MACHINE LEARNING AND BORDER SECURITY

Abstract

Border security has been a significant issue of concern since decades, not only for India but for the whole world. Conventional border surveillance and protection systems include video surveillance systems, border patrol vehicles, permanent and mobile observation posts and control centers which engage high deployment and operational expense. Moreover, the hostile nature of borders makes deployment of the surveillance systems trickier. Conventional border surveillance and protection systems are not competent to ensure complete security, so an improved surveillance and protection system is needed. This research examines numerous intrusion detection techniques, border surveillance methods and a variety of algorithms for tracking moving objects.