IoT-enabled Real-time Water Quality Monitoring System for Sustainable Small-scale Aquaculture in Sub-Saharan Africa

Small-scale aquaculture in sub-Saharan Africa is significantly impacted by poor water quality, with primary challenges including low dissolved oxygen, temperature stress, and high turbidity, often leading to considerable losses. The purpose of this study is to develop and evaluate a low-cost, IoT-based real-time monitoring system. This system is designed to facilitate early intervention and improve fish survival rates for farmers with limited resources. The system is built upon an ESP32 microcontroller, which is integrated with multi-parameter water sensors and automated pumps. Wi-Fi connectivity is utilised to transmit live data to the ThingSpeak and Blynk cloud platforms. To validate its performance, experimental tests were conducted to assess sensor accuracy, system responsiveness, and the effectiveness of its automated mitigation functions. The results of the experiments show reliable measurements and the rapid detection of unsafe water conditions. The automated corrective flushing successfully restored dissolved oxygen, temperature, and turbidity to acceptable levels. These findings demonstrate that the proposed system provides an affordable and practical solution for enhancing water quality management and reducing fish mortality in small-scale aquaculture environments.