Intelligent Scheduling System and Method for Logistics Transfer Center Based on Internet of Things

Abstract

The present invention discloses an intelligent scheduling system and method for a logistics transfer center based on the Internet of Things, belonging to the technical field of logistics allocation. To solve the problems of inaccurate and untimely cargo data obtained by the logistics center and low task dispatching efficiency, the warehouse data interaction unit interacts with the warehouse management system in real time to ensure that the logistics transfer center can quickly obtain the latest cargo data. By integrating the cargo information in the transportation orders, the transportation projects are made more reasonable and efficient. Through the transfer task dispatching unit, the system can quickly determine the logistics tasks based on the transportation projects and perform accurate task dispatching. By constructing a transfer blockchain and using Internet of Things technology, the system can simultaneously obtain the information of the cargo party and the carrier, realizing the two-way matching of the task quota and the logistics vehicle information. This intelligent matching mechanism ensures that the tasks can be quickly and accurately dispatched to the appropriate carrier, improving the efficiency and accuracy of task dispatching.

Description

Technical Field

[0001] The present invention relates to the technical field of logistics distribution, and particularly to an intelligent scheduling system and method for a logistics transfer center based on the Internet of Things. Background Art

[0002] With the continuous development of industrial production and infrastructure construction levels, more and more raw materials need to be transported to corresponding locations through logistics. Logistics scheduling mainly refers to the reasonable arrangement and dispatch of the affiliated vehicles and personnel by logistics companies according to the weight, destination, specifications, urgency, etc. of the goods to be shipped during the logistics process. Good logistics scheduling by logistics companies can quickly deliver the goods entrusted by customers to the consignee in a timely and intact manner.

[0003] The following problems still exist in actual operations:

[0004] Existing warehouse management systems may not be able to interact with the logistics transfer center in real time, resulting in inaccurate and untimely cargo data obtained by the logistics center. At the same time, task distribution depends on manual allocation, with low efficiency and easy errors. Existing logistics systems may lack an intelligent matching mechanism, resulting in unreasonable or delayed task allocation. Summary of the Invention

[0005] The purpose of the present invention is to provide an intelligent scheduling system and method for a logistics transfer center based on the Internet of Things to solve the problems raised in the above background art.

[0006] To achieve the above purpose, the present invention provides the following technical solution: An intelligent scheduling system for a logistics transfer center based on the Internet of Things, including:

[0007] An information service management module, used for:

[0008] Interacting with the warehousing collaboration module, the logistics scheduling module, and the logistics monitoring module, providing a human-computer interaction interface, performing data transmission and communication with the vehicle navigation system and the warehouse management system based on the Internet of Things and Ethernet, sharing data with the vehicle navigation system and the warehouse management system, and providing a data information encryption function during the data sharing process;

[0009] A warehousing collaboration module, used for:

[0010] Interacting and docking with the warehouse management system, obtaining real-time warehouse cargo inventory, cargo inbound and outbound records, and cargo details, generating transportation projects, and at the same time, analyzing the cargo inbound and outbound records, predicting future cargo demands, and planning inventory warehouse management in advance;

[0011] A logistics scheduling module, used for:

[0012] Determine logistics tasks based on transportation projects, dispatch tasks, interact with the logistics monitoring module, obtain logistics information during the logistics transportation process, construct a logistics network, perform real-time scheduling and optimal route planning based on the logistics network. At the same time, the logistics scheduling module interacts with in-vehicle navigation devices and control systems, issues scheduling signal instructions, and automatically navigates the vehicle based on the optimal route;

[0013] The logistics monitoring module is used for:

[0014] Based on the Internet of Things, data transmission and communication are carried out between Internet of Things sensors and in-vehicle systems, and logistics information during the logistics transportation process is collected and monitored in real time. The logistics information includes vehicle location, temperature and humidity, and cargo status. At the same time, equipment failure conditions are monitored based on the health status monitoring of Internet of Things sensors and in-vehicle systems;

[0015] Among them, the logistics scheduling module performs optimal route planning, specifically:

[0016] Determine multiple transportation route information according to route planning, and obtain the theoretical transportation distance, transfer logistics point information, and transportation road information according to each transportation route information;

[0017] Evaluate the travel cost coefficient of each transportation route through a preset artificial intelligence model according to the theoretical transportation distance;

[0018] Determine the available resource ratio of each transportation route according to the transfer logistics point information;

[0019] Determine the road condition complexity, logistics speed influence index, and transportation cost coefficient of each transportation route according to the transportation road information;

[0020] Calculate the rationality index of each transportation route according to the road condition complexity, logistics speed influence index, transportation cost coefficient, travel cost coefficient, and available resource ratio of each route:

[0021] S i =θ1(F i *γ)+θ2*(0.5+M i )*(A1G i +A2D i +A3R i )

[0022] Among them, S i represents the rationality index of the i-th transportation route, θ1 represents the driving weight, F i represents the road condition complexity of the i-th transportation route, γ represents the smoothness index of road conditions under standard logistics efficiency, θ2 represents the cost weight, M i represents the available resource ratio of the i-th transportation route, A1 represents the first fuzzy weight, Gi denoted as the logistics speed impact index of the i-th transportation route, A2 denoted as the second fuzzy weight, D i denoted as the transportation cost coefficient of the i-th transportation route, A3 denoted as the third fuzzy weight, R i denoted as the travel cost coefficient of the i-th transportation route;

[0023] Select the target transportation route with the largest rationality index as the optimal route.

[0024] Furthermore, the warehousing collaboration module includes:

[0025] Warehouse data interaction unit, used for:

[0026] Interact and dock with the warehouse management system, obtain the inventory information of goods, the inbound and outbound records of goods, and the details of goods in the warehouse in real time, obtain transportation orders, match all the goods recorded in the warehouse management system with all the goods in the transportation orders, and encode and mark the successfully matched goods;

[0027] Warehouse inventory prediction unit, used for:

[0028] Obtain the historical record data of goods inbound and outbound, where the historical record data includes date, time, goods type, quantity, source, and destination, perform data preprocessing on the historical record data to eliminate outliers, missing values, and incorrect data, create a time series graph based on the historical record data, and judge the distribution, trend, and periodicity of the historical record data based on the time series graph;

[0029] Based on the distribution, trend, and periodicity of the historical record data, predict the future demand for goods, and generate an inventory warehousing management plan according to the prediction results, combined with warehousing capacity and logistics scheduling factors. The inventory warehousing management plan includes storage location adjustment, inventory structure adjustment, and procurement plan adjustment, monitor the inventory status and changes in goods demand, and adjust the inventory warehousing management plan in real time based on changes in goods demand;

[0030] Transportation project generation unit, used for:

[0031] Based on the goods encoded and marked by the warehouse data interaction unit, determine the types and quantities of goods to be transported, and generate a transportation project.

[0032] Furthermore, the generation of the transportation project, the specific process includes:

[0033] Obtain the goods information of the goods, where the goods information includes the goods type, quantity of goods, and the receiving address;

[0034] Obtain a transportation order, where the transportation order corresponds to the goods one by one. Integrate all the goods included in the transportation order and generate an item set. Generate a transportation project based on the item set and the goods information of all the goods in the item set.

[0035] Generate an item number, and each item number is a unique number. Assign the generated item number to the corresponding transportation project. Each item number corresponds to each transportation project one by one. The item number contains transfer information about the transportation project. The transfer information includes the type of goods, the quantity of goods, and the receiving address. Among them, the item number is used to distinguish and retrieve the corresponding transportation project.

[0036] Furthermore, the logistics scheduling module includes:

[0037] A transfer task dispatching unit, which is used for:

[0038] Determine the logistics task based on the transportation project and dispatch the task based on the logistics task.

[0039] A logistics transportation scheduling unit, which is used for:

[0040] Collect logistics nodes, transportation routes, tool performance, historical transportation and prediction data, establish and optimize a logistics network model, conduct route planning in combination with graph theory, obtain logistics information in real time, generate a scheduling plan, calculate the optimal route, and perform automatic navigation through in-vehicle navigation equipment.

[0041] Furthermore, the process of determining the logistics task based on the transportation project and dispatching the task based on the logistics task specifically includes:

[0042] Obtain the project to be transported, read the project to be transported, and determine the transportation plan of the project to be transported. Among them, there is at least one project to be transported, and the transportation plan includes the transfer order of the project to be transported, the type of goods, the quantity of goods, and the number of transportation vehicles corresponding to the quantity of goods.

[0043] Analyze the transportation plan, determine the priority of the project to be transported, and create a logistics task based on the priority for the project.

[0044] When performing the project to create a logistics task, determine the transfer requirements corresponding to the project to be transported based on the attribute information of the project to be transported, and create task quotas based on the transfer requirements. Among them, there is at least one task quota.

[0045] Build a transfer blockchain based on the task quotas, obtain the IP addresses of the goods party and the carrier simultaneously through the Internet of Things, and create a matching link.

[0046] Based on the matching link, the task quota and quota requirements are bidirectionally matched with the logistics vehicle information of the carrier in the transfer blockchain. After successful matching, the logistics task is dispatched to the logistics vehicle of the matched carrier, and the quota matching progress of the task quota is synchronized based on the matching result and task dispatch situation;

[0047] Based on the data synchronization result, determine the matching completion index of the task quota. When the completion index is equal to the preset task quota quantity, complete the dispatching task of the task quota.

[0048] Further, the logistics transportation scheduling unit further includes the following steps:

[0049] Obtain the logistics nodes and transportation route information related to the logistics task. Among them, the logistics nodes include warehouses, distribution centers, and transfer stations. Obtain the performance data of the transportation tools in the logistics task, and obtain the historical transportation data and demand forecast data in the logistics task;

[0050] Based on the logistics nodes, transportation route information, performance data, historical transportation data, and demand forecast data, establish a logistics network model, and use graph theory to construct a network model in combination with transportation costs, time, distance, capacity limitations, and traffic conditions;

[0051] Interact with the logistics monitoring module and obtain the logistics information during the logistics transportation process. Extract the real-time data in the logistics information, generate a scheduling plan based on the real-time data and forecast data. The scheduling plan includes the selection of transportation tools, transportation route planning, and transportation time arrangement, and calculate the optimal route based on the scheduling plan;

[0052] Based on sending the optimal route data to the in-vehicle navigation device, the in-vehicle navigation device performs automatic navigation according to the received optimal route data.

[0053] Further, the logistics monitoring module includes:

[0054] A real-time collection unit, used for:

[0055] Based on the Internet of Things, collect logistics information in real time. Among them, the real-time collection module includes a temperature sensor, a humidity sensor, a light sensor, an inertial sensor, and a Beidou positioning unit. The temperature sensor, humidity sensor, light sensor, inertial sensor, and Beidou positioning unit are all arranged inside the logistics vehicle;

[0056] A fault monitoring unit, used for:

[0057] Based on the continuous collection of the operation data of vehicle equipment by Internet of Things sensors and in-vehicle systems, the operation data includes temperature, humidity, vibration and pressure, and the operation data is transmitted in real time through the Internet of Things. The health status of the equipment is evaluated based on the operation data, and the monitoring thresholds of the operation data are set. The monitoring thresholds include temperature range, humidity range, vibration amplitude and pressure range. The abnormal conditions of the operation data are judged based on the monitoring thresholds. When the operation data exceeds or is lower than the range of the monitoring thresholds, it is determined that abnormal operation data appears, and it is judged that the equipment is in an abnormal working state. The fault monitoring unit immediately triggers the warning mechanism and notifies the personnel to repair and maintain the equipment by means of SMS, email, and APP push. At the same time, the system records the process and results of the fault handling and outputs the fault log;

[0058] The in-vehicle system unit is used for:

[0059] Data reception and transmission, receiving the real-time logistics information data collected by the real-time collection unit, sending the real-time logistics information data to the information service management module based on the Ethernet, and at the same time receiving the scheduling signal instructions sent by the logistics scheduling module.

[0060] Furthermore, analyze the transportation plan, determine the priority of the items to be transported, and execute the project to create logistics tasks based on the priority, including:

[0061] Determine the main body parameters of the transported items and the main body parameters of the participating personnel according to the transportation plan;

[0062] Establish a direct current linear model of manpower scheduling for each item to be transported based on the main body parameters of the transported items and the main body parameters of the participating personnel;

[0063] Obtain the scheduling object entries for each item to be transported based on the direct current linear model of manpower scheduling, and obtain the delay-related factors of each scheduling object;

[0064] Determine the logistics delay data characteristics according to the delay-related factors of each scheduling object;

[0065] Determine the logistics chain calibration parameters for each item to be transported according to the transportation plan, and determine the influence index of the parameters of the logistics chain calibration for this transportation project according to the logistics delay data characteristics of the scheduling objects of each item to be transported;

[0066] Determine the priority of the items to be transported according to the influence index;

[0067] Determine the order of logistics task objects based on the priority of the items to be transported and create initial logistics tasks in sequence;

[0068] Obtain the logistics target parameters for each item to be transported, and determine multiple logistics decision-making indicators according to the logistics target parameters;

[0069] Determine the scheduling resource parameters for each logistics decision-making indicator, and select the same scheduling resource parameters during the same time period according to the initial logistics tasks;

[0070] Conduct a conflict assessment on the same scheduling resource parameters, adjust the initial logistics tasks according to the assessment results, and obtain the target logistics tasks;

[0071] Take the target logistics tasks of each item to be transported as the final logistics tasks.

[0072] Another technical problem to be solved by the present invention is to provide a method for an intelligent scheduling system of a logistics transfer center based on the Internet of Things, including the following steps:

[0073] Warehouse collaboration. The warehouse collaboration module obtains the goods inventory, inbound and outbound records, and goods details in real time from the warehouse management system. Based on the obtained data, the warehouse collaboration module generates transportation projects and determines the goods to be transported in the transportation projects;

[0074] Task dispatch. Based on the generated transportation projects, determine the logistics tasks and perform task dispatch;

[0075] Logistics scheduling. The logistics scheduling module interacts with the logistics monitoring module to obtain real-time logistics information, constructs a logistics network, and performs real-time scheduling and optimal route planning. The logistics scheduling module interacts with in-vehicle navigation equipment and control systems, sends scheduling signal instructions, and automatically navigates based on the optimal route;

[0076] Logistics monitoring. The logistics monitoring module continuously collects and monitors various information during the logistics transportation process, and the monitoring module feeds back the real-time information to the information service management module.

[0077] Compared with the prior art, the beneficial effects of the present invention are:

[0078] 1. The warehouse data interaction unit of the present invention interacts with the warehouse management system in real time to ensure that the logistics transfer center can quickly obtain the latest goods inventory information, inbound and outbound records, and goods details, and obtain accurate and error-free goods data. The transportation project generation unit can quickly determine the types and quantities of goods to be transported based on the encoded goods information, and generate corresponding transportation projects, simplifying the generation process of transportation projects. Moreover, by integrating the goods information in the transportation orders, the transportation projects are made more reasonable and efficient. By generating a unique project number and corresponding the project number to the transportation project one by one, it is convenient to distinguish and retrieve the transportation projects.

[0079] 2. Through the transfer task dispatching unit, the system can quickly determine logistics tasks based on transportation projects and perform accurate task dispatching, greatly reducing the time and labor costs of task allocation, improving the efficiency of logistics operations. By constructing a transfer blockchain and using Internet of Things technology, the system can simultaneously obtain information from both the cargo side and the carrier side, achieving two-way matching of task quotas and logistics vehicle information. This intelligent matching mechanism ensures that tasks can be quickly and accurately dispatched to the appropriate carrier, improving the efficiency and accuracy of task dispatching.

[0080] 3. By comprehensively considering logistics nodes, transportation routes, tool performance, historical transportation data, and demand forecasting data, this solution can more accurately establish a logistics network model and generate a scheduling plan based on this model, helping to reduce transportation time, lower costs, and improve overall logistics efficiency. Combining graph theory for route planning can ensure that the generated route is optimal, that is, considering transportation costs, time, distance, capacity limitations, and real-time traffic conditions. The interaction with the logistics monitoring module enables the logistics transportation scheduling unit to obtain real-time logistics information, thereby timely adjusting the scheduling plan, helping to ensure the smooth progress of the logistics process and cope with various emergencies. BRIEF DESCRIPTION OF THE DRAWINGS

[0081] Figure 1 is the schematic diagram of the modules of the intelligent scheduling system for the logistics transfer center based on the Internet of Things of the present invention;

[0082] Figure 2 is the schematic diagram of the intelligent scheduling process of the logistics transfer center based on the Internet of Things of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0083] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0084] To solve the technical problems that the warehouse management system may not be able to interact with the logistics transfer center in real time, resulting in inaccurate and untimely cargo data obtained by the logistics center, and at the same time, task dispatching depends on manual allocation, with low efficiency and prone to errors, and the existing logistics system may lack an intelligent matching mechanism, resulting in unreasonable or delayed task allocation, please refer to Figure 1-2 , the present invention provides the following technical solutions:

[0085] An intelligent scheduling system for a logistics transfer center based on the Internet of Things, comprising:

[0086] An information service management module, for:

[0087] Interact with the warehousing collaboration module, logistics scheduling module, and logistics monitoring module, provide a human-machine interaction interface, conduct data transmission and communication with the vehicle navigation system and warehouse management system based on the Internet of Things and Ethernet network, share data with the vehicle navigation system and warehouse management system, and provide a data information encryption function during the data sharing process;

[0088] The warehousing collaboration module is used for:

[0089] Interact and dock with the warehouse management system, obtain the inventory of warehouse goods, goods in and out records, and goods details in real time, generate transportation projects, and at the same time, analyze the goods in and out records, predict future goods demands, and plan inventory warehousing management in advance;

[0090] The logistics scheduling module is used for:

[0091] Determine logistics tasks based on transportation projects and dispatch tasks, interact with the logistics monitoring module, obtain logistics information during the logistics transportation process, construct a logistics network, conduct real-time scheduling and optimal route planning based on the logistics network. At the same time, the logistics scheduling module interacts with in-vehicle navigation devices and control systems, sends scheduling signal instructions, and automatically navigates the vehicle based on the optimal route;

[0092] The logistics monitoring module is used for:

[0093] Conduct data transmission and communication between the Internet of Things, Internet of Things sensors, and in-vehicle systems, collect and monitor logistics information during the logistics transportation process in real time. The logistics information includes vehicle location, temperature and humidity, and goods status. At the same time, monitor equipment failure conditions based on the health status monitoring of Internet of Things sensors and in-vehicle systems.

[0094] Specifically, when the system is working, the warehousing collaboration module obtains the goods inventory, in and out records, and goods details from the warehouse management system in real time. Based on the obtained data, the warehousing collaboration module generates transportation projects, determines the goods to be transported in the transportation projects, determines logistics tasks based on the generated transportation projects, and dispatches tasks. The logistics scheduling module interacts with the logistics monitoring module, obtains real-time logistics information, constructs a logistics network, and conducts real-time scheduling and optimal route planning. The logistics scheduling module interacts with in-vehicle navigation devices and control systems, sends scheduling signal instructions, and automatically navigates based on the optimal route. The logistics monitoring module continuously collects and monitors various information during the logistics transportation process, and the monitoring module feeds back the real-time information to the information service management module.

[0095] In the above embodiments, based on data transmission and communication of Internet of Things technology, the system can obtain and analyze information such as warehouse inventory and transportation requirements in real time, so as to make optimal logistics task allocation and route planning. Through real-time collection and analysis of logistics data, the system can provide accurate and timely decision-making support for management personnel, help improve the logistics operation process and service quality. The logistics scheduling module can automatically navigate vehicles based on the optimal route, reducing manual intervention and improving the automation and intelligence level of logistics transfer. Through data sharing with external systems such as vehicle navigation systems and warehouse management systems, the system realizes effective integration and sharing of information, improving the transparency and collaborative efficiency of logistics transfer.

[0096] The warehousing collaboration module includes:

[0097] The warehouse data interaction unit is used for:

[0098] Interact and dock with the warehouse management system to obtain the goods inventory information, goods inbound and outbound records, and goods details of the warehouse in real time, obtain transportation orders, match all the goods recorded in the warehouse management system with all the goods in the transportation orders, and encode and mark the successfully matched goods;

[0099] The warehousing inventory prediction unit is used for:

[0100] Obtain the historical record data of goods inbound and outbound, where the historical record data includes date, time, goods type, quantity, source, and destination. Perform data preprocessing on the historical record data to eliminate outliers, missing values, and incorrect data. Create a time series graph based on the historical record data, and judge the distribution, trend, and periodicity of the historical record data based on the time series graph;

[0101] Based on the distribution, trend, and periodicity of the historical record data, predict the future goods demand. According to the prediction results, combined with warehousing capacity and logistics scheduling factors, generate an inventory warehousing management plan, which includes storage location adjustment, inventory structure adjustment, and procurement plan adjustment. Monitor the inventory status and changes in goods demand, and adjust the inventory warehousing management plan in real time based on changes in goods demand;

[0102] The transportation project generation unit is used for:

[0103] Based on the goods encoded and marked by the warehouse data interaction unit, determine the types and quantities of goods to be transported and generate a transportation project.

[0104] Generate a transportation project, and its specific process includes:

[0105] Obtain the goods information of the goods, where the goods information includes the goods type, quantity of the goods, and the receiving address;

[0106] Obtain a transportation order, where the transportation order corresponds to the goods one by one. Integrate all the goods included in the transportation order and generate an item set, and generate a transportation project based on the item set and the goods information of all the goods in the item set;

[0107] Generate an item number, each item number is a unique number, assign the generated item number to the corresponding transportation project, each item number corresponds to each transportation project one by one, and the item number contains the transshipment information of the transportation project. The transshipment information includes the goods type, the quantity of goods, and the receiving address. Among them, the item number is used to distinguish and retrieve the corresponding transportation project.

[0108] In the above embodiment, the warehouse data interaction unit interacts with the warehouse management system in real time to ensure that the logistics transshipment center can quickly obtain the latest goods inventory information, inbound and outbound records, and goods details, and obtain accurate goods data. At the same time, matching and coding marks are made for the transportation order and the warehouse goods, further ensuring the accuracy and reliability of the data, and providing a solid foundation for the generation of subsequent transportation projects.

[0109] In the above embodiment, based on the coded goods information, the transportation project generation unit can quickly determine the goods type and quantity to be transported and generate the corresponding transportation project, simplifying the generation process of the transportation project. Moreover, by integrating the goods information in the transportation order, the transportation project is made more reasonable and efficient. By generating a unique item number and corresponding the item number to the transportation project one by one, it is convenient to distinguish and retrieve the transportation project.

[0110] In the above embodiment, by obtaining detailed historical records of goods inbound and outbound, and using visualization tools such as time series diagrams to analyze the distribution, trend, and periodicity of the data, the future goods demand can be predicted more accurately. Based on the prediction results, the system can generate targeted inventory warehousing management plans, including storage location adjustment, inventory structure adjustment, and procurement plan adjustment, which helps to improve warehousing efficiency, reduce unnecessary handling and operation costs, and at the same time ensure that the goods can meet customer needs in a timely and accurate manner. At the same time, the system can monitor the inventory status and changes in goods demand in real time, and adjust the inventory warehousing management plan in real time based on these changes. This ability of dynamic adjustment enables the system to quickly respond to emergencies or demand changes and maintain the stable operation of the logistics transshipment center.

[0111] The logistics scheduling module includes:

[0112] The transshipment task dispatching unit is used for:

[0113] Determine the logistics task based on the transportation project and dispatch the task based on the logistics task;

[0114] A logistics transportation scheduling unit, configured to:

[0115] Collect logistics node, transportation route, tool performance, historical transportation and prediction data, establish and optimize a logistics network model, conduct route planning in combination with graph theory, obtain logistics information in real time, generate a scheduling plan, calculate the optimal route, and perform automatic navigation through in-vehicle navigation equipment.

[0116] Determine logistics tasks based on transportation projects, and perform task distribution based on the logistics tasks. The specific process includes:

[0117] Obtain the project to be transported, read the project to be transported, and determine the transportation plan of the project to be transported. Wherein, the project to be transported is at least one, and the transportation plan includes the transfer order of the project to be transported, the types of goods, the quantity of goods, and the number of transportation vehicles corresponding to the quantity of goods;

[0118] Analyze the transportation plan, determine the priority of the project to be transported, and create logistics tasks based on the priority to execute the project;

[0119] When executing the project to create logistics tasks, determine the transfer requirements corresponding to the project to be transported based on the attribute information of the project to be transported, and create task quotas based on the transfer requirements. Wherein, the task quotas are at least one;

[0120] Construct a transfer blockchain based on the task quotas, obtain the IP addresses of the goods party and the carrier simultaneously through the Internet of Things, and create a matching link;

[0121] Based on the matching link, perform two-way matching of the task quotas and quota requirements with the logistics vehicle information of the carrier in the transfer blockchain. After successful matching, dispatch the logistics tasks to the logistics vehicles of the matched carrier, and synchronize the data of the quota matching progress of the task quotas based on the matching results and task dispatch situations;

[0122] Determine the matching completion index of the task quotas based on the data synchronization results, and when the completion index is equal to the preset number of task quotas, complete the task dispatch of the task quotas.

[0123] In the above embodiment, through the transfer task dispatch unit, the system can quickly determine logistics tasks based on transportation projects and perform accurate task dispatch, greatly reducing the time and labor costs of task allocation and improving the efficiency of logistics operations.

[0124] In the above embodiments, during the task distribution process, the system can analyze the priority of the transportation plan and create logistics tasks according to the priority to ensure that high-priority tasks can be processed first, thus meeting the needs and expectations of different customers.

[0125] In the above embodiments, by constructing a transfer blockchain and using Internet of Things technology, the system can simultaneously obtain information of the cargo party and the carrier party, realize the two-way matching of task quotas and logistics vehicle information. This intelligent matching mechanism ensures that tasks can be quickly and accurately assigned to the appropriate carrier, improving the efficiency and accuracy of task distribution. The system can synchronize the matching progress of task quotas in real time and determine the matching completion index of task quotas according to the data synchronization result, which helps managers monitor the task distribution situation in real time, discover and solve problems in time, and ensure the smooth completion of logistics tasks.

[0126] The logistics transportation scheduling unit further includes the following steps:

[0127] Obtain logistics node and transportation route information related to the logistics task. Among them, the logistics nodes include warehouses, distribution centers, and transfer stations. Obtain the performance data of the transportation tools in the logistics task, and obtain the historical transportation data and demand forecast data in the logistics task;

[0128] Based on the logistics nodes, transportation route information, performance data, historical transportation data, and demand forecast data, establish a logistics network model, and use graph theory to construct the network model in combination with transportation costs, time, distance, capacity limitations, and traffic conditions;

[0129] Interact with the logistics monitoring module and obtain logistics information during the logistics transportation process. Extract real-time data from the logistics information, generate a scheduling plan according to the real-time data and forecast data. The scheduling plan includes the selection of transportation tools, transportation route planning, and transportation time arrangement, and calculate the optimal route based on the scheduling plan;

[0130] Based on sending the optimal route data to the in-vehicle navigation device, the in-vehicle navigation device performs automatic navigation according to the received optimal route data.

[0131] In the above embodiments, by comprehensively considering logistics nodes, transportation routes, tool performance, historical transportation data, and demand forecast data, this solution can more accurately establish a logistics network model and generate a scheduling plan based on this model, which helps to reduce transportation time, lower costs, and improve overall logistics efficiency. Combining graph theory for route planning can ensure that the generated route is optimal, that is, considering transportation costs, time, distance, capacity limitations, and real-time traffic conditions. In addition, by obtaining logistics information in real time and generating a scheduling plan according to real-time data and forecast data, the decision-making becomes more intelligent and real-time.

[0132] In the above embodiments, the interaction with the logistics monitoring module enables the logistics transportation scheduling unit to obtain real-time logistics information, thereby timely adjusting the scheduling plan, which helps to ensure the smooth progress of the logistics process and cope with various emergencies. Through the automatic navigation function of the in-vehicle navigation device, the driver can focus more on driving, reduce human errors, and thus improve transportation safety. At the same time, the real-time monitoring of logistics information also helps to detect and handle potential safety risks in a timely manner.

[0133] The logistics monitoring module includes:

[0134] The real-time acquisition unit is used for:

[0135] Based on the Internet of Things, it acquires logistics information in real time. Among them, the real-time acquisition module includes a temperature sensor, a humidity sensor, a light sensor, an inertial sensor, and a Beidou positioning unit. The temperature sensor, humidity sensor, light sensor, inertial sensor, and Beidou positioning unit are all arranged inside the logistics vehicle;

[0136] The fault monitoring unit is used for:

[0137] Based on the Internet of Things sensors and the vehicle system, it continuously acquires the operation data of the vehicle equipment. The operation data includes temperature, humidity, vibration, and pressure, and transmits the operation data in real time through the Internet of Things. It evaluates the health status of the equipment based on the operation data, sets the monitoring threshold of the operation data. The monitoring threshold includes a temperature range, a humidity range, a vibration amplitude, and a pressure range. It judges the abnormal situation of the operation data based on the monitoring threshold. When the operation data exceeds or is lower than the range of the monitoring threshold, it is determined that abnormal operation data appears, and it is judged that the equipment is in an abnormal working state. The fault monitoring unit immediately triggers an early warning mechanism and notifies the personnel to repair and maintain the equipment by means of text messages, emails, and APP push. At the same time, the system records the fault handling process and results and outputs a fault log;

[0138] The vehicle system unit is used for:

[0139] Data reception and transmission, receiving the real-time logistics information data collected by the real-time acquisition unit, sending the real-time logistics information data to the information service management module based on the Ethernet, and at the same time receiving the scheduling signal instructions sent by the logistics scheduling module.

[0140] In the above embodiments, through the real-time acquisition unit, this module can collect logistics information in real time based on Internet of Things technology, including temperature, humidity, light, inertial data, and location information, etc. The real-time acquisition module integrates various sensors such as temperature sensors, humidity sensors, light sensors, inertial sensors, and Beidou positioning units. These sensors can comprehensively and accurately reflect the environmental state inside the logistics vehicle and the driving conditions of the vehicle, providing rich basic data for subsequent data analysis and decision-making.

[0141] In the above embodiments, the fault monitoring unit can collect the operation data of vehicle equipment in real time based on Internet of Things sensors and in-vehicle systems, enabling the system to continuously monitor the working state of vehicle equipment. By setting monitoring thresholds, the system can immediately trigger an early warning mechanism when abnormal operation data occurs in the equipment, thus avoiding the occurrence of equipment failures or promptly responding to existing failures. This real-time monitoring and preventive maintenance strategy can significantly reduce the logistics transfer interruptions caused by equipment failures, improve the overall operation efficiency. By reducing equipment failures and interruptions, and optimizing the equipment maintenance plan, the fault monitoring unit helps to reduce the operation costs of the logistics transfer center, reduce direct equipment repair costs, and indirect costs such as logistics delays and decreased customer satisfaction caused by equipment failures.

[0142] In the above embodiments, by collecting and analyzing logistics information in real time, the logistics monitoring module can provide accurate data support for the logistics scheduling module, helping the scheduling module make more reasonable scheduling decisions.

[0143] To better demonstrate the intelligent scheduling system of the logistics transfer center based on the Internet of Things, this embodiment now proposes a method for the intelligent scheduling system of the logistics transfer center based on the Internet of Things, including the following steps:

[0144] Warehouse collaboration: The warehouse collaboration module obtains the goods inventory, inbound and outbound records, and goods details from the warehouse management system in real time. Based on the obtained data, the warehouse collaboration module generates transportation projects and determines the goods to be transported in the transportation projects;

[0145] Task distribution: Based on the generated transportation projects, determine logistics tasks and perform task distribution;

[0146] Logistics scheduling: The logistics scheduling module interacts with the logistics monitoring module to obtain real-time logistics information, constructs a logistics network, and performs real-time scheduling and optimal route planning. The logistics scheduling module interacts with in-vehicle navigation equipment and control systems, sends scheduling signal instructions, and automatically navigates based on the optimal route;

[0147] Logistics monitoring: The logistics monitoring module continuously collects and monitors various information during the logistics transportation process, and the monitoring module feeds back the real-time information to the information service management module.

[0148] In one embodiment, the transportation plan is analyzed to determine the priority of the items to be transported, and based on the priority, logistics tasks are created for the items, including:

[0149] Determine the main parameters of the transported items and the main parameters of the participating human resources according to the transportation plan;

[0150] Based on the main parameters of the transported items and the main parameters of the participating human resources, establish a direct current linear model for human resource scheduling for each item to be transported; the direct current linear model for human resource scheduling is a scheduling model used to evaluate the human resource cost of the entire project process of each transportation project, and is set up in advance. The relevant main parameters of the transported items and the main parameters of the participating human resources can be input in combination with the goals and objects of logistics scheduling, and a corresponding mapping relationship can be formed to facilitate tracking and querying.

[0151] Based on the direct current linear model for human resource scheduling, obtain the scheduling object entries for each item to be transported, and obtain the delay-related factors of each scheduling object;

[0152] Determine the logistics delay data characteristics according to the delay-related factors of each scheduling object;

[0153] Determine the logistics chain calibration parameters for each item to be transported according to the transportation plan, and determine the influence indicators of the logistics chain calibration parameters for the transportation project according to the logistics delay data characteristics of the scheduling objects of each item to be transported;

[0154] Determine the priority of the items to be transported according to the influence indicators;

[0155] Based on the priority of the items to be transported, determine the order of the logistics task objects and create initial logistics tasks in sequence;

[0156] Obtain the logistics target parameters for each item to be transported, and determine multiple logistics decision-making indicators according to the logistics target parameters;

[0157] Determine the scheduling resource parameters for each logistics decision-making indicator, and select the same scheduling resource parameters in the same time period according to the initial logistics tasks;

[0158] Conduct a conflict assessment on the same scheduling resource parameters, and adjust the initial logistics tasks according to the assessment results to obtain the target logistics tasks;

[0159] Take the target logistics tasks of each item to be transported as the final logistics tasks.

[0160] The beneficial effects of the above technical solution are as follows: By conducting priority evaluation based on the impact indicators of the calibration parameters of the logistics chain of the transportation project, it is possible to ensure that the logistics chains of other projects are not affected starting from the entire logistics chain, guarantee the normal operation of logistics, and at the same time quickly determine the logistics priority for the transportation project. Further, by intelligently adjusting the initial logistics tasks of each transportation project, the logistics efficiency can be maximized, avoiding the problem of reduced work efficiency caused by the synchronous application of logistics resource parameters, and improving the practicability and stability.

[0161] In one embodiment, calculating the optimal route specifically includes:

[0162] Determine multiple transportation route information according to the route planning, and obtain the theoretical transportation distance, transfer logistics point information, and transportation road information based on each transportation route information;

[0163] Evaluate the travel cost coefficient of each transportation route through a preset artificial intelligence model based on the theoretical transportation distance;

[0164] Determine the available resource ratio of each transportation route according to the transfer logistics point information;

[0165] Determine the road condition complexity, logistics speed impact index, and transportation cost coefficient of each transportation route according to the transportation road information;

[0166] Calculate the rationality index of each transportation route according to the road condition complexity, logistics speed impact index, transportation cost coefficient, travel cost coefficient, and available resource ratio of each route:

[0167] S i =θ1(F i *γ)+θ2*(0.5+M i )*(A1G i +A2D i +A3R i )

[0168] Among them, S i represents the rationality index of the i-th transportation route, θ1 represents the travel weight, F i represents the road condition complexity of the i-th transportation route, γ represents the smoothness index of the road condition under the standard logistics efficiency, θ2 represents the cost weight, M i represents the available resource ratio of the i-th transportation route, A1 represents the first fuzzy weight, G i represents the logistics speed impact index of the i-th transportation route, A2 represents the second fuzzy weight, D i represents the transportation cost coefficient of the i-th transportation route, A3 represents the third fuzzy weight, R iIt is expressed as the travel cost coefficient of the i-th transportation route; among them, the first fuzzy weight, the second fuzzy weight, and the third fuzzy weight refer to the calculation weights, which are preset parameters. The first fuzzy weight can be expressed as the calculation weight of the logistics speed of the i-th transportation route, the second fuzzy weight can be expressed as the calculation weight of the transportation cost of the i-th transportation route, and the third fuzzy weight can be expressed as the calculation weight of the travel cost of the i-th transportation route;

[0169] Select the target transportation route with the largest rationality index as the optimal route.

[0170] The beneficial effects of the above technical solution are as follows: By calculating the rationality index of each transportation route, the reliability of each transportation route during logistics can be comprehensively evaluated based on the transportation cost and driving cost of each transportation route, which not only ensures the logistics efficiency but also ensures the timely response to emergencies during the journey, improving the practicability and stability.

[0171] The above is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention, according to the technical solution of the present invention and its inventive concept, makes equivalent substitutions or changes, and should be covered by the protection scope of the present invention.

Claims

1. The intelligent dispatching system of logistics transfer center based on Internet of Things is characterized by: include: Information service management module, used to: Interact with the warehouse collaboration module, logistics scheduling module and logistics monitoring module, provide a human-computer interaction interface, transmit and communicate with the vehicle navigation system and warehouse management system based on the Internet of Things and Ethernet network, share data with the vehicle navigation system and warehouse management system, and provide data information encryption function during the data sharing process; Warehouse collaboration module, used for: Interact with the warehouse management system to obtain warehouse inventory, goods in and out records, and goods details in real time, and generate transportation projects. At the same time, analyze goods in and out records, predict future goods demand, and plan inventory storage management in advance; Logistics scheduling module, used for: Determine logistics tasks based on transportation projects and distribute tasks, interact with the logistics monitoring module, obtain logistics information during logistics transportation, build a logistics network, and perform real-time scheduling and optimal route planning based on the logistics network. At the same time, the logistics scheduling module interacts with the on-board navigation equipment and control system, generates scheduling signal instructions, and automatically navigates the vehicle based on the optimal route; Logistics monitoring module for: Based on data transmission and communication between the Internet of Things and the Internet of Things sensors and the vehicle-mounted system, the logistics information in the logistics transportation process is collected and monitored in real time. The logistics information includes vehicle location, temperature and humidity, and cargo status. At the same time, the health status monitoring of the Internet of Things sensors and the vehicle-mounted system is used to monitor equipment failures; Take the target logistics task of each item to be transported as the final logistics task; Among them, the logistics scheduling module performs optimal route planning, specifically: Determine multiple transport route information based on route planning, and obtain theoretical transport distance, transit logistics point information and transport road information based on each transport route information; The travel cost coefficient of each transport route is evaluated through a preset artificial intelligence model based on the theoretical transport distance; Determine the proportion of available resources for each transport route based on the information of transit logistics points; Determine the road condition complexity, logistics speed impact index and transportation cost coefficient of each transportation route based on transportation road information; The rationality index of each transport route is calculated based on the road complexity, logistics speed impact index, transportation cost coefficient, travel cost coefficient and available resource ratio of each route: in, Expressed as the rationality index of the i-th transportation route, is represented as the travel weight, It is expressed as the traffic complexity of the i-th transportation route, It is expressed as the road condition smoothness index under standard logistics efficiency. Expressed as cost weight, Expressed as the ratio of available resources of the i-th transport route, is represented as the first fuzzy weight, It is expressed as the logistics speed impact index of the i-th transportation route, Expressed as the second fuzzy weight, Expressed as the transportation cost coefficient of the i-th transportation route, Expressed as the third fuzzy weight, It is expressed as the travel cost coefficient of the i-th transport route; Select the target transport route with the largest rationality index as the optimal route; The logistics scheduling module includes: The transfer task dispatching unit is used to: Determine logistics tasks based on the transportation project, and assign tasks based on the logistics tasks; Logistics and transportation dispatching unit, used for: Collect logistics nodes, transportation routes, tool performance, historical transportation and forecast data, establish and optimize logistics network models, combine graph theory for route planning, obtain logistics information in real time, generate scheduling plans, calculate the optimal route, and perform automatic navigation through vehicle navigation equipment. Determine logistics tasks based on transportation projects and assign tasks based on the logistics tasks. The specific process includes: Acquire the item to be transported, read the item to be transported, and determine a transportation plan for the item to be transported, wherein the item to be transported is at least one, and the transportation plan includes a transshipment order, a type of goods, a quantity of goods, and a number of transport vehicles corresponding to the quantity of goods for the item to be transported; Analyze the transportation plan, determine the priority of the items to be transported, and execute the project creation logistics task based on the priority; When executing the project to create a logistics task, determining the transshipment requirements corresponding to the item to be transported based on the attribute information of the item to be transported, and creating a task quota based on the transshipment requirements, wherein the task quota is at least one; Construct a transshipment blockchain based on the task quota, obtain the IP addresses of the cargo party and the carrier at the same time through the Internet of Things, and create a matching link; Based on the matching link, the task quota and quota requirements are bidirectionally matched with the logistics vehicle information of the carrier in the transit blockchain, and after the matching is successful, the logistics task is dispatched to the logistics vehicle of the matched carrier, and the quota matching progress of the task quota is synchronized based on the matching result and the task dispatching situation; Determine a matching completion index of the task quota based on the data synchronization result, and when the matching completion index is equal to a preset number of task quotas, complete the task of dispatching the task quotas; The transportation plan is analyzed to determine the priority of the items to be transported, and the project creation logistics task is executed based on the priority, including: Determine the main parameters of the transported goods and the main parameters of the participating manpower according to the transport plan; Based on the main parameters of the transported items and the main parameters of the participating manpower, a DC linear model for manpower scheduling of each item to be transported is established; Based on the manpower scheduling DC linear model, the scheduling object entry of each item to be transported is obtained, and the delay-related factors of each scheduling object are obtained; Determine the logistics delay data characteristics based on the delay-related factors of each scheduling object; Determine the calibration parameters of the logistics chain for each item to be transported according to the transportation plan, and determine the influencing index of the parameters of the calibration of the logistics chain for each item to be transported according to the logistics delay data characteristics of the scheduling object of each item to be transported; Prioritize items to be transported based on impact indicators; Determine the order of logistics task objects based on the priority of the items to be transported and create initial logistics tasks in sequence; Obtain the logistics target parameters of each item to be transported, and determine multiple logistics decision indicators based on the logistics target parameters; Determine the scheduling resource parameters for each logistics decision indicator, and select the same scheduling resource parameters in the same period according to the initial logistics task; Conduct conflict assessment on the same scheduling resource parameters, adjust the initial logistics tasks according to the assessment results, and obtain the target logistics tasks.

2. The intelligent dispatching system for logistics transfer center based on the Internet of Things as claimed in claim 1, characterized in that: The warehousing collaboration module includes: Warehouse data interaction unit, used for: Interact with the warehouse management system to obtain the warehouse's inventory information, goods in and out records, and goods details in real time, obtain transportation orders, match all goods recorded in the warehouse management system with all goods in the transportation order, and encode and mark the successfully matched goods; Warehouse inventory forecasting unit for: Obtain historical record data of goods entering and leaving the warehouse, wherein the historical record data includes date, time, type of goods, quantity, source and destination, perform data preprocessing on the historical record data to eliminate abnormal values, missing values ​​and erroneous data, create a time series graph based on the historical record data, and judge the distribution, trend and periodicity of the historical record data based on the time series graph; Based on the distribution, trend and periodicity of historical record data, the future demand for goods is predicted. According to the prediction results, combined with storage capacity and logistics scheduling factors, an inventory management plan is generated. The inventory management plan includes storage location adjustment, inventory structure adjustment and procurement plan adjustment, monitoring inventory status and changes in goods demand, and adjusting the inventory management plan in real time based on changes in goods demand; Transport project generation unit for: Based on the goods coded and marked in the warehouse data interaction unit, determine the type and quantity of goods to be transported and generate a transportation project.

3. The intelligent dispatching system for logistics transfer center based on Internet of Things as claimed in claim 2, characterized in that: The specific process of generating the transport project includes: Obtaining product information of the goods, wherein the product information includes the type of goods, the quantity of goods, and the delivery address of the goods; Acquire a transport order, wherein the transport order corresponds to the goods one by one, integrate all the goods included in the transport order and generate a project set, and generate a transport project based on the project set and the product information of all the goods in the project set; Generate project numbers, each of which is a unique number, and assign the generated project numbers to corresponding transport items. Each project number corresponds to each transport item one by one. The project number contains the transshipment information of the transport item, and the transshipment information includes the type of goods, the quantity of goods, and the delivery address. The project number is used to distinguish and retrieve the corresponding transport item.

4. The intelligent dispatching system for logistics transfer center based on Internet of Things as claimed in claim 1, characterized in that: The logistics transportation scheduling unit further includes the following steps: Obtain information about logistics nodes and transportation routes related to logistics tasks, where logistics nodes include warehouses, distribution centers, and transfer stations; obtain performance data of transportation tools in logistics tasks; and obtain historical transportation data and demand forecast data in logistics tasks; Establish a logistics network model based on logistics nodes, transportation route information, performance data, historical transportation data and demand forecast data, and use graph theory to build the network model in combination with transportation cost, time, distance, capacity constraints and traffic conditions; Interact with the logistics monitoring module and obtain logistics information during the logistics transportation process, extract real-time data from the logistics information, generate a scheduling plan based on the real-time data and forecast data, the scheduling plan includes transportation tool selection, transportation route planning, transportation time arrangement, and calculate the optimal route based on the scheduling plan; Based on sending the optimal route data to the in-vehicle navigation device, the in-vehicle navigation device performs automatic navigation according to the received optimal route data.

5. The intelligent dispatching system for logistics transfer center based on Internet of Things as claimed in claim 1, characterized in that: The logistics monitoring module includes: Real-time acquisition unit for: Collect logistics information in real time based on the Internet of Things, where the real-time collection module includes a temperature sensor, a humidity sensor, a light sensor, an inertial sensor and a Beidou positioning unit, and the temperature sensor, humidity sensor, light sensor, inertial sensor and Beidou positioning unit are all set inside the logistics vehicle; On-board system unit for: Data reception and transmission, receiving real-time logistics information data collected by the real-time collection unit, sending the real-time logistics information data to the information service management module based on the Ethernet network, and receiving the scheduling signal instructions sent by the logistics scheduling module.

6. The intelligent dispatching system for logistics transfer center based on Internet of Things as claimed in claim 5, characterized in that: The logistics monitoring module also includes: Fault monitoring unit for: Based on the Internet of Things sensors and the vehicle-mounted system, the operating data of the vehicle equipment is continuously collected, and the operating data includes temperature, humidity, vibration and pressure. The operating data is transmitted in real time through the Internet of Things, and the health status of the equipment is evaluated based on the operating data. The operating data monitoring threshold is set, and the monitoring threshold includes temperature range, humidity range, vibration amplitude and pressure range. The abnormal situation of the operating data is judged based on the monitoring threshold. When the operating data exceeds or falls below the range of the monitoring threshold, it is determined that abnormal operating data has occurred, and the equipment is judged to be in an abnormal working state. The fault monitoring unit immediately triggers the early warning mechanism and notifies the personnel to inspect and maintain the equipment through SMS, email, and APP push. At the same time, the system records the fault handling process and results and outputs the fault log.

7. A method for implementing an intelligent dispatching system for a logistics transfer center based on the Internet of Things according to any one of claims 1 to 6, characterized in that: The steps include: Warehousing collaboration: The warehousing collaboration module obtains the inventory, inbound and outbound records and cargo details from the warehouse management system in real time. Based on the acquired data, the warehousing collaboration module generates a transportation project and determines the cargo that needs to be transported in the transportation project. Task dispatching: determining logistics tasks based on generated transportation items and dispatching tasks; Logistics dispatching: the logistics dispatching module interacts with the logistics monitoring module to obtain real-time logistics information, build a logistics network, and perform real-time dispatching and optimal route planning. The logistics dispatching module interacts with the on-board navigation equipment and control system, sends dispatching signal instructions, and automatically navigates based on the optimal route. Logistics monitoring, the logistics monitoring module continuously collects and monitors various information during the logistics transportation process, and the monitoring module feeds back real-time information to the information service management module.

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