IoT-Based Real-Time Monitoring System for Post-Harvest Fish Storage Quality - Adyanata Lubis; Firman Santosa; Purnama Wirawan (Jurnal Sistem Komputer dan Informatika (JSON), 2025)
This study develops an Internet of Things (IoT)-based system for continuously monitoring the environmental conditions and freshness indicators of post-harvest fish storage. The system integrates an ESP32 microcontroller with a DHT22 temperature-humidity sensor, an MQ-137 ammonia sensor, and an analog pH probe. Sensor measurements are sampled every five seconds, transmitted through Wi-Fi using the MQTT publish-subscribe protocol, stored in a MySQL database through a Node.js backend, and visualized on a React.js web dashboard. A research-and-development design with iterative prototyping was applied, followed by sensor calibration, integration testing, transmission-performance testing, and a 72-hour storage experiment using tuna and snapper samples. The system achieved average accuracies of 97.3% for temperature, 96.8% for relative humidity, 94.2% for ammonia, and 95.1% for pH. Average end-to-end latency was 0.856 s on a local network, 1.230 s on a 10 Mbps Internet connection, and 2.145 s on a 5 Mbps connection. Continuous operation for seven days produced 99.2% uptime. During the storage test, ammonia increased from below 2 ppm to 28.4 ppm while pH decreased from 6.8 to 5.2. The dashboard issued warning and critical alerts when predefined ammonia thresholds were exceeded, demonstrating its capability for timely quality-risk detection.