Border Surveillance System Using Deep Learning


Aditya Nahata, Nanhay Singh
Netaji Subhas University Of Technology, Dwarka, New Delhi, India.


The old notion of physical borders between nations has become obsolete with the onset of globalization and the greater mobility of global inhabitants. Physical boundaries that depend on military forces and powerful weaponry need a large amount of labor, are prone to human mistake, and could be harmful to the environment, especially in rocky areas. This project seeks to introduce a "Smart Border Surveillance System" as a novel way to overcome the constraints of physical borders. This system replaces the traditional strategy of armed patrolling with cutting-edge surveillance technology and includes an integrated Intruder Alert System. By doing this, border security concerns are addressed without the need for armed patrols and physical barriers, which frequently result in the loss of human life and put a burden on technology. The given system makes use of sensors and surveillance cameras which can detect any kind of threats like drones and weapons through machine learning algorithms and alerts the officials in case of such detections.