Kualitas Ikan Asap Hasil Proses Smart Cold Smoking Berbasis IoT - Krishnadhana, I Komang Pande Andika; Suteja, I Made Wira; Sugandi, Muhamad Mirza; Dharma, Agus; Agung, I Gusti Agung Putu Raka (Universitas Pahlawan Tuanku Tambusai, 2025)
Traditional fish smoking methods often face challenges in maintaining stable temperature and smoke density, which affect product quality. This capstone project develops a Smart Cold Smoking system based on the Internet of Things (IoT), utilizing the ESP32 devkit for automatic control of temperature and smoke. The system integrates DS18B20 temperature sensor, MQ-135 smoke sensor, RTC DS3231, DC fan, servo motor, buzzer, and 16x2 LCD, all monitored via the ThingSpeak platform. Smoking is carried out at 45–50°C for 6 hours using a mixture of coconut shell and husk. Results showed moisture reduction of 29.24% in mackerel and 18.72% in skipjack, with organoleptic scores averaging close to 7. This system improves product consistency and efficiency, making it suitable for small to medium-scale fish smoking businesses.