Real-time loading and intelligent internet-of-things system for commercial transport vehicle

Abstract

The invention discloses a commercial transport vehicle real-time load and intelligent Internet of Things system, and particularly relates to the technical field of load monitoring and intelligent Internet of Things of commercial transport vehicles. The load measurement and data acquisition module is used for measuring vehicle load information in real time and collecting related data; the data processing and storage module is used for processing, converting and storing the collected data; and the wireless communication and transmission module is used for realizing wireless transmission of load and position information and ensuring that data can be uploaded to a management platform in real time. By adopting the high-precision load sensor and a multi-point measurement mode, the precision of load measurement is remarkably improved, it is ensured that the load change of the vehicle can be accurately monitored, and the system achieves real-time collection and transmission of the load information of the vehicle through the intelligent terminal and the communication module, so that a logistics enterprise can obtain the load condition of the vehicle in time, and the logistics efficiency is improved. Therefore, the efficiency and safety of logistics transportation are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of load monitoring and intelligent Internet of Things for commercial transport vehicles, and particularly to a real-time load and intelligent Internet of Things system for commercial transport vehicles. Background Art

[0002] In the modern logistics and transportation industry, the load management of commercial transport vehicles is an important part of ensuring transportation efficiency and safety. With the development of global trade and e-commerce, logistics enterprises are facing increasing transportation demands and increasingly complex logistics networks. To remain competitive, enterprises need to optimize every link in the transportation process, thereby improving efficiency, reducing costs, and ensuring the safety of the transportation process.

[0003] In the field of commercial transportation, traditional load measurement methods have a series of problems, mainly manifested in low accuracy, poor real-time performance, and difficulty in remote monitoring: 1. Traditional load measurement devices usually have low accuracy and are easily affected by vehicle movement and environmental factors, unable to provide accurate real-time weight data, which may cause the vehicle to operate under overloaded or uneven load conditions, increasing the risks of traffic accidents and equipment wear; 2. Existing systems usually lack real-time communication and data transmission capabilities, making it difficult for logistics enterprises to obtain the load information of vehicles in a timely manner and unable to quickly respond to changes in the transportation process to make effective scheduling and loading decisions. This lagging information feedback not only affects logistics efficiency but also may lead to waste of resources and an increase in operational risks; 3. Traditional load management systems are often isolated and lack the ability to integrate with other logistics management tools, making it difficult to comprehensively analyze and optimize multi-dimensional data such as the load condition, driving route, and transportation time of vehicles, which limits the enterprise's ability to optimize transportation routes, improve loading efficiency, and reduce operating costs. To solve these problems, therefore, we provide a real-time load and intelligent Internet of Things system for commercial transport vehicles. Summary of the Invention

[0004] The purpose of the present invention is to solve the deficiencies existing in the prior art and propose a real-time load and intelligent Internet of Things system for commercial transport vehicles.

[0005] To achieve the above purpose, the present invention adopts the following technical solutions:

[0006] A real-time load capacity and intelligent Internet of Things system for commercial transport vehicles, comprising a load measurement and data acquisition module responsible for measuring the vehicle load information in real time and collecting relevant data, a data processing and storage module for processing, converting and storing the collected data, a wireless communication and transmission module for realizing the wireless transmission of load and position information to ensure that the data can be uploaded to the management platform in real time, and a logistics management and decision support module for analyzing and processing the received data to provide decision support such as optimized scheduling, cargo stowage and route planning for logistics operations;

[0007] The load measurement and data acquisition module includes a vehicle load sensing module for installing high-precision sensors on the vehicle suspension or axle to measure the load in real time, a multi-point data fusion module for fusing measurement data by installing multiple sensors at different positions using algorithms, a data filtering and amplification module for filtering and amplifying the sensor signals, and an A / D data conversion module for converting analog signals into digital signals;

[0008] The data processing and storage module includes an embedded data processing module for processing and calculating the collected data using an embedded system, a local data storage module for storing the processed data in a smart terminal, a data encryption and security module for encrypting the data, and a vehicle positioning and status monitoring module for obtaining the vehicle position and monitoring the vehicle operation status using the GPS or Beidou system.

[0009] The present invention is further configured as: the wireless communication and transmission module includes a communication device integration module for integrating 4G / 5G / NB-IoT modules to realize wireless data transmission, a signal enhancement and optimization module for signal enhancement and optimization through antenna design and signal optimization technologies, a network connection and configuration module for configuring the network connection parameters of the communication module, and a two-way data transmission module for realizing data upload and instruction issuance and supporting real-time interaction;

[0010] The logistics management and decision support module includes a cloud data calculation module for receiving and processing data using cloud computing technology, a big data analysis module for analyzing the load data and position data to generate reports and charts, a vehicle scheduling and optimization module for optimizing vehicle scheduling and transportation tasks according to the analysis results, a path planning and navigation module for planning the optimal transportation route in combination with real-time traffic information and vehicle status, and an alarm and monitoring module for monitoring the vehicle status in real time to provide abnormal alarm and handling suggestions.

[0011] The present invention is further configured such that: the vehicle positioning and status monitoring module includes a multi-source positioning fusion module for integrating GPS, Beidou, and Wi-Fi positioning for multi-source data fusion, a vehicle inertial navigation prediction module for calculating the vehicle position using an inertial navigation system in case of weak or lost signals, a real-time load monitoring module for monitoring the vehicle load change in real time through a load sensor, an environment perception and dynamic adjustment module for perceiving the surrounding environment using camera or lidar technology to adjust the vehicle status monitoring parameters, a status analysis and determination module for analyzing the vehicle status data to determine whether the vehicle is in a normal operating state, a load anomaly determination module for determining whether the load exceeds the rated load or shows abnormal fluctuations, an intelligent feedback and adjustment module for adjusting the vehicle operating parameters in real time according to the results of the determination module, an abnormal data comparison module for comparing the abnormal data threshold with the current vehicle status data, an abnormal data threshold module for storing the system preset abnormal data threshold, and an abnormal event response module for automatically generating an event report and notifying relevant personnel when an anomaly is detected.

[0012] The present invention is further configured such that: the vehicle inertial navigation prediction module uses the vehicle position data to supplement the positioning ability of the multi-source positioning fusion module in case of weak signals; the real-time load monitoring module provides the load data in real time for the load anomaly determination module to detect load anomalies; the status analysis and determination module evaluates the vehicle status to determine whether it is operating normally and provides the result to the intelligent feedback and adjustment module for adjustment.

[0013] The present invention is further configured such that: the load anomaly determination module detects load problems and transmits the information to the status analysis and determination module for analyzing whether adjustment is needed; the abnormal data comparison module uses the preset threshold stored in the abnormal data threshold module for data comparison to detect whether the current status is abnormal; the abnormal event response module generates an event report and notifies relevant personnel using the results of the abnormal data comparison module.

[0014] The present invention is further configured such that: the vehicle load sensing module measures the load data in real time and transmits it to the multi-point data fusion module to integrate the data of multiple sensors; the multi-point data fusion module comprehensively processes the data of each sensor and outputs it to the data filtering and amplification module for signal processing; the data filtering and amplification module filters and amplifies the processed signal and transmits it to the A / D data conversion module for signal conversion; the A / D data conversion module converts the analog signal into a digital signal.

[0015] The present invention is further configured such that: the embedded data processing module receives digitized data, processes it, and transfers it to the local data storage module for storage; the local data storage module stores the processed data and provides it to the data encryption and security module for data protection; the data encryption and security module encrypts the stored data and shares the processed secure data and vehicle status with the vehicle positioning and status monitoring module.

[0016] The present invention is further configured such that: the communication device integration module integrates different communication technologies to achieve data transmission and optimizes the signal through the signal enhancement and optimization module; the signal enhancement and optimization module improves the quality and stability of the communication signal and provides it to the network connection and configuration module to process connection parameters; the network connection and configuration module configures network parameters based on the signal optimization result, and then realizes data upload and instruction issuance through the bidirectional data transmission module.

[0017] The present invention is further configured such that: the cloud data computing module receives the processed data and performs data analysis through the big data analysis module; the big data analysis module uses analysis techniques to generate reports to provide data support for the vehicle scheduling and optimization module; the vehicle scheduling and optimization module performs scheduling optimization according to the analysis results, and then uses the information for route planning by the route planning and navigation module; the route planning and navigation module combines actual traffic information to plan the route path and feeds it back to the alarm and monitoring module for status monitoring and alarm.

[0018] The beneficial effects of the present invention are as follows:

[0019] 1. By adopting high-precision load sensors and multi-point measurement methods, the present invention significantly improves the accuracy of load measurement, ensuring that the load changes of the vehicle can be accurately monitored. The system realizes real-time collection and transmission of vehicle load information through intelligent terminals and communication modules, enabling logistics enterprises to timely obtain the load conditions of vehicles, thereby improving the efficiency and safety of logistics transportation.

[0020] 2. By combining Internet of Things technology and big data analysis algorithms, the present invention constructs an intelligent logistics management platform, which can monitor and analyze the load conditions, driving routes, and transportation times of vehicles in real time, providing decision-making support such as intelligent vehicle scheduling, cargo loading, and transportation route planning for logistics enterprises, thereby improving logistics transportation efficiency and reducing costs. Through real-time monitoring of load conditions, the system can also timely detect illegal acts such as overloading, further improving its safety during actual use. Brief Description of the Drawings

[0021] Figure 1 It is a schematic diagram of the system modules in the present invention.

[0022] Figure 2This is a schematic diagram of the system process of the vehicle positioning and status monitoring module in the present invention. Specific embodiments

[0023] In order to make the technical problems, technical solutions and beneficial effects to be solved by the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. The specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present application without creative efforts belong to the scope of protection of the present application.

[0024] It should be further noted that the drawings and embodiments of the present invention mainly describe and illustrate the concept of the present invention. On the basis of this concept, the specific forms and settings of some connection relationships, positional relationships, power mechanisms, power supply systems, hydraulic systems and control systems may not be completely described. However, on the premise that those skilled in the art understand the concept of the present invention, those skilled in the art can adopt well-known methods to implement the above specific forms and settings.

[0025] When an element is referred to as being "fixed to" or "disposed on" another element, it can be directly on the other element or indirectly on the other element. When an element is referred to as being "connected to" another element, it can be directly connected to the other element or indirectly connected to the other element.

[0026] The orientation terms "inside" and "outside" refer to the inside and outside of the contour of each component itself. The terms "length", "width", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc. indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings. It is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation of the present invention.

[0027] For ease of description, spatial relative terms, such as "above", "over", "on the upper surface", "upper", etc., may be used herein to describe the spatial positional relationship of one device or feature to other devices or features as shown in the figures. It should be understood that the spatial relative terms are intended to encompass different orientations in use or operation in addition to the orientation depicted in the figures. For example, if the device in the figures is inverted, the device described as "above" or "over" other devices or structures will then be positioned "below" or "under" the other devices or structures. Thus, the exemplary term "above" can include both the orientations of "above" and "below". The device may also be positioned in other different ways, and corresponding interpretations are made for the spatial relative descriptions used herein.

[0028] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, features defined with "first" and "second" may explicitly or implicitly include one or more of such features. In the description of the present invention, "a plurality of" means two or more, and "several" means one or more, unless otherwise specifically defined.

[0029] A real-time load and intelligent Internet of Things system for commercial transport vehicles provided by the present invention will now be described.

[0030] Embodiment 1

[0031] As Figure 1 shown, a real-time load and intelligent Internet of Things system for commercial transport vehicles includes a load measurement and data acquisition module responsible for measuring the vehicle load information in real time and collecting relevant data, a data processing and storage module for processing, converting, and storing the collected data, a wireless communication and transmission module for realizing the wireless transmission of load and position information to ensure that the data can be uploaded to the management platform in real time, and a logistics management and decision support module for analyzing and processing the received data to provide decision support such as optimized scheduling, cargo loading, and route planning for logistics operations;

[0032] The load measurement and data acquisition module includes a vehicle load sensing module for installing high-precision sensors on the vehicle suspension or axle to measure the load in real time, a multi-point data fusion module for fusing measurement data by installing multiple sensors at different positions, a data filtering and amplification module for filtering and amplifying the sensor signals, and an A / D data conversion module for converting analog signals into digital signals;

[0033] The data processing and storage module includes an embedded data processing module for processing and calculating the collected data using an embedded system, a local data storage module for storing the processed data in the intelligent terminal, a data encryption and security module for encrypting the data, and a vehicle positioning and status monitoring module for obtaining the vehicle position and monitoring the vehicle operation status using the GPS or Beidou system;

[0034] The wireless communication and transmission module includes a communication device integration module for integrating 4G / 5G / NB-IoT modules to achieve wireless data transmission, a signal enhancement and optimization module for signal enhancement and optimization through antenna design and signal optimization technologies, a network connection and configuration module for configuring the network connection parameters of the communication module, and a two-way data transmission module for uploading data and issuing commands and supporting real-time interaction;

[0035] The logistics management and decision support module includes a cloud data calculation module for receiving and processing data using cloud computing technology, a big data analysis module for analyzing the load data and location data to generate reports and charts, a vehicle scheduling and optimization module for vehicle scheduling and transportation task optimization based on the analysis results, a route planning and navigation module for planning the optimal transportation route by combining real-time traffic information and vehicle status, and an alarm and monitoring module for real-time monitoring of vehicle status to provide abnormal alarm and processing suggestions;

[0036] The vehicle load sensing module measures the load data in real time and transmits it to the multi-point data fusion module to integrate the data of multiple sensors; the multi-point data fusion module comprehensively processes the data of each sensor and outputs it to the data filtering and amplification module for signal processing; the data filtering and amplification module filters and amplifies the processed signal and transmits it to the A / D data conversion module for signal conversion; the A / D data conversion module converts the analog signal into a digital signal;

[0037] The embedded data processing module receives the digitized data for processing and transmits it to the local data storage module for storage; the local data storage module stores the processed data and provides it to the data encryption and security module for data protection; the data encryption and security module encrypts the stored data and shares the processed security data and vehicle status with the vehicle positioning and status monitoring module;

[0038] The communication device integration module integrates different communication technologies to achieve data transmission and optimizes the signal through the signal enhancement and optimization module; the signal enhancement and optimization module improves the quality and stability of the communication signal and provides it to the network connection and configuration module to process the connection parameters; the network connection and configuration module configures the network parameters based on the signal optimization result, and then realizes the data upload and command issuance through the two-way data transmission module;

[0039] The cloud data calculation module receives the processed data and performs data analysis through the big data analysis module. The big data analysis module uses analysis techniques to generate reports and provide data support for the vehicle scheduling and optimization module. The vehicle scheduling and optimization module performs scheduling optimization based on the analysis results and then uses the information for route planning in the route planning and navigation module. The route planning and navigation module combines actual traffic information to plan the route path and feedbacks it to the alarm and monitoring module for status monitoring and alarm.

[0040] In the above embodiment, the load sensor is installed on the suspension or axle of the vehicle, and a suitable installation position is selected according to the vehicle model and structure, and calibration and debugging are carried out to ensure the measurement accuracy. The intelligent terminal is installed in the cab and connected to the load sensor through a serial port or CAN bus. The power supply can be provided by the vehicle power system or an independent module, and initialization settings are performed to configure communication parameters and vehicle information. The communication module should be installed on the vehicle and connected to the intelligent terminal, and the antenna needs to be installed externally to ensure signal quality. Subsequently, network configuration and testing are carried out to ensure normal wireless network connection. A logistics management platform is built on the server of the logistics enterprise, including a database, application, and Web server. The software adopts a B / S architecture, and users operate and manage through a browser. After completion, function testing and performance optimization are carried out to ensure the stable operation of the platform.

[0041] Embodiment 2

[0042] As Figure 1-2 shown, a real-time load and intelligent Internet of Things system for commercial transport vehicles. The vehicle positioning and status monitoring module includes a multi-source positioning fusion module for integrating GPS, Beidou, and Wi-Fi positioning for multi-source data fusion, a vehicle inertial navigation prediction module for calculating the vehicle position using an inertial navigation system in case of weak or lost signals, a real-time load monitoring module for real-time monitoring of vehicle load changes through a load sensor, an environmental perception and dynamic adjustment module for perceiving the surrounding environment using camera or lidar technology to adjust vehicle status monitoring parameters, a status analysis and determination module for analyzing vehicle status data to determine whether the vehicle is in a normal operating state, a load anomaly determination module for determining whether the load exceeds the rated load or shows abnormal fluctuations, an intelligent feedback and adjustment module for adjusting vehicle operating parameters in real-time according to the results of the determination module, an abnormal data comparison module for comparing the current vehicle status data with the preset abnormal data threshold, an abnormal data threshold module for storing the system preset abnormal data threshold, and an abnormal event response module for automatically generating an event report and notifying relevant personnel when an anomaly is detected;

[0043] The vehicle inertial navigation prediction module uses vehicle position data to supplement the positioning ability of the multi-source positioning fusion module when the signal is weak; the real-time load monitoring module provides load data in real time for the load anomaly determination module to detect load anomalies; the status analysis and determination module evaluates the vehicle status to determine whether it is operating normally, and provides the result to the intelligent feedback and adjustment module for adjustment. The load anomaly determination module detects a load problem and transmits the information to the status analysis and determination module to analyze whether adjustment is needed; the abnormal data comparison module uses the preset threshold stored in the abnormal data threshold module to compare data to detect whether the current status is abnormal; the abnormal event response module generates an event report and notifies relevant personnel using the result of the abnormal data comparison module.

[0044] In the above embodiment, during the vehicle driving process, the load sensor measures the load information in real time and transmits it to the intelligent terminal. After the intelligent terminal processes and stores the data, it uploads the data to the logistics management platform through the communication module. At the same time, the intelligent terminal obtains the vehicle position information through the GPS or Beidou system and uploads it together with the load data. The logistics management platform analyzes the received load and position information, generates load reports, driving trajectory maps, transportation efficiency analysis, etc., and provides decision-making support for logistics enterprises. Enterprises can perform vehicle scheduling and cargo stowage according to the analysis results to optimize transportation tasks, improve efficiency and reduce costs. The platform also plans the optimal transportation route for the vehicle according to the load, route and traffic conditions, prevents congestion and overloading, and improves efficiency and safety. In addition, if the vehicle load exceeds the standard or an abnormality occurs, the platform will send an alarm message to remind relevant personnel to take measures, such as adjusting the cargo stowage or stopping for inspection, to ensure safe operation.

[0045] Among them, the real-time load monitoring module provides load data to supplement the navigation judgment of the vehicle inertial navigation prediction module to make the navigation more accurate; the real-time load monitoring module affects the parameter adjustment of the environment perception and dynamic adjustment module by providing load data to improve the accuracy of monitoring.

[0046] Among them, the status analysis and determination module uses the environment information provided by the environment perception and dynamic adjustment module to evaluate the operating condition of the vehicle; the status analysis and determination module uses the load status result provided by the load anomaly determination module to comprehensively analyze the overall operating status of the vehicle.

[0047] Working principle: When the present invention is in use, a high-precision load sensor is installed on the vehicle's suspension or axle. Select a suitable installation location and perform calibration and debugging to ensure measurement accuracy. The intelligent terminal is installed in the cab and connected to the load sensor through a serial port or CAN bus. The power supply can be provided by the vehicle power system or an independent module. After completion, perform initialization settings, configure communication parameters and vehicle information. The communication module should be installed on the vehicle and connected to the intelligent terminal. The antenna needs to be installed externally to ensure signal quality. Then, perform network configuration and testing to ensure normal wireless network connection. Build a logistics management platform on the server of the logistics enterprise, including a database, application, and web server. The software adopts a B / S architecture, and users operate and manage through a browser. After completion, perform functional testing and performance optimization to ensure the stable operation of the platform.

[0048] During the vehicle's driving process, the load sensor measures the load information in real-time and transmits the data to the intelligent terminal. The intelligent terminal processes and stores the data and uploads the data to the logistics management platform through the communication module. At the same time, the intelligent terminal obtains the vehicle's location information through the GPS or Beidou navigation system and uploads it together with the load data. The logistics management platform analyzes and processes the received data, generates load reports, driving trajectory maps, transportation efficiency analysis, etc., to provide decision-making support for the logistics enterprise. The enterprise can perform vehicle scheduling and cargo loading according to the analysis results, optimize transportation tasks, improve efficiency, and reduce costs.

[0049] The logistics management platform plans the optimal transportation route based on factors such as the vehicle's load condition, driving route, and traffic conditions, avoiding congestion and overloading situations, and improving transportation efficiency and safety. The platform is equipped with an alarm function. When the vehicle load exceeds the rated value or an abnormality occurs, an alarm message is sent in a timely manner to remind relevant personnel to take measures, such as adjusting the cargo loading or stopping for inspection, to ensure the safe operation of the vehicle. By implementing these steps, the system realizes the real-time collection, analysis, and decision-making support of the vehicle's load information, improving the operation efficiency and safety of the logistics enterprise.

[0050] The above is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent replacements, and improvements made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

[0051] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present application. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprise" and / or "include" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0052] Unless otherwise specifically stated, the relative arrangements of components and steps, numerical expressions, and numerical values set forth in these embodiments do not limit the scope of the present application. At the same time, it should be understood that, for the sake of convenience of description, the dimensions of the various parts shown in the drawings are not drawn in actual proportional relationships. Technologies, methods, and devices known to those of ordinary skill in the relevant art may not be discussed in detail, but where appropriate, the said technologies, methods, and devices should be regarded as part of the authorization specification. In all the examples shown and discussed here, any specific value should be construed as merely exemplary and not as a limitation. Therefore, other examples of the exemplary embodiments may have different values. It should be noted that: like reference numerals and letters denote like items in the following drawings, and thus, once an item is defined in one drawing, it does not need to be further discussed in subsequent drawings.

Claims

1. A real-time load and intelligent IoT system for commercial transport vehicles, characterized in that: It includes a load measurement and data collection module for measuring vehicle load information in real time and collecting relevant data, a data processing and storage module for processing, converting and storing the collected data, a wireless communication and transmission module for realizing wireless transmission of load and position information to ensure that data can be uploaded to the management platform in real time, and a logistics management and decision support module for analyzing and processing received data to provide decision support for logistics operations such as optimized scheduling, cargo loading and route planning; The load measurement and data acquisition module includes a vehicle load sensing module for real-time measurement of load by a high-precision sensor installed on the vehicle suspension or axle, a multi-point data fusion module for fusing measurement data using an algorithm by installing multiple sensors at different positions, a data filtering and amplification module for filtering and amplifying sensor signals, and an A / D data conversion module for converting analog signals into digital signals; The data processing and storage module includes an embedded data processing module for processing and calculating the collected data using an embedded system, a local data storage module for storing the processed data in the intelligent terminal, a data encryption and security module for encrypting the data, and a vehicle positioning and status monitoring module for obtaining the vehicle position and monitoring the vehicle operation status using the GPS or Beidou system.

2. A commercial transport vehicle real-time load and intelligent IoT system according to claim 1, characterized in that: The wireless communication and transmission module includes a communication device integration module for integrating 4G / 5G / NB-IoT modules to realize wireless data transmission, a signal enhancement and optimization module for antenna design and signal optimization technology, a network connection and configuration module for configuring the network connection parameters of the communication module, and a two-way data transmission module for realizing data upload and command issuance and supporting real-time interaction; The logistics management and decision support module includes a cloud data computing module for receiving and processing data using cloud computing technology, a big data analysis module for analyzing load data and location data to generate reports and charts, a vehicle scheduling and optimization module for optimizing vehicle scheduling and transportation tasks based on analysis results, a path planning and navigation module for planning the optimal transportation route based on real-time traffic information and vehicle status, and an alarm and monitoring module for real-time monitoring of vehicle status to provide abnormal alarms and processing suggestions.

3. A commercial transport vehicle real-time load and intelligent IoT system according to claim 1, characterized in that: The vehicle positioning and status monitoring module includes a multi-source positioning fusion module for integrating GPS, Beidou and Wi-Fi positioning for multi-source data fusion, a vehicle inertial navigation prediction module for calculating the vehicle position by using an inertial navigation system when the signal is weak or the signal is lost, a real-time load monitoring module for real-time monitoring of vehicle load changes through a load sensor, an environment perception and dynamic adjustment module for using a camera or lidar technology to perceive the surrounding environment and adjust vehicle status monitoring parameters, a status analysis and determination module for analyzing vehicle status data to determine whether the vehicle is in normal operating status, a load abnormality determination module for determining whether the load exceeds the rated load or has abnormal fluctuations, an intelligent feedback and adjustment module for adjusting vehicle operating parameters in real time according to the results of the determination module, an abnormal data comparison module for calling an abnormal data threshold for comparison with the current vehicle status data, an abnormal data threshold module for storing system preset abnormal data thresholds, and an abnormal event response module for automatically generating an event report and notifying relevant personnel when an abnormality is detected.

4. A commercial transport vehicle real-time load and intelligent IoT system according to claim 3, characterized in that: The vehicle inertial navigation prediction module uses the vehicle position data to supplement the positioning capability of the multi-source positioning fusion module when the signal is weak; the real-time load monitoring module provides load data in real time for the load abnormality determination module to detect load abnormalities; The state analysis and determination module evaluates the vehicle state to determine whether it is operating normally, and provides the result to the intelligent feedback and adjustment module for adjustment.

5. A commercial transport vehicle real-time load and intelligent IoT system according to claim 4, characterized in that: The load abnormality determination module detects the load problem and passes the information to the status analysis determination module to analyze whether adjustment is needed; the abnormal data comparison module uses the preset threshold stored in the abnormal data threshold module to perform data comparison to detect whether the current state is abnormal; the abnormal event response module uses the results of the abnormal data comparison module to generate an event report and notify relevant personnel.

6. A commercial transport vehicle real-time load and intelligent IoT system according to claim 1, characterized in that: The vehicle load sensing module measures the load data in real time and transmits it to the multi-point data fusion module to integrate the data of multiple sensors; the multi-point data fusion module comprehensively outputs the data of each sensor to the data filtering and amplification module for signal processing; the data filtering and amplification module filters and amplifies the processed signal and transmits it to the A / D data conversion module for signal conversion; the A / D data conversion module converts the analog signal into a digital signal.

7. A commercial transport vehicle real-time load and intelligent IoT system according to claim 1, characterized in that: The embedded data processing module receives the digitized data for processing and transmits it to the local data storage module for storage; the local data storage module stores the processed data and provides it to the data encryption and security module for data protection; the data encryption and security module encrypts the stored data and shares the processed security data and vehicle status with the vehicle positioning and status monitoring module.

8. A commercial transport vehicle real-time load and intelligent IoT system according to claim 2, characterized in that: The communication equipment integration module integrates different communication technologies to realize data transmission and optimizes the signal through the signal enhancement and optimization module; the signal enhancement and optimization module improves the quality and stability of the communication signal and provides it to the network connection and configuration module to process the connection parameters; the network connection and configuration module configures the network parameters based on the signal optimization results, and then realizes data uploading and command issuing through the two-way data transmission module.

9. A commercial transport vehicle real-time load and intelligent IoT system according to claim 2, characterized in that: The cloud data computing module receives the processed data and performs data analysis through the big data analysis module; the big data analysis module generates reports using analysis technology to provide data support for the vehicle scheduling and optimization module; the vehicle scheduling and optimization module performs scheduling optimization based on the analysis results, and then uses the information for the path planning and navigation module to perform route planning; the path planning and navigation module plans the route path in combination with the actual traffic information, and feeds back to the alarm and monitoring module for status monitoring and alarm.

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