Enterprise logistics transportation optimization method based on artificial intelligence

Abstract

The invention discloses an enterprise logistics transportation optimization method based on artificial intelligence, and relates to the technical field of logistics management, and the method comprises the steps: 1, carrying out the planning of the position of a storage end based on the geographic information technology and the cooperation of a traffic network, and building a storage distribution model, the method comprises the following steps: collecting data of a vehicle team and data updating conditions of a storage end, monitoring vehicle conditions of the vehicle team and information of workers by establishing a vehicle team statistical model, and uploading the collected data. In the enterprise logistics transportation process, the stability and efficiency in the transportation process can be improved through the road condition in the transportation process, the enterprise condition in the docking process and the transportation scheme formulated in advance, and meanwhile, the safety in the transportation process is improved through dual monitoring of the carrying end and the driver in the transportation process.

Description

Technical Field

[0001] The present invention relates to the technical field of logistics management, and in particular to an enterprise logistics transportation optimization method based on artificial intelligence. Background Art

[0002] At present, enterprise logistics management involves a series of logistics activities such as material procurement, inventory management, transportation, warehousing, and distribution within the enterprise, aiming to achieve effective management of enterprise logistics operations by rationally allocating resources, improving transportation speed and reducing costs;

[0003] In the process of enterprise logistics transportation, although the existing technology can monitor the location of logistics in real time, it cannot formulate transportation plans in advance during the transportation process. Although some transportation plans can be formulated in advance, they cannot be optimized, resulting in too low efficiency in the transportation process. It is also impossible to monitor the driving conditions of the transportation end and the driver, resulting in limitations in the monitoring process, and the transportation method cannot be fully optimized. Summary of the invention

[0004] The purpose of the present invention is to provide an enterprise logistics transportation optimization method based on artificial intelligence to solve the problems raised in the above background technology.

[0005] To achieve the above purpose, the present invention provides the following technical solution: an enterprise logistics transportation optimization method based on artificial intelligence, comprising the following steps:

[0006] Step 1: Based on geographic information technology and the use of transportation networks, the location of the warehouse is planned, and a warehouse distribution model is established to collect the warehouse level and data update status of the warehouse. The fleet statistics model is established to monitor the fleet's vehicle conditions and staff information, and the collected data is uploaded;

[0007] Step 2: After the warehouse information and fleet data are collected, a central control model is established to receive and process the collected data, and a comprehensive management model is established to collect enterprise logistics information, and a plan formulation model is also established;

[0008] Step 3: During the logistics transportation process, a route planning model and an emergency response model are developed respectively. The route planning model plans the transportation route, and the emergency response module handles emergencies during the transportation process.

[0009] Preferably, the specific steps for constructing the warehouse distribution model in step 1 are as follows:

[0010] (1) The geographical location of the warehousing end is divided according to the distance between the location of the warehousing end and the main traffic artery. The best location is within five kilometers from the main traffic artery, the middle location is within ten kilometers from the main traffic artery, and the worst location is more than ten kilometers from the main traffic artery. The main traffic artery includes highways, national roads, expressways, water transport, railways and airport cargo. The order from high to low according to the tonnage is water transport, railways, highways, national roads, expressways and airport cargo;

[0011] (2) After the storage ends are divided into different levels, the location of each storage end is marked. The storage locations are divided into zones using A1, A2, A3, ..., and An for marking. Each storage end is modeled using virtual technology, and after modeling, the planning identification number is marked on the virtual model. A bar chart is used outside each virtual model to display the data inside the storage end, and the data is connected to each storage end in real time. When each storage end changes, the data of each storage end is updated in real time.

[0012] Preferably, the steps for constructing a fleet statistics module are as follows:

[0013] (1) After receiving the information from the warehouse, a process scheduling plan for the loading fleet is formulated based on the time and type of goods loaded at the warehouse. The area where goods are loaded at the warehouse is modeled in three dimensions through virtual technology to form a three-dimensional virtual world. After the loading process scheduling plan is formulated, a scheduling simulation is performed inside the virtual world. If problems are found during the scheduling simulation, the scheduling process plan is modified and optimized. After the plan is optimized, it is sent to the central control model, and an emergency scheduling plan is formulated at the same time.

[0014] (2) Investigate the driver's credit and violation record within five years and three years respectively. Drivers with ten violation records within five years will not be hired, and drivers with five violation records within three years will not be hired. After loading is completed, the freight route is connected to the map software. When the freight route is compared with the route in the map software, if it is found that the road section is congested or the road is narrow due to maintenance, the route will be readjusted;

[0015] A sensor is installed at the brake position of each truck. An electronic counter is installed inside the sensor, and the sensor is connected to the external central control model. Each sensor is marked, and the number of brakes for each truck is limited according to mileage and time during driving. The number of brakes in a short period of time is also limited, such as twenty times within ten seconds and thirty times within twenty seconds. Road condition information is collected during driving. When the number of brakes in a short period of time is too many, and the number of brakes generated in the freight mileage is too many, the driver will be interviewed. If the driver who is interviewed still exhibits the above-mentioned behavior later, the driver will be stopped from driving the truck again.

[0016] Preferably, the steps for constructing the comprehensive management module in step 2 are as follows:

[0017] (1) The procurement information, transportation time, inventory information, distribution capacity, climate of the region during transportation, road conditions during transportation, and unexpected situations of each warehouse are judged, and the storage information between each warehouse is networked, and a control plan is formulated for each warehouse. When the procurement or storage of one warehouse is abnormal, it is networked with the nearest warehouse to schedule the procurement plan and storage volume through the control plan;

[0018] (2) Carry out real-time monitoring of the regional climate at each storage end, formulate an early warning plan for each area, and connect with the Meteorological Bureau during the monitoring process. After connecting with the network, the early warning plan is optimized in real time. If an unexpected situation occurs, the early warning plan is immediately implemented for regulation.

[0019] Preferably, the steps of constructing the solution formulation model in step 2 are as follows:

[0020] (1) During the transportation process, each transport end is monitored in real time, and the road conditions and driver status of the transport route are monitored and fed back during the monitoring process. When the driver is found to be driving fatigued or suffering from a sudden illness, the driver will be stopped from driving through remote control. In addition, when the road conditions are abnormal, the delivery time of the goods will be flexibly adjusted;

[0021] (2) During the transportation process, the comprehensive information of the cooperative enterprises is integrated, including the quarterly turnover, annual turnover, shareholder information, financial status, investment situation, corporate debt ratio, number of employees, tax payment situation, number of people paying social security, and credit information of each shareholder. At the same time, the customer quality of the docking enterprises is analyzed and judged.

[0022] Preferably, the scheme formulation model building step in step 2 also includes the following:

[0023] (3) When formulating a fleet control plan, first measure and register the cargo capacity of vehicles in different fleets, and use the intelligent control terminal to record the vehicle information. The license plate of each vehicle is used as the vehicle's information data terminal. The levels of different cargo capacities are classified and marked with A, B, C and D respectively. The classified information is marked inside the vehicle's information data terminal, with Class A being the largest and Class D being the smallest. The type of vehicle is also identified. Semi-trailers are identified with English letters inside the information data terminal, vans are represented with English lowercase letters, and general trucks are identified with the number 1. The identified information is recorded inside the information data terminal. At the same time, the age of the vehicle and the number of repairs are registered and analyzed. The number of repairs for a vehicle in three years of use is twenty times, for five years of use is thirty times, and for ten years of use is fifty times as the limit value for analyzing the vehicle. The safety of the vehicle during use is judged and classified by red, yellow and green colors, with red being the lowest safety and green being the highest safety. When the judgment is completed, the color mark will be displayed on the outside of the information data terminal.

[0024] Preferably, the specific steps of constructing the route planning model in step 3 are as follows:

[0025] (1) During the transportation period, the first route, the second route, the third route and the fourth route are respectively formulated according to the area where the storage end is located. In the process of route formulation, the distance between the storage end and the main traffic artery is used for optimization, and the first route, the second route, the third route and the fourth route each include three modes of transportation, for example, the first route includes expressways, national roads and water transportation;

[0026] (2) During the route planning process, the planned route is optimized in real time by following the traffic department’s official Weibo, mini-programs and public accounts. In addition, by connecting to the Internet, the system can monitor the feedback from drivers on the road in real time and adjust the route plan as soon as possible when any abnormality is found.

[0027] Preferably, the specific steps of constructing the emergency response model in step 3 are as follows:

[0028] (1) Formulate three emergency plans, namely the first emergency plan, the second emergency plan and the third emergency plan, with the first emergency plan having the highest level and the third emergency plan having the lowest level. The first emergency plan, the second emergency plan and the third emergency plan shall be adjusted and optimized every fifteen days. After optimization, the first emergency plan, the second emergency plan and the third emergency plan shall be sent to the front-line staff and drivers. Based on the feedback from the front-line staff and drivers, the first emergency plan, the second emergency plan and the third emergency plan shall be adjusted again;

[0029] (2) During the formulation of the emergency plan, the remaining load capacity and remaining cargo space of the transport end are counted respectively. After each transport end is loaded, the loading personnel will count the data and form a database. When an abnormality occurs during transportation and the transportation needs to be adjusted, the route is calculated and the remaining tonnage and loading space are comprehensively calculated to notify the nearest transport end to handle it. When the transport end handles it, the delivery time is adjusted, and the staff will communicate with the recipient.

[0030] Compared with the prior art, the present invention has the following beneficial effects:

[0031] The present invention can improve the stability and efficiency of the transportation process by predicting the road conditions during transportation, the enterprise conditions during docking, and the transportation plan formulated in advance during the enterprise logistics transportation process. At the same time, the dual monitoring of the carrier and the driver during transportation can increase the safety during transportation. The transportation plan can also be adjusted and optimized in real time to avoid unexpected situations that may cause unsuccessful transportation, or the transportation plan is not optimized enough to reduce the transportation efficiency, and to avoid abnormalities of the carrier and the driver, and failure to discover problems in time, which may lead to unexpected situations. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 An overall structural diagram is provided for an embodiment of the present invention. DETAILED DESCRIPTION

[0033] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments 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.

[0034] See also Figure 1 The present invention provides a technical solution: an enterprise logistics transportation optimization method based on artificial intelligence, comprising the following steps:

[0035] Step 1: Based on geographic information technology and the use of transportation networks, the location of the warehouse is planned, and a warehouse distribution model is established to collect the warehouse level and data update status of the warehouse. The fleet statistics model is established to monitor the fleet's vehicle conditions and staff information, and the collected data is uploaded;

[0036] Step 2: After the warehouse information and fleet data are collected, a central control model is established to receive and process the collected data, and a comprehensive management model is established to collect enterprise logistics information, and a plan formulation model is also established;

[0037] Step 3: During the logistics transportation process, a route planning model and an emergency response model are developed respectively. The route planning model plans the transportation route, and the emergency response module handles emergencies during the transportation process.

[0038] The specific steps for constructing the warehouse distribution model in step 1 are as follows:

[0039] (1) The geographical location of the warehousing end is divided according to the distance between the location of the warehousing end and the main traffic artery. The best location is within five kilometers from the main traffic artery, the middle location is within ten kilometers from the main traffic artery, and the worst location is more than ten kilometers from the main traffic artery. The main traffic artery includes highways, national roads, expressways, water transport, railways and airport cargo. The order from high to low according to the tonnage is water transport, railways, highways, national roads, expressways and airport cargo;

[0040] (2) After the storage ends are divided into different levels, the location of each storage end is marked. The storage locations are divided into zones using A1, A2, A3, ..., and An for marking. Each storage end is modeled using virtual technology, and after modeling, the planning identification number is marked on the virtual model. A bar chart is used outside each virtual model to display the data inside the storage end, and the data is connected to each storage end in real time. When each storage end changes, the data of each storage end is updated in real time.

[0041] Steps to build a fleet statistics module are as follows:

[0042] (1) After receiving the information from the warehouse, a process scheduling plan for the loading fleet is formulated based on the time and type of goods loaded at the warehouse. The area where goods are loaded at the warehouse is modeled in three dimensions through virtual technology to form a three-dimensional virtual world. After the loading process scheduling plan is formulated, a scheduling simulation is performed inside the virtual world. If problems are found during the scheduling simulation, the scheduling process plan is modified and optimized. After the plan is optimized, it is sent to the central control model, and an emergency scheduling plan is formulated at the same time.

[0043] In the process of formulating the plan, a fleet control plan is included. The fleet control plan is formulated according to the type of goods in the loading information and the weight of the goods. At the same time, a dispatch vehicle assembly plan is formulated. After receiving the loading information, the fleet control method is formulated first. In the process of formulating the control plan according to the weight of the goods, it is found that the dispatched fleet cannot load all the goods during loading, and the excess weight of the goods cannot be loaded by a fleet. In this case, a dispatch vehicle assembly plan can be used to dispatch a truck separately for loading. After the plan is formulated, the control plan is sent to the control terminal, and the control terminal determines the number of vehicles to be used.

[0044] (2) Investigate the driver's credit and violation record within five years and three years respectively. Drivers with ten violation records within five years will not be hired, and drivers with five violation records within three years will not be hired. After loading is completed, the freight route is connected to the map software. When the freight route is compared with the route in the map software, if it is found that the road section is congested or the road is narrow due to maintenance, the route will be readjusted;

[0045] A sensor is installed at the brake position of each truck. An electronic counter is installed inside the sensor, and the sensor is connected to the external central control model. Each sensor is marked, and the number of brakes for each truck is limited according to mileage and time during driving. The number of brakes in a short period of time is also limited, such as twenty times within ten seconds and thirty times within twenty seconds. Road condition information is collected during driving. When the number of brakes in a short period of time is too many, and the number of brakes generated in the freight mileage is too many, the driver will be interviewed. If the driver who is interviewed still exhibits the above-mentioned behavior later, the driver will be stopped from driving the truck again.

[0046] The steps for building the comprehensive management module in step 2 are as follows:

[0047] (1) The procurement information, transportation time, inventory information, distribution capacity, climate of the region during transportation, road conditions during transportation, and unexpected situations of each warehouse are judged, and the storage information between each warehouse is networked, and a control plan is formulated for each warehouse. When the procurement or storage of one warehouse is abnormal, it is networked with the nearest warehouse to schedule the procurement plan and storage volume through the control plan;

[0048] (2) Carry out real-time monitoring of the regional climate at each storage end, formulate an early warning plan for each area, and connect with the Meteorological Bureau during the monitoring process. After connecting with the network, the early warning plan is optimized in real time. If an unexpected situation occurs, the early warning plan is immediately implemented for regulation.

[0049] The steps for constructing the solution formulation model in step 2 are as follows:

[0050] (1) During the transportation process, each transport end is monitored in real time, and the road conditions and driver status of the transport route are monitored and fed back during the monitoring process. When the driver is found to be driving fatigued or suffering from a sudden illness, the driver will be stopped from driving through remote control. In addition, when the road conditions are abnormal, the delivery time of the goods will be flexibly adjusted;

[0051] (2) During the transportation process, the comprehensive information of the cooperative enterprises is integrated, including the quarterly turnover, annual turnover, shareholder information, financial status, investment situation, corporate debt ratio, number of employees, tax payment situation, number of people paying social security, and credit information of each shareholder. At the same time, the customer quality of the docking enterprises is analyzed and judged.

[0052] The steps of constructing the solution model in step 2 also include the following:

[0053] (3) When formulating a fleet control plan, first measure and register the cargo capacity of vehicles in different fleets, and use the intelligent control terminal to record the vehicle information. The license plate of each vehicle is used as the vehicle's information data terminal. The levels of different cargo capacities are classified and marked with A, B, C and D respectively. The classified information is marked inside the vehicle's information data terminal, with Class A being the largest and Class D being the smallest. The type of vehicle is also identified. Semi-trailers are identified with English letters inside the information data terminal, vans are represented with English lowercase letters, and general trucks are identified with the number 1. The identified information is recorded inside the information data terminal. At the same time, the age of the vehicle and the number of repairs are registered and analyzed. The number of repairs for a vehicle in three years of use is twenty times, for five years of use is thirty times, and for ten years of use is fifty times as the limit value for analyzing the vehicle. The safety of the vehicle during use is judged and classified by red, yellow and green colors, with red being the lowest safety and green being the highest safety. When the judgment is completed, the color mark will be displayed on the outside of the information data terminal.

[0054] The specific steps for building the route planning model in step 3 are as follows:

[0055] (1) During the transportation period, the first route, the second route, the third route and the fourth route are respectively formulated according to the area where the storage end is located. In the process of route formulation, the distance between the storage end and the main traffic artery is used for optimization, and the first route, the second route, the third route and the fourth route each include three modes of transportation, for example, the first route includes expressways, national roads and water transportation;

[0056] (2) During the route planning process, the planned route is optimized in real time by following the traffic department’s official Weibo, mini-programs, and public accounts. In addition, by connecting to the Internet, the real-time feedback from drivers on the road is followed. When an abnormality is found, the route plan is adjusted immediately, and the route is optimized through the path optimization algorithm. The algorithm is as follows:

[0057] D m =Map2Matrix(map);

[0058] Among them, Map is the map file that stores map information, D m is the transformed w*h matrix, D m The elements of correspond to the map information of the nodes;

[0059] The D* algorithm uses the Euclidean distance between nodes as the basis for calculating the loss between nodes. The Euclidean distance between any two nodes is calculated as follows:

[0060]

[0061] Where X N For N nodes in D m One-dimensional index into the matrix, Y N For N nodes in D m Two-bit index in the matrix;

[0062] To plan the global optimal path, the D* algorithm needs to calculate and update the global loss of each node to the target point. Each calculation first updates the h loss of the node, and then updates the k loss of the node. The loss is calculated as follows:

[0063]

[0064] Among them, N h Represents the h loss of node N, which is the loss value of the current distance between N and the target point. k Represents the k loss of node N and the global calculation of the loss value of N from the target point, is the h loss before updating, is the k loss before updating.

[0065] Step 3: The specific steps for building the emergency response model are as follows:

[0066] (1) Formulate three emergency plans, namely the first emergency plan, the second emergency plan and the third emergency plan, with the first emergency plan having the highest level and the third emergency plan having the lowest level. The first emergency plan, the second emergency plan and the third emergency plan shall be adjusted and optimized every fifteen days. After optimization, the first emergency plan, the second emergency plan and the third emergency plan shall be sent to the front-line staff and drivers. Based on the feedback from the front-line staff and drivers, the first emergency plan, the second emergency plan and the third emergency plan shall be adjusted again;

[0067] (2) During the formulation of the emergency plan, the remaining load capacity and remaining cargo space of the transport end are counted respectively. After each transport end is loaded, the loading personnel will count the data and form a database. When an abnormality occurs during transportation and the transportation needs to be adjusted, the route is calculated and the remaining tonnage and loading space are comprehensively calculated to notify the nearest transport end to handle it. When the transport end handles it, the delivery time is adjusted, and the staff will communicate with the recipient.

[0068] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0069] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. An enterprise logistics and transportation optimization method based on artificial intelligence, characterized in that: The following steps are involved: Step 1: Based on geographic information technology and the use of transportation networks, the location of the warehouse is planned, and a warehouse distribution model is established to collect the warehouse level and data update status of the warehouse. The fleet statistics model is established to monitor the fleet's vehicle conditions and staff information, and the collected data is uploaded; Step 2: After the warehouse information and fleet data are collected, a central control model is established to receive and process the collected data, and a comprehensive management model is established to collect enterprise logistics information, and a plan formulation model is also established; Step 3: During the logistics transportation process, a route planning model and an emergency response model are developed respectively. The route planning model plans the transportation route, and the emergency response module handles emergencies during the transportation process.

2. According to claim 1, the enterprise logistics and transportation optimization method based on artificial intelligence is characterized by: The specific steps for constructing the warehouse distribution model in step 1 are as follows: (1) The geographical location of the warehousing end is divided according to the distance between the location of the warehousing end and the main traffic artery. The distance within five kilometers from the main traffic artery is the best, the distance within ten kilometers from the main traffic artery is medium, and the distance beyond ten kilometers from the main traffic artery is the worst. The warehousing end is ranked from high to low according to the tonnage carried, namely water transport, railway, highway, national highway, expressway and airport freight; (2) After the storage ends are divided into different levels, the location of each storage end is marked. The storage locations are divided into zones using A1, A2, A3, ..., and An for marking. Each storage end is modeled using virtual technology, and after modeling, the planning identification number is marked on the virtual model. A bar chart is used outside each virtual model to display the data inside the storage end, and the data is connected to each storage end in real time. When each storage end changes, the data of each storage end is updated in real time.

3. The enterprise logistics and transportation optimization method based on artificial intelligence according to claim 1 is characterized by: Steps to build a fleet statistics module are as follows: (1) After receiving the information from the warehouse, a process scheduling plan for the loading fleet is formulated based on the time and type of goods loaded at the warehouse. The area where goods are loaded at the warehouse is modeled in three dimensions through virtual technology to form a three-dimensional virtual world. After the loading process scheduling plan is formulated, a scheduling simulation is performed inside the virtual world. If problems are found during the scheduling simulation, the scheduling process plan is modified and optimized. After the plan is optimized, it is sent to the central control model, and an emergency scheduling plan is formulated at the same time. (2) Investigate the driver's credit and violation record within five years and three years respectively. Drivers with ten violation records within five years will not be hired, and drivers with five violation records within three years will not be hired. After loading is completed, the freight route will be connected to the map software. When the freight route is compared with the route in the map software and it is found that the road section is congested or the road is narrow due to maintenance, the route will be readjusted.

4. The enterprise logistics and transportation optimization method based on artificial intelligence according to claim 1 is characterized by: The steps for building the comprehensive management module in step 2 are as follows: (1) The procurement information, transportation time, inventory information, distribution capacity, climate of the region during transportation, road conditions during transportation, and unexpected situations of each warehouse are judged, and the storage information between each warehouse is networked, and a control plan is formulated for each warehouse. When the procurement or storage of one warehouse is abnormal, it is networked with the nearest warehouse to schedule the procurement plan and storage volume through the control plan; (2) Carry out real-time monitoring of the regional climate at each storage end, formulate an early warning plan for each area, and connect with the Meteorological Bureau during the monitoring process. After connecting with the network, the early warning plan is optimized in real time. If an unexpected situation occurs, the early warning plan is immediately implemented for regulation.

5. The enterprise logistics and transportation optimization method based on artificial intelligence according to claim 1 is characterized by: The steps for constructing the solution formulation model in step 2 are as follows: (1) During the transportation process, each transport end is monitored in real time, and the road conditions and driver status of the transport route are monitored and fed back during the monitoring process. When the driver is found to be driving fatigued or suffering from a sudden illness, the driver will be stopped from driving through remote control. In addition, when the road conditions are abnormal, the delivery time of the goods will be flexibly adjusted; (2) During the transportation process, the comprehensive information of the cooperative enterprises is integrated, including the quarterly turnover, annual turnover, shareholder information, financial status, investment situation, corporate debt ratio, number of employees, tax payment situation, number of people paying social security, and credit information of each shareholder. At the same time, the customer quality of the docking enterprises is analyzed and judged.

6. The method for optimizing enterprise logistics and transportation based on artificial intelligence according to claim 5 is characterized by: The steps of constructing the solution model in step 2 also include the following: (3) When formulating a fleet control plan, first measure and register the cargo capacity of vehicles in different fleets, and use the intelligent control terminal to record vehicle information. The license plate of each vehicle is used as the vehicle information data terminal. The levels of different cargo capacities are classified and marked with A, B, C and D respectively. The classified information is marked inside the vehicle information data terminal, with Class A being the largest and Class D being the smallest. The type of vehicle is also marked. Semi-trailers are marked with English letters inside the information data terminal, vans are marked with English lowercase letters, and general trucks are marked with the number 1. The marked information is recorded inside the information data terminal. At the same time, the vehicle's age and number of repairs are registered and analyzed. The number of repairs in three years, thirty times in five years, and fifty times in ten years are used as the limit values ​​for analyzing the vehicle. The safety of the vehicle during use is then judged and classified using three colors: red, yellow, and green, with red being the lowest safety and green being the highest safety. When the judgment is completed, the color will be marked on the outside of the information data terminal.

7. The enterprise logistics and transportation optimization method based on artificial intelligence according to claim 1 is characterized by: The specific steps for building the route planning model in step 3 are as follows: (1) During the transportation period, the first route, the second route, the third route and the fourth route are respectively formulated according to the area where the storage end is located, and during the route formulation process, the distance between the storage end and the main traffic artery is used for optimization, and the first route, the second route, the third route and the fourth route each include three modes of transportation; (2) During the route planning process, the planned route is optimized in real time by communicating with the transportation department. In addition, by connecting to the network, real-time feedback from drivers on the road is monitored and the route plan is adjusted immediately when any abnormality is found.

8. The enterprise logistics and transportation optimization method based on artificial intelligence according to claim 1 is characterized by: Step 3: The specific steps for building the emergency response model are as follows: (1) Formulate three emergency plans, namely the first emergency plan, the second emergency plan and the third emergency plan, with the first emergency plan having the highest level and the third emergency plan having the lowest level. The first emergency plan, the second emergency plan and the third emergency plan shall be adjusted and optimized every fifteen days. After optimization, the first emergency plan, the second emergency plan and the third emergency plan shall be sent to the front-line staff and drivers. Based on the feedback from the front-line staff and drivers, the first emergency plan, the second emergency plan and the third emergency plan shall be adjusted again; (2) During the formulation of the emergency plan, the remaining load capacity and remaining cargo space of the transport end are counted respectively. After each transport end is loaded, the loading personnel will count the data and form a database. When an abnormality occurs during transportation and the transportation needs to be adjusted, the route is calculated and the remaining tonnage and loading space are comprehensively calculated to notify the nearest transport end to handle it. When the transport end handles it, the delivery time is adjusted, and the staff will communicate with the recipient.

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