<![CDATA[Advancements in information technology have driven the development of home security systems based on the Internet of Things (IoT). This study aims to design a home security system using ESP32-CAM, multisensors, and Telegram for real-time monitoring. The system features face recognition using the Haar Cascade and LBPH algorithms, along with DHT22 and MQ-2 sensors to monitor temperature, humidity, and hazardous gases. The development method used is the prototype model. Testing results showed a face recognition accuracy of 95.31% and the ability to detect temperatures above 40°C and gas concentrations exceeding 300 PPM. The system performs optimally at a distance of 35–150 cm but is limited by extreme lighting and facial angle variations. In conclusion, the system enhances home surveillance effectiveness through real-time monitoring and reliable remote access control]]>
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