Security systems are essential for homes, offices, and industries, but traditional systems often rely on simple motion detection, which can generate false alarms. This project implements an AI-based intruder detection system using computer vision and deep learning. The system uses YOLO or OpenCV to detect and classify objects such as humans, animals, and vehicles in real time. It can differentiate between authorized personnel and intruders based on facial recognition, reducing false alerts. Additionally, it integrates IoT-enabled alarm systems that trigger alerts, send notifications via mobile apps or SMS, and activate security cameras when unauthorized movement is detected. This smart security system can be deployed in residential areas, offices, or industrial zones to enhance safety and prevent unauthorized access.