Efficient and Secured Routing Management for Internet of Vehicles Using AI

The Unmanned Ariel Vehicles (UAV) play a major role in establishing the environmental sustainability, by providing the most valuable services in pandemic situations and disaster management. But these devices are constrained with major challenges with respect to the trajectory movements, collision and other attacks by the intruders. This paper provides solution to handle the collisions, with respect to known attacks or unknown accidents by building a robust trained model to train the possibilities of the collisions, so that to build an effective remedial system, to handle the same. The accuracy observed by the Random Forest (RF), Ada Boost(ADB) and Decision Tree (DT) models are proving the efficiency of the system, where it is almost closer to 100%, except for the DT which recorded 99.98%. The Naive Bayes(NB) which recorded 95.42% defines the effectiveness of the system developed.