<![CDATA[This research presents the design and implementation of a warehouse door security system based on ESP32-CAM S3 N16R8 integrated with Android applications. The study was motivated by the increasing need for reliable and automated security systems in institutional environments. The objective was to develop a prototype capable of detecting human presence, authenticating registered faces, and providing real time notifications through Telegram. The system utilized PIR sensors to trigger the ESP32-CAM S3 N16R8 camera, which captured facial images and processed them using the LBPH algorithm for recognition. If a registered face was detected, the servo motor unlocked the door, while the buzzer remained inactive. Conversely, unregistered faces triggered the buzzer alarm and denied access. Notifications containing facial data and access status were sent instantly to users via Telegram. The testing phase demonstrated that the system operated consistently and accurately, with high reliability across multiple trials. Internal validation by academic experts yielded a score of 84%, categorized as “Highly Feasible,” while external validation by five respondents from Hero Creative resulted in an average score of 84%, categorized as “Highly Satisfactory.” The findings confirm that the system is not only academically sound but also practically effective for real-world application. This research contributes to the advancement of IoT-based security systems and offers potential for further development, including integration with cloud databases, enhanced algorithms, and broader institutional deployment.]]>
