Implementation and Performance Evaluation of an IoT-Based Multi-Sensor Water Quality Monitoring System for Nile Tilapia Ponds Using an ESP32 Microcontroller
Water quality strongly governs the growth, health, and survival of Nile tilapia (Oreochromis niloticus), yet many small- and medium-scale ponds are still monitored manually through periodic sampling, which is labor-intensive, infrequent, and prone to error. This study designed, implemented, and evaluated an Internet of Things (IoT)-based monitoring system that integrates seven sensors with a single ESP32 microcontroller: five water quality sensors (pH, total dissolved solids [TDS], dissolved oxygen [DO], turbidity, and temperature) and two environmental sensors (rainfall and light intensity). Following a research and development (R&D) approach with a waterfall model, the prototype transmitted data to a web-based IoT platform and displayed readings on a local OLED screen. The system was evaluated through component voltage measurements, a 7-day monitoring trial with pond water (May 4–10, 2026), a functionality test by two expert validators, and a usability test with 10 respondents. All sensors and the microcontroller operated as intended, with measured component voltages of 3.7–4.9 V. Over the trial, mean values were 26.48 °C for temperature, 7.31 for pH, 1,060.67 ppm for TDS, 3.41 mg/L for DO, and 39.68 NTU for turbidity; the persistently low DO indicated a need for supplementary aeration. The overall usability score was 83.08%, classified as “very feasible.” The results show that a low-cost, single-board multi-sensor system can provide continuous, remotely accessible records of pond conditions to support decision-making in sustainable tilapia aquaculture. Validation against calibrated reference instruments under field conditions is the recommended next step.