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 (Innovative: Journal Of Social Science Research, 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.