This study designs and implements an intelligent early fire detection system based on Edge Intelligence using the ESP32-CAM module and an IR photoelectric sensor. The main issues addressed are the reliance of conventional detection systems on cloud connectivity and the high rate of false alarms. This system employs TinyML technology to classify smoke density levels offline and in real-time dire…
Ikbal Muhamad Teland dan Dinda Mutiara Sukmaningrum, “Perancangan Companion Computer Berbasis TinyML untuk Autonomous Edge-Based Early Warning System Lahar Dingin dengan Komunikasi LoRa dan MQTT Cloud”, Tugas Akhir (D-IV) Program Studi Teknologi Rekayasa Komputer Jurusan Teknik Elektro Politeknik Negeri Semarang, di bawah bimbingan Kuwat Santoso , S.T., M.Kom. dan Tahan Prahara, S.T., M.Kom…