Development of Internet of Things (IoT)-Based Fish Dryer

Abstract

This study presents the design and evaluation of an Internet of Things (IoT)-based fish dryer developed to improve traditional drying practices in Northern Samar, Philippines. The system integrates an ESP32 microcontroller for real-time monitoring and control of temperature, humidity, and weight using LCD and web-based interfaces. A bang–bang temperature controller with ±2°C hysteresis maintained stable drying conditions while preventing rapid switching. Drying trials of danggit (Siganus canaliculatus) reduced moisture content from 54–56 % to 24–29 % within 180–200 minutes, following a two-stage drying pattern of surface evaporation and diffusion. Univariate ANOVA revealed that drying location significantly affected temperature (p < 0.001, η² = 0.771) and humidity (p < 0.001, η² = 0.578), while drying duration showed no significant effect. The heat collector consistently exhibited the highest temperature and lowest humidity, confirming effective heat transfer and moisture control. The system achieved an average Specific Moisture Extraction Rate (SMER) of 0.0882 kg/kWh, demonstrating strong energy efficiency. Economic analysis indicated a 24.89 % return on investment and a payback period of 3.88 years. Overall, the IoT-based fish dryer proved technically efficient, energy-saving, and economically viable for small-scale fish processors.