5G-based big data logistics management system according to claim 1, characterized in that: The process of storing vehicle information in the vehicle information sub-library includes: An input unit is provided, through which various basic information of the vehicle is input, the inputted various basic information of the vehicle is reviewed, and the various basic information of the vehicle that passes the review is uploaded to the vehicle information sub-library for storage.

3. According to a 5G-based big data logistics management system according to claim 1, it is characterized in that: The process of storing cargo information in the cargo information sub-database includes: A collection unit is provided to collect various basic information of the goods, and the collected basic information of the goods is reviewed, and the basic information of the goods that passes the review is uploaded to the goods information sub-library for storage.

4. A 5G-based big data logistics management system according to claim 2, characterized in that: The process of classifying the vehicle by the vehicle classification unit includes: According to the basic information of the vehicle entered, the vehicle load G of the vehicle is obtained. i and the vehicle volume V i ; Set the load threshold G a and volume threshold V a ; When G i ≥G a And V i ≥V a , marking the vehicle as a large vehicle; When G i ≥G a And V i <V a , marking the vehicle as a medium vehicle; When G i <G a And V i ≥V a , marking the vehicle as a medium vehicle; When G i <G a And V i <V a , the vehicle is marked as a small vehicle.

5. A 5G-based big data logistics management system according to claim 3, characterized in that: The process of classifying cargo by the cargo classification unit includes: According to the basic information of the collected goods, the weight of the goods G is obtained. j and the cargo volume is denoted as V j ; Set the weight threshold G b and volume threshold V b ; When G j ≥G b And V j ≥V b When the cargo is marked as large cargo; When G j ≥G b And V j <V b When the cargo is marked as medium cargo; When G j <G b And V j ≥V b When the cargo is marked as medium cargo; When G j <G b And V j <V b When the cargo is shipped, the cargo is marked as small cargo.

6. The 5G-based big data logistics management system according to claim 1 is characterized in that: The process of dividing the logistics routes by the route division unit includes: Randomly select a geographical location as the initial logistics management station, obtain the shortest distance between each geographical location and the current existing logistics management station, and obtain the probability value of each geographical location being selected as the next logistics management station; Select the geographical location corresponding to the maximum probability value as the next logistics management station, and repeat this step until n logistics management stations are selected, and obtain the total distance between each logistics management station and other logistics management stations; The logistics management station corresponding to the minimum total distance is selected as the logistics management main station, and other logistics management stations are used as logistics management sub-stations. With the logistics management main station as the starting point and the logistics management sub-station as the end point, n-1 logistics routes are constructed.

7. A 5G-based big data logistics management system according to claim 6, characterized in that: The process of dividing the cargo on the carrier by the cargo dividing unit includes: Set the statistical period; For vehicles, obtain the theoretical transportation volume L and actual transportation volume S of each logistics route in the most recent statistical period; When L=S, no operation is performed on it; When L<S, increase the number of various vehicles provided; When L>S, reduce the number of various vehicles provided; For goods, the destination of each piece of goods is obtained, and the distance value between the destination of the goods and each logistics management substation is obtained; Select the logistics management substation corresponding to the minimum distance value, and divide the goods into the logistics routes leading to the logistics management substation, load the same type of goods into the same type of vehicles, and after the goods are loaded into the vehicles, bind the goods and the vehicles.

8. The 5G-based big data logistics management system according to claim 1, characterized in that: The process of the path planning unit planning the logistics path includes: Set monitoring period; A monitoring unit is arranged inside the vehicle, and the road state is detected by the monitoring unit to obtain the road state in the most recent monitoring cycle; The logistics path of subsequent vehicles is replanned according to the obtained road conditions to obtain the logistics path with the shortest time.

9. A 5G-based big data logistics management system according to claim 8, characterized in that: The process of the cargo query unit querying the cargo on the carrier includes: A positioning device is arranged inside the vehicle, and the specific position of the vehicle is monitored in real time by the positioning device to obtain the specific position of the current vehicle; Obtain the transportation time of different vehicles on the same logistics route in the most recent monitoring period, and obtain the transportation degree of the logistics route; According to the specific location of the current vehicle, the distance traveled and the distance not traveled by the vehicle are obtained, and the remaining time for the vehicle to arrive is obtained.

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