IoT-Based Smart Fishery as an Appropriate Technology Solution for Optimizing Freshwater Fish Farming in Remote Areas of Indonesia: A Learning Resource

Abstract

Freshwater fish farming in remote areas of Indonesia faces various challenges, particularly limited water quality monitoring, which results in high fish mortality and low production efficiency. This study aims to develop an Internet of Things (IoT)-based Smart Fishery prototype as an appropriate technology for real-time water quality monitoring. The research employs a Research and Development (R&D) approach, encompassing needs analysis, system design, prototype development, laboratory testing, and limited field trials. The system integrates temperature, pH, and turbidity sensors with an ESP32 microcontroller, data correction algorithms, and a monitoring dashboard. Test results indicate sensor error rates of 0.77% for temperature, 1.62% for pH, and 5.14% for turbidity. The data transmission success rate reached 96.8%. A 30-day field trial demonstrated a reduction in fish mortality from 12.5% ​​to 7.4%. Paired t-test results revealed a statistically significant difference (p < 0.05) between conditions before and after system implementation. This study demonstrates that the IoT-based Smart Fishery system enhances the effectiveness of water quality monitoring and supports faster, more accurate decision-making for fish farming operations in remote areas.