Highly accurate emergency vehicle management for multiple path using support vector machine based predictor

Abstract

Emergency vehicle management (EVM) plays an important role in different lifesaving field such as medicine, fire and safety, and defense etc. The transportation time of the EV mainly depends upon various parameter such as traffic density (TD), weather condition (WC), road condition, conjunction etc. Before selecting a route, it is necessary to confirm that the selected route can reach the destination with minimum time without any destruction of the carrier. A highly accurate emergency vehicle management for multiple path using support vector machine (MP-EVM-SVM) with objective function which is modelled mathematically is proposed in this work. Objective function is modelled based on various parameters such as distance, traffic density, slope, road type, road width etc. MP-EVM-SVM system can be used in the real-time applications such as transportation time estimation and optimum path selection from various path. MP-EVM-SVM can predict the best path which can reach the destination with less time in smooth manner. Proposed algorithm gives 97% of accuracy which is high when compared to the conventional path prediction techniques.