Study Of Highway Long-Distance Passenger Transport Safety Supervisory System Based On IOT Technology

In recent years, China’s highway mileage is increasing, and the road passenger transportation has the characteristics of fast and convenient. The social demand for highway passenger transport has never reduced. But it also brings traffic accidents frequently, causing massive losses of personnel and property with great social influence, especially in the long-distance passenger transport. Therefore, improving highway long-distance passenger transport safety state is positive and significant.First of all, this paper analyses the highway long-distance passenger transport safety factors from the literature researches combining with the survey of passenger production process. This paper analyses the transport safety factors of person, vehicles, roads and environment from the perspective of system.Secondly, this paper establishes Bayesian networks of driver’s error and mechanical failure. By contrast to the prior probability of each node and the change of the a posteriori probability amplitude, the paper analyzes emphatically the regulatory factors, respectively is speeding, driving time, weather condition, road grade, overload state, state of the braking system and tires.Again, this paper analyzes the application of the Internet of Things(IOT) technology which is used in the field of the supervisory system of passenger transport. Based on the technical features of the Internet of things, this paper builds the system of the safety supervisory system’s function model and network layer model. To achieve the goal of safety state’s automatic identification, this paper establishes the safety judgment algorithm model.Finally, after designing the hardware and database of passenger transport supervisory system, this paper designs the program of highway long-distance passenger transport supervisory system. It can automatically monitor the factors of vehicle safety state, license plate number, monitoring time, monitoring location, single driver’s driving time, vehicle speed, vehicle overloading, highway grade, vehicle automatic fault detection alarm level, vehicle maintenance period, the rainy, snowy and fog weather conditions.