Comprehensive Real-Time Intrusion Detection System Using IoT, Computer Vision (OpenCV), and Machine Learning (YOLO) Algorithms
Shailaja Nilesh Uke, Pranay Junghare, Shrishti Kenjale, Srushti Korade, Aniket Kothwade · 2024
The objective of this project is to develop an advanced quality human intrusion detection system, integrating IoT hardware with advanced software technologies. This will be done by relying on real-time video footage and using image processing techniques in the identification process of human presence and other potential threats, such as weapons. A face recognition module will be attached, which will let the entry of only authorized people and immediately detect unauthorized intrusions. The system includes live alerts for efficient monitoring and protection of secure places. This system, with high algorithms used and strong hardware, is scalable and reliable, proving to be fully comprehensive in relation to the potential threats against the security offered.