Autonomous Drone Surveillance for Enhancing Discipline in Institutions

This paper presents an AI-powered autonomous drone surveillance system designed to enhance discipline and security in educational institutions. The system integrates unmanned aerial vehicle (UAV) technology with computer vision and deep learning algorithms to enable real-time monitoring of campus environments. A drone equipped with a high-resolution camera captures live video, which is processed using the YOLO (You Only Look Once) model for detecting human presence and identifying whether individuals are wearing ID cards. The system operates autonomously using GPS-based navigation and predefined patrol routes. A web-based dashboard provides real-time video streaming and generates instant alerts when violations are detected. The proposed system overcomes the limitations of traditional CCTV surveillance by offering mobility, wider coverage, and intelligent decision-making. It improves security response time, reduces human effort, and provides a scalable solution for smart campus monitoring