Design And Implementation Of Vehicle Monitoring System Based On Internet Of Things Platform

Special equipment refers to equipment that involves people's lives and safety,such as boilers,elevators,and special motor vehicles in the field.In recent years,with the rapid development of China's economy,the number of special equipment has continued to increase.Judging from the current status of special equipment management in China,there are problems that the equipment is not registered or not subject to safety monitoring,and the equipment that is critically scrapped is still in operation.For special equipment vehicles,due to their large mobility and scattered location,important information such as vehicle driving status and equipment status cannot be acquired and managed in a timely manner,which affects driving safety.Secondly,since the GPS signal of the vehicle is an electromagnetic wave,it is easily affected by external environmental factors and causes abnormal problems such as positional drift,which greatly affects the reliability of the vehicle monitoring while reducing the accuracy of the data.The traditional vehicle monitoring system on the market,the server is generally leased and developed by developers,causing serious waste of human power and material resources for the regular maintenance of the system.With the multi-user high concurrent load brought by the expansion of the vehicle monitoring business in the future,the bottleneck problem that the system is prone to will also lead to more economic losses.In view of the above requirements,this paper designs and implements a high-performance vehicle monitoring system that integrates the registration of special equipment and comprehensive multi-demand based on the open source Internet of Things platform.The system can realize remote centralized registration management of special equipment under different states,and can also monitor special equipment vehicles and road motor vehicles.While ensuring the safety of people and vehicles,the monitoring work is made more intelligent,which greatly improves the efficiency of enterprise management.In this paper,based on the research background,the in-depth functional and non-functional requirements analysis is carried out,and the organizational structure of the platform is designed.Subsequently,based on the SiteWhere open source Internet of Things platform,Spring,Hibernate,MongoDB,Vue.j s,third-party LBS services and other technical methods are used to implement various functional modules of the system.For the abnormal problem of GPS data,this paper introduces an unsupervised learning method in machine learning-isolated forest algorithm to detect abnormal data.At the same time,using the original GPS dataset of real vehicle,the cormparison experiment with local anomaly factor algorithm verifies that the isolated forest algorithm has good anomaly detection effect.This paper also uses Redis cache to optimize the performance of the vehicle monitoring system,which solves the access pressure of the main database under the multi-user high concurrency environment.Finally,the availability and stability of the system were verified by functional tests and stress tests.