ANTI-DRONE PROTECTION and SURVEILLANCE for VIPS in PUBLIC SPACES

This project focuses on developing a real-time weapon and intrusion detection system using drones and Convolutional Neural Networks (CNN). A drone equipped with a Wi-Fi camera captures live video, from which frames are extracted and processed by the Raspberry Pi Pico. The CNN algorithm accurately detects weapons and intrusions, triggering instant alerts via a GSM modem to a connected PC. A GPS module provides precise location tracking for enhanced monitoring. The system is divided into three modules: hardware integration, CNN-based detection, and drone deployment for real-time surveillance. This cost-effective solution improves security in sensitive areas, ensuring quick threat detection and response while addressing challenges like processing speed, accuracy, and false positives.