Rancang Bangun Sistem Kamera Pengawas dengan Pengenalan Wajah untuk Keamanan Berbasis Blynk Legacy - Zamorano, Chandra I.; Prawiroredjo, Kiki; Julian, E. Shintadewi; Djuana, Endang (Fakultas Teknik Elektronika dan Komputer Universitas Kristen Satya Wacana, 2023)
Covid-19 pandemic that has occurred since the beginning of 2020 has brought down all aspects of the country, starting from community activities to the economy. This has an impact on increasing the number of crimes committed by the community such as theft, robbery or other crimes. In this study, a room security system is proposed that uses a surveillance camera with a face recognition ability that records the face image of an intruder and records events as evidence of an intrusion. This system sends information quickly and automatically to the Android application user if an intruder who the camera doesn't recognize enters his house. The smartphone application user can control camera movements inside the house to monitor the movement of intruders and record the incident. This system uses 5 ESP32-CAM cameras. One camera is used to recognize and record the intruder's face image placed in front of the house and four cameras as surveillance and face recognition cameras are placed inside of the house. Each camera is driven by a servo motor controlled by a ESP8266 microcontroller. From the test results it is known that the maximum distance that the cameras still recognize the face image of an intruder or the home owner's face image is 2 meters when the light is bright. When it is dim, the camera in front of the house recognizes the face images up to 0.5 meters while the cameras inside of the house recognize the face images up to 1 meter. The average delay time for sending data from the camera system to application user is 201 ms to 617 ms.