A logistics hub area planning method based on 5G technology

Abstract

The present invention discloses a logistics hub area planning method based on 5G technology, comprising the following steps: S1, data collection, obtaining the logistics information of trucks in the area through a detection device arranged at the center of the logistics hub, and uploading the obtained logistics information to the background processor through a 5G base station; S2, data processing, the background processor calculates the proportion of freight volume in each functional area of ​​the logistics hub according to the logistics information of all trucks; S3, formulating a planning strategy for the logistics hub area according to the calculation results. The present invention obtains the logistics information of all vehicles in the logistics hub, calculates the freight volume proportion data of various types of goods, and formulates a planning strategy for the logistics hub area according to the data, avoiding the interference of human subjective factors on the strategy, conforming to the law of logistics and transportation development, and effectively solving the problems of chaotic management and distribution of goods in the logistics hub and low efficiency of logistics distribution.

Description

Technical Field

[0001] The present invention belongs to the field of logistics technology, and specifically relates to a logistics hub area planning method based on 5G technology. Background Art

[0002] The distribution center of the express logistics industry is a key node in the entire distribution chain. Generally speaking, there will be multiple distribution centers in a larger spatial area, and multiple distribution centers will be responsible for different areas in the space. When several distribution centers in a certain area are determined, because the multiple distribution centers may differ in area, equipment, etc., how to accurately divide the entire area according to the distribution of different distribution centers and regional businesses has become a real practical problem faced by the distribution center of the express logistics industry during its operation. Unreasonable area planning schemes will lead to reduced express delivery timeliness and increased operating costs of distribution centers.

[0003] As the importance of regional logistics hub construction in regional economic development becomes increasingly prominent, logistics hubs are places for cargo transfer, sorting, and other operations. They have huge freight and logistics volumes and can effectively improve the speed of logistics cargo transfer. At present, many logistics hubs have been built or are under construction in China. Logistics hubs often bring together a variety of types of goods, such as fresh food, chemicals, textiles, etc. In the past, logistics hubs often lacked the detection and matching comparison of the freight volume of various types of goods, resulting in confusion in the management and allocation of goods at logistics hubs, affecting the efficiency of logistics distribution.

[0004] The Chinese patent with publication number CN111144675A discloses a district planning method, device, equipment and storage medium, the district planning method includes: obtaining the distribution data of the distribution center in the planning area, and the handover data between the distribution center and the corresponding handover mechanism; pre-allocating the service relationship between the handover mechanism and the distribution center under the preset rules; collecting all pre-allocation plans and corresponding transportation costs, and selecting the service relationship combination of the distribution center and the handover mechanism with the lowest total transportation cost as the district planning. It is suitable for the regional division containing multiple distribution centers, such as the aviation hub, land transportation hub, different levels of transfer yards, warehouses, and even the regional division of customer service points in the express logistics industry.

[0005] Although this patent can also plan the area of ​​the logistics distribution center, it does not take into account the types of goods and the amount of logistics, and still cannot solve the problem of chaotic management and distribution of goods in the logistics hub, which affects the efficiency of logistics distribution. Summary of the invention

[0006] The purpose of this invention is to provide a logistics hub area planning method based on 5G technology to address the problems existing in the prior art.

[0007] To achieve the above object, the technical solution adopted by the present invention is:

[0008] A logistics hub area planning method based on 5G technology includes the following steps:

[0009] S1, data collection, obtaining logistics information of trucks in the area through a detection device deployed at the center of the logistics hub, and uploading the acquired logistics information to the backend processor through a 5G base station. The detection device is connected to the smart terminal on the truck through 5G base station wireless communication;

[0010] S2, data processing, the backend processor calculates the proportion of freight volume in each functional area of ​​the logistics hub based on the logistics information of all trucks, and displays the calculation results in the form of charts on the display screen at the center of the logistics hub;

[0011] S3, formulating a planning strategy for the logistics hub area based on the calculation results.

[0012] Specifically, in step S1, the logistics information includes: the type of truck and the type of goods, and different types of goods correspond to different functional areas.

[0013] Specifically, in step S2, the data processing process includes:

[0014] Data preprocessing, matching the collected logistics information with the types of goods installed in each functional area to obtain the logistics information of each functional area; the functional areas include: imported goods area, e-commerce express logistics area, international transit assembly area, fresh food area, chemical products area, textile area, etc.

[0015] Data conversion uses the rated load capacity of medium-sized trucks as the unit of measurement, converts different types of trucks according to their load capacity, and obtains the freight volume of each functional area; through data conversion, trucks of different load capacities are normalized to trucks of the same unit of measurement, which facilitates data statistics and calculations.

[0016] Data calculation, calculate the proportion of freight volume of each functional area based on the freight volume of each functional area.

[0017] Furthermore, the formula for converting different types of trucks according to load capacity is as follows:

[0018] m1=k1·m

[0019] m2=k2·m

[0020] Among them, m1 is the rated load of a small truck; m is the rated load of a medium truck; m2 is the rated load of a large truck; k1 is the conversion factor from a small truck to a medium truck, 0<k1<1; k2 is the conversion factor from a large truck to a medium truck, k2>1.

[0021] Furthermore, the proportion of freight volume in each functional area is calculated by the following formula:

[0022]

[0023] Among them, P i is the proportion of freight volume in the ith functional area; M i is the freight volume of the ith functional area; n is the number of functional areas, that is, the number of types of goods.

[0024] Furthermore, considering the proportion of trucks equipped with intelligent terminals, when calculating the freight volume of each functional area, it is necessary to increase the correction coefficient to reduce the error. The proportion of freight volume of each functional area after correction is:

[0025]

[0026] Wherein, k is the correction coefficient, and k≥1; the value of the correction coefficient is obtained based on statistical probability.

[0027] Specifically, in step S3, the planning strategy of the logistics hub area is:

[0028] Adjust the floor space, location, number of channels and number of equipment of each functional area according to the proportion of freight volume in each functional area;

[0029] The principles of adjustment are:

[0030] The larger the proportion of freight volume in a functional area, the larger the area of ​​the corresponding functional area (to ensure that goods of the same type are stored in the same area), the closer the location is to the edge of the logistics hub (to avoid large trucks blocking the logistics hub and affecting logistics efficiency), and the more channels and equipment there are (to improve the efficiency of cargo transportation and transit);

[0031] Avoid the aggregation of multiple functional areas with large freight volumes, so as to prevent multiple large trucks from being squeezed together, affecting the efficiency of freight transportation;

[0032] Multiple functional areas with small freight volumes are concentrated together. The freight transportation transit time in the areas with small freight volumes is short, and all of them are small trucks, which will not affect the transportation efficiency.

[0033] Furthermore, the planning strategy of the logistics hub area also includes: adding a standby area and a backup channel between two functional areas. When the difference in the proportion of freight volume between the two functional areas is too large, the backup area and the backup channel will be temporarily transferred to the functional area with a larger proportion of freight volume for use, which can effectively alleviate the pressure of cargo transshipment.

[0034] Compared with the prior art, the beneficial effects of the present invention are as follows: the present invention obtains the logistics information of all vehicles in the logistics hub through 5G technology, obtains the freight volume share data of each type of goods through calculation, and formulates the planning strategy of the logistics hub area based on the data, avoiding the interference of human subjective factors on the strategy, conforming to the law of logistics and transportation development, and effectively solving the problems of chaotic management and distribution of goods in the logistics hub and low efficiency of logistics distribution. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 This is a flow chart of a logistics hub area planning method based on 5G technology in the present invention.

[0036] Figure 2 This is a diagram of the communication link architecture within the logistics hub in an embodiment of the present invention.

[0037] Figure 3 This is a schematic diagram of logistics hub area planning in an embodiment of the present invention. DETAILED DESCRIPTION

[0038] The technical solution of the present invention will be described clearly and completely below in conjunction with the accompanying drawings of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0039] like Figure 1 , 2 As shown, this embodiment provides a logistics hub area planning method based on 5G technology, including the following steps:

[0040] S1, data collection, obtains the logistics information of trucks in the area through the detection device deployed in the center of the logistics hub, and uploads the obtained logistics information to the background processor through the 5G base station. The detection device is connected to the smart terminal (mobile phone, etc.) on the truck through the 5G base station wireless communication; the detection device is a communication device for detecting mobile phone signals. The driver has registered the mobile phone number, truck type, cargo category and other information in advance. When the truck enters the coverage of the 5G base station, the detection device can detect the truck driver's mobile phone signal, thereby obtaining logistics information such as truck type and cargo category.

[0041] S2, data processing, the backend processor calculates the proportion of freight volume in each functional area of ​​the logistics hub based on the logistics information of all trucks, and displays the calculation results in the form of charts on the display screen at the center of the logistics hub;

[0042] S3, formulating a planning strategy for the logistics hub area based on the calculation results.

[0043] Specifically, in step S1, the logistics information includes: the type of truck and the type of goods, and different types of goods correspond to different functional areas.

[0044] Specifically, in step S2, the data processing process includes:

[0045] Data preprocessing, matching the collected logistics information with the types of goods installed in each functional area to obtain the logistics information of each functional area; the functional areas include: imported goods area, e-commerce express logistics area, international transit assembly area, fresh food area, chemical products area, textile area, etc.

[0046] Data conversion uses the rated load capacity of medium-sized trucks as the unit of measurement, converts different types of trucks according to their load capacity, and obtains the freight volume of each functional area; through data conversion, trucks of different load capacities are normalized to trucks of the same unit of measurement, which facilitates data statistics and calculations.

[0047] Data calculation, calculate the proportion of freight volume of each functional area based on the freight volume of each functional area.

[0048] Furthermore, the formula for converting different types of trucks according to load capacity is as follows:

[0049] m1=k1·m

[0050] m2=k2·m

[0051] Among them, m1 is the rated load of a small truck; m is the rated load of a medium truck; m2 is the rated load of a large truck; k1 is the conversion factor from a small truck to a medium truck, 0<k1<1; k2 is the conversion factor from a large truck to a medium truck, k2>1.

[0052] Furthermore, the proportion of freight volume in each functional area is calculated by the following formula:

[0053]

[0054] Among them, P i is the proportion of freight volume in the ith functional area; M i is the freight volume of the ith functional area; n is the number of functional areas, that is, the number of types of goods.

[0055] Furthermore, considering the proportion of trucks equipped with intelligent terminals, when calculating the freight volume of each functional area, it is necessary to increase the correction coefficient to reduce the error. The proportion of freight volume of each functional area after correction is:

[0056]

[0057] Wherein, k is the correction coefficient, and k≥1; the value of the correction coefficient is obtained based on statistical probability.

[0058] Specifically, in step S3, the planning strategy of the logistics hub area is:

[0059] Adjust the floor space, location, number of channels and number of equipment of each functional area according to the proportion of freight volume in each functional area;

[0060] The principles of adjustment are:

[0061] The larger the proportion of freight volume in a functional area, the larger the area of ​​the corresponding functional area (to ensure that goods of the same type are stored in the same area), the closer the location is to the edge of the logistics hub (to avoid large trucks blocking the logistics hub and affecting logistics efficiency), and the more channels and equipment there are (to improve the efficiency of cargo transportation and transit);

[0062] Avoid the aggregation of multiple functional areas with a large proportion of freight volume, so as to prevent multiple large trucks from being squeezed together and affecting the efficiency of freight transportation; in this embodiment, the functional area with a freight volume of more than 15% is the area with a large proportion (such as Figure 3 In the middle, areas A, B, C and D), it is necessary to avoid the aggregation of multiple areas with the same large proportion;

[0063] Multiple functional areas with a small proportion of freight volume are concentrated together. The freight transportation transit time in the areas with a small proportion of freight volume is short, and all of them are small trucks, which will not affect the transportation efficiency. In this embodiment, the functional areas with a freight volume proportion of less than 5% are areas with a small proportion. These areas can be concentrated together for easy management.

[0064] Furthermore, the planning strategy of the logistics hub area also includes: adding a device-use area between two functional areas (such as Figure 3 In the E, F, G and H zones, Figure 3 The unnumbered areas are the areas other than the areas with a relatively large proportion of freight volume and the backup areas) and backup channels. When the difference in the proportion of freight volume between two functional areas is too large, the backup areas and backup channels will be temporarily transferred to the functional areas with a relatively large proportion of freight volume, which can effectively alleviate the pressure of cargo transshipment.

[0065] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0066] The present invention is described with reference to flowcharts and / or block diagrams of methods, platforms (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0067] This specification may be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. This specification may also be practiced in distributed computing environments where tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules may be located in local and remote computer storage media, including storage devices.

[0068] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0069] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1In a typical configuration, a computer includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0070] The memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0071] Computer-readable media include permanent and non-permanent, removable and non-removable media that can be used to store information by any method or technology. Information can be computer-readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, disk storage, quantum memory, graphene-based storage media or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include temporary computer-readable media (transitory media), such as modulated data signals and carrier waves.

[0072] In the description of this specification, the description with reference to the terms "one embodiment", "certain embodiments", "illustrative embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials, or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0073] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the technical solutions of the embodiments of the present invention.

Claims

1. A logistics hub area planning method based on 5G technology, characterized in that: The following steps are involved: S1, data collection, obtaining logistics information of trucks in the area through a detection device deployed at the center of the logistics hub, and uploading the acquired logistics information to the backend processor through a 5G base station. The detection device is connected to the smart terminal on the truck through 5G base station wireless communication; S2, data processing, the backend processor calculates the proportion of freight volume in each functional area of ​​the logistics hub based on the logistics information of all trucks, and displays the calculation results in the form of charts on the display screen at the center of the logistics hub; In step S2, the data processing process includes: Data preprocessing: matching the collected logistics information with the types of goods installed in each functional area to obtain the logistics information of each functional area; Data conversion, using the rated load of medium-sized trucks as the unit of measurement, convert different types of trucks by load to obtain the freight volume of each functional area; the formula for converting different types of trucks by load is as follows: ， in, is the rated load of a small truck; m is the rated load of a medium truck; is the rated load capacity of a large truck; The conversion factor for converting a small truck to a medium truck is ; The conversion factor for converting large trucks to medium trucks, ; Data calculation, calculate the proportion of freight volume in each functional area according to the freight volume of each functional area: ， in, is the proportion of freight volume in the ith functional area; is the freight volume of the ith functional area; n is the number of functional areas, i.e., the number of types of goods; S3, formulating a planning strategy for the logistics hub area based on the calculation results.

2. According to a 5G technology-based logistics hub area planning method according to claim 1, it is characterized in that: In step S1, the logistics information includes: the type of truck and the type of goods, and different types of goods correspond to different functional areas.

3. According to a 5G technology-based logistics hub area planning method according to claim 1, it is characterized in that: Taking into account the proportion of trucks equipped with smart terminals, when calculating the freight volume of each functional area, it is necessary to increase the correction coefficient to reduce the error. The corrected proportion of freight volume in each functional area is: ， Where k is the correction factor, and ; The value of the correction factor is derived based on statistical probability.

4. According to a 5G technology-based logistics hub area planning method according to claim 1, it is characterized in that: In step S3, the planning strategy of the logistics hub area is: Adjust the floor space, location, number of channels and equipment of each functional area according to the proportion of freight volume in each functional area; The principles of adjustment are: The larger the proportion of freight volume in a functional area, the larger the area of ​​the corresponding functional area, the closer the location is to the edge of the logistics hub, and the more channels and equipment there are; Avoid the concentration of multiple functional areas with large freight volumes; Multiple functional areas with small freight volumes will be concentrated together.

5. According to the 5G technology-based logistics hub area planning method of claim 4, it is characterized in that: The planning strategy for the logistics hub area also includes: adding a standby area and a backup channel between two functional areas. When the difference in the proportion of freight volume between the two functional areas is too large, the backup area and the backup channel will be temporarily transferred to the functional area with a larger proportion of freight volume for use.

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