Development of wireless sensor network for collision avoidance system using emergency situation prediction mechanism

An efficient and secure transportation system is critical and imperative for the development of a country. In modern societies the transport system can be expected to be easy, safe and effective. Most collision avoidance frameworks are right now being researched and dependent on street vehicles or inter-vehicle communication. Such organizations are dependent on the vehicle, thereby limiting its compliance with the production of vehicles equipped with the right technologies. In this work, the Emergency Situation Prediction Mechanism (ESPM) framework has been developed and validated to predict the likelihood of a road accident (WSN) for detection and warning information for drivers to prevent accidents. ESPM performs three stages such as reporting, monitoring and prediction in times of emergency. Within the ESPM, the correct prediction is calculated against the vehicle density in three dissimilar states. In these three visualizations, it can be seen that the small gap between assessment and modeling is not analytical results. The results show that the working of the ESPM has increased the reliably towards the prospect. The accuracy of the ESPM prediction on vehicle density is nearly 98 percent in all three scenarios. ESPM framework has been designed and validated for traffic accident prediction and this is considered as the basis for traffic accident prevention methods.