CN-121985035-A - Logistics vehicle-mounted Internet of things data processing device and method based on edge calculation

CN121985035ACN 121985035 ACN121985035 ACN 121985035ACN-121985035-A

Abstract

The invention relates to the technical field of intelligent logistics and Internet of things, in particular to a logistics vehicle-mounted Internet of things data processing device and method based on edge calculation, wherein the processing method comprises the following steps of S1, collecting multisource sensing data of a transport vehicle in real time; S2, executing a preset safety initialization and equipment identity verification process, S3, generating a risk prediction result, S4, generating a key data packet and uploading the key data packet to a cloud platform, S5, starting a corresponding emergency response process based on the type of the abnormal judgment result, and by introducing a safety initialization and equipment identity dual verification mechanism, the safety of equipment and a system is ensured from the source, the millisecond-level local identification and early warning of an abnormal event are realized, the problems of large cloud processing delay and strong network dependence are fundamentally solved, a complete closed loop from on-site rapid treatment to multi-department collaborative scheduling is formed, and the safety management level of high-risk cargo transportation such as dangerous chemicals is remarkably improved.

Inventors

WANG DAXIN
GUO XIANCHANG
XIAO CAIXIA
DAI MENGQI
Yu Jiangcan
LAO GUOWEI
LIU WEI
XIE MINGHAO

Assignees

桂林理工大学南宁分校

Dates

Publication Date: 20260505
Application Date: 20260109

Claims (10)

1. The data processing method of the logistics vehicular Internet of things based on edge calculation is characterized by comprising the following steps of: S1, acquiring multisource sensing data of a transport vehicle in real time, wherein the multisource sensing data comprise vehicle state data, cargo state data and environment sensing data; s2, executing a preset safety initialization and equipment identity verification process, and entering a safety operation state after verification is passed; s3, under the safe running state, generating fusion data based on the multi-source sensing data, performing rule matching analysis on the fusion data to generate an abnormal judgment result, performing machine learning model reasoning analysis on the fusion data to generate a risk prediction result; S4, when the abnormal judgment result shows that an abnormal event exists, local early warning operation is executed, corresponding key data fragments are extracted from the fusion data based on the abnormal event, the key data fragments are processed, and a key data packet is generated and uploaded to a cloud platform; S5, the cloud platform receives the key data packet and analyzes the key data packet to obtain an abnormality judgment result, and a corresponding emergency response flow is started based on the type of the abnormality judgment result.
2. The method for processing logistics vehicular internet of things data based on edge calculation according to claim 1, wherein in S1, the vehicle state data comprises position, speed, acceleration and tire pressure information, the goods state data comprises temperature, humidity, vibration amplitude, inclination angle, pressure value and gas concentration information, and the environment sensing data comprises video streams and external weather information.
3. The method for processing data of the logistics vehicular Internet of things based on edge calculation as set forth in claim 1, wherein in S2, a preset security initialization and equipment identity verification process is executed as follows: reading a starting identification bit, and judging the starting type based on the starting identification bit; If the judging result is the first starting type, executing hardware self-checking to generate a pin state list, and reading a unique machine code of the equipment; Encrypting the pin state list and the unique machine code to generate verification request data; receiving a response to the verification request data, wherein the response is generated after comparison and verification with a prestored legal equipment information base; if the response is a verification passing response, writing corresponding execution codes, modifying the starting identification bit and restarting, and if the response is a verification failure response, modifying the starting identification bit and entering a limited mode.
4. The method for processing the data of the logistics vehicular Internet of things based on edge calculation according to claim 3, wherein the response is generated after comparison and verification with a prestored legal device information base, and the method is characterized by judging whether the unique machine code exists in a legal device list or not and judging whether the matching degree of the pin state list and a prestored reference pin state list exceeds a preset threshold value or not.
5. The method for processing the data of the logistics vehicular Internet of things based on edge calculation according to claim 1, wherein in S3, rule matching analysis is performed on the fusion data to generate an abnormality judgment result, and parameters in the fusion data are compared with a preset rule threshold in real time to generate the abnormality judgment result, wherein the preset rule threshold comprises a threshold for judging overspeed, route deviation, fatigue driving, temperature exceeding, vibration exceeding or gas concentration exceeding.
6. The method for processing logistics vehicular Internet of things data based on edge calculation according to claim 5, wherein machine learning model reasoning analysis is performed on the fusion data to generate a risk prediction result, and the fusion data is input into a machine learning model which is trained and deployed in advance to obtain at least one risk prediction index of a vehicle part failure probability, a cargo deterioration risk level or a traffic accident occurrence probability to generate a risk prediction result.
7. The method for processing the data of the logistics vehicular Internet of things based on edge calculation of claim 1 is characterized by comprising the steps of S4, extracting corresponding key data fragments from the fusion data, and processing the key data fragments, wherein the key data fragments are generated by intercepting the fusion data for a preset time period forwards and backwards respectively by taking a time point generated by the abnormality judgment result as a reference, and the key data fragments are compressed and encrypted to generate a key data packet.
8. The method for processing data of the internet of things on a vehicle by a logistics vehicle based on edge calculation as set forth in claim 1, wherein in S4, the performing a local early warning operation includes at least one of touching an audible and visual alarm, displaying early warning information, or sending a voice prompt signal.
9. The method for processing the data of the logistics vehicular Internet of things based on the edge calculation, which is disclosed in claim 1, is characterized in that in S5, a corresponding emergency response flow is started, an emergency plan template is matched according to the type and the grade of the abnormality judgment result to generate an emergency report, and the emergency report is pushed to a preset regulatory department information system.
10. An edge calculation-based logistics vehicular internet of things data processing device, which adopts the edge calculation-based logistics vehicular internet of things data processing method as set forth in any one of claims 1-9, and is characterized by comprising: the system comprises a data acquisition module, a control module and a control module, wherein the data acquisition module is used for acquiring multi-source sensing data of a transport vehicle in real time, wherein the multi-source sensing data comprises vehicle state data, cargo state data and environment sensing data; The initial verification module is used for executing a preset safety initialization and equipment identity verification process, and entering a safety operation state after verification is passed; The edge processing module is used for generating fusion data based on the multi-source sensing data in the safe running state, executing rule matching analysis on the fusion data to generate an abnormal judgment result, executing machine learning model reasoning analysis on the fusion data to generate a risk prediction result; The early warning reporting module is used for executing local early warning operation when the abnormal judgment result shows that an abnormal event exists, extracting corresponding key data fragments from the fusion data based on the abnormal event, processing the key data fragments, generating a key data packet and uploading the key data packet to the cloud platform; The cloud response module is used for receiving and analyzing the key data packet by the cloud platform, acquiring an abnormality judgment result and starting a corresponding emergency response flow based on the type of the abnormality judgment result.

Description

Logistics vehicle-mounted Internet of things data processing device and method based on edge calculation Technical Field The invention relates to the technical field of intelligent logistics and Internet of things, in particular to a logistics vehicle-mounted Internet of things data processing device and method based on edge calculation. Background Along with the intelligent development of the logistics transportation industry, the vehicle-mounted Internet of things system is widely applied to vehicle monitoring, cargo state sensing and transportation management. The prior art mainly relies on a centralized cloud platform for data processing and analysis. In particular, the safety regulations for the transportation of dangerous chemicals are becoming increasingly stringent. The traditional logistics transportation management system relies on the centralized cloud platform to process data, and has the problems of large data transmission delay, strong network dependence, insufficient real-time performance and the like. Particularly, in the transportation of dangerous chemicals, if the accidents such as leakage, overload, route deviation and the like occur, the second-level response cannot be realized, and the safety accidents are easy to cause. In addition, the existing terminal equipment of the Internet of things has potential safety hazards in the starting stage, such as malicious detection, data tampering and the like, and the overall safety of the system is affected. Disclosure of Invention In order to solve the technical problems in the background art, the invention provides a logistics vehicle-mounted Internet of things data processing device and method based on edge calculation, and the specific scheme is as follows: a logistics vehicle-mounted Internet of things data processing method based on edge calculation comprises the following steps: S1, acquiring multisource sensing data of a transport vehicle in real time, wherein the multisource sensing data comprise vehicle state data, cargo state data and environment sensing data; s2, executing a preset safety initialization and equipment identity verification process, and entering a safety operation state after verification is passed; s3, under the safe running state, generating fusion data based on the multi-source sensing data, performing rule matching analysis on the fusion data to generate an abnormal judgment result, performing machine learning model reasoning analysis on the fusion data to generate a risk prediction result; S4, when the abnormal judgment result shows that an abnormal event exists, local early warning operation is executed, corresponding key data fragments are extracted from the fusion data based on the abnormal event, the key data fragments are processed, and a key data packet is generated and uploaded to a cloud platform; S5, the cloud platform receives the key data packet and analyzes the key data packet to obtain an abnormality judgment result, and a corresponding emergency response flow is started based on the type of the abnormality judgment result. Further, in S1, the vehicle state data includes position, speed, acceleration and tire pressure information, the cargo state data includes temperature, humidity, vibration amplitude, inclination angle, pressure value and gas concentration information, and the environment sensing data includes video stream and external weather information. Further, in S2, a preset security initialization and device authentication procedure is executed as follows: reading a starting identification bit, and judging the starting type based on the starting identification bit; If the judging result is the first starting type, executing hardware self-checking to generate a pin state list, and reading a unique machine code of the equipment; Encrypting the pin state list and the unique machine code to generate verification request data; receiving a response to the verification request data, wherein the response is generated after comparison and verification with a prestored legal equipment information base; if the response is a verification passing response, writing corresponding execution codes, modifying the starting identification bit and restarting, and if the response is a verification failure response, modifying the starting identification bit and entering a limited mode. Further, the response is generated after comparison and verification with a pre-stored legal device information base, and is that whether the unique machine code exists in a legal device list or not is judged, and whether the matching degree of the pin state list and the pre-stored reference pin state list exceeds a preset threshold is judged. Further, in S3, rule matching analysis is performed on the fusion data to generate an abnormality judgment result, wherein the abnormality judgment result is generated by comparing parameters in the fusion data with preset rule thresholds in real time, and the preset rule thresholds comprise thr