Smart Iot-Enabled Home Security System With Yolo-Based Intruder Detection And Sms-Driven Proactive Response

Resumen

The fast growth of smart home devices has resulted in a growing demand for smarter reliable systems. This paper describes the design and implementation of an IoT home security system that combines computer vision and sensor-based detection with real-time communications. The proposed system uses the YOLO algorithm for a view-based human detection utilizing a webcam, with Passive Infrared Sensor (PIR) capabilities for motion-activated detection. To provide a layered security system, LEDs and buzzers give immediate alerts locally, relays control devices such as lights and deterrent sprayers that are activated during Human detection events, the NodeMCU ESP8266 microcontroller acts as the central hub, which managed the sensors, relays and communication to the SMS module. The SMS module provides real-time notification through SMS text message, and a voice call; removing reliance on internet-based platforms and provides reliability; especially in areas with limited internet connections. The proposed system was assessed during various environments and conditions to assess detection accuracy, response time and energy efficiency. It was determined that the system was capable of accurate Human detection, timely alerts, and energy efficient. Overall the combination of YOLO based vision detection with IoT capable hardware management creates a unique and reliable security solution.