Design and Implementation of an IoT-Based Automatic Salted Fish Dryer System Using Load Cell as an Objective Moisture Indicator

Abstract

Fish is a highly nutritious but rapidly perishable food commodity. Traditional salted fish drying methods heavily depend on unpredictable weather conditions, often taking days to complete and leaving the product prone to contamination. While automated dryers have been introduced, most lack an objective metric to halt the process, relying instead on subjective visual inspection. This study aims to design and implement an Internet of Things (IoT)-based automatic salted fish dryer system equipped with a load cell to objectively determine the dryness level. The proposed system utilizes an ESP32 microcontroller, a DHT22 sensor, a PTC heater, and a DC fan to automatically maintain the drying chamber at an optimal temperature of 70°C. Furthermore, a load cell sensor continuously monitors weight reduction, serving as a real-time proxy for the moisture content. Operational data is transmitted via Wi-Fi to the ThingsBoard platform for remote visualization. System validation showed that the DHT22 and load cell sensors have an accuracy of over 99.20%. Experimental results on 1 kg of Sepat and Layang fish demonstrate that the automated system significantly accelerates the drying process, reducing the required time from 2-3 days to just 8 hours. The system successfully executed an automatic cut-off when the fish weight dropped by 50%, ensuring hygienic, efficient, and consistent production for small-to-medium enterprises.