Study On Intervention And Optimization Of The Performance Of Internet Of Vehicles Security System

With the vigorous development of China’s economy and mobile Internet of Things(IOT),the Internet of Vehicles based on smart hardware has entered a golden period of development.As a subdivision of the Internet of Vehicles,the Internet of Vehicles logistics platform aim to solving all problems in the entire business line of the industry,like freight and transportation of goods and safety management of vehicle driving.There are so many safety problems in the logistics industry of track drivers in their daily transportation work.The"X Car" networking security platform integrates and calculates the dangerous events with the intelligent equipment in the car,which can help alarm the driver’s risk and avoid it.This article aims to solve the problem of "X Car"platform with untimely and unreasonable risk scheduling and unreasonable and inaccurate risk performance intervention.First,to formulate the risk label calculation rules and visualize the risk types.A risk profile is established,and the risk is classified and divided into different areas by quantitative calculation to solve the problem of risk segmentation.Second,to optimize the risk scheduling model in order to shorten the risk calculation cycle.The matching result is determined by both the customer preference and the risk task,and each risk had one corresponding processing object,so that all risks could be solved.Third,to optimize risk performance intervention.According to multi-dimensional data such as risk level,risk interval,and risk label,risks are sorted,queued,and reminded.The processing method in the risk intervention matrix is automatically selected according to the risk scenario.The newly optimized performance method can track the trend of high-risks and historical intervention methods and times,so that high-risks can be better tracked and managed.