Aquaculture Water Quality Monitoring Measuring Physicochemical Parameters Using Wireless Sensor Networks and IoT

• Published in: 2025 1st International Conference on AIML-Applications for Engineering & Technology (ICAET) pp. 1 - 5
• Main Authors: Kumar, Padarti Vijaya, Rajani, Koduri Naga, Saritha, Vanka, Prasad, Kudumu Vara, Lakshmi, T.V. Hyma, Devana, V.N. Koteswara Rao
• Format: Conference Proceeding
• Language: English
• Published: IEEE 16.01.2025
• Subjects: Arduino UNO; Blynk server; Conductivity; Fisheries; Internet of Things; IoT; Monitoring; Parameters measuring; Sensors; Servers; Temperature measurement; Temperature sensors; Turbidity; Wireless sensor networks
• DOI: 10.1109/ICAET63349.2025.10932148

IoT is a pivotal factor among rapidly advancing technologies. Through the utilisation of this technology, we can execute all tasks without the need for human interaction. By utilising this method, we can ascertain the water's quality, a crucial factor for the optimal growth of fish. Fisheries aquaculture is a crucial source of sustenance, nourishment, income, and livelihood for countless individuals worldwide. Financing and operational expenses associated with the modernization of fishponds. In the present era, given the essentiality of water for the survival of fish, fish farmers often encounter challenges pertaining to the quality of water. Several factors, including the pH level of the water, temperature, oxygen content, hardness, and salinity, can influence the situation. Failure to promptly assess the water quality might lead to significant financial losses for the farmer. The implementation of Internet of Things (IoT) technology can help overcome many challenges with the assistance of a state-of-the-art water tracking system. This proposed system utilises an innovative way to monitor water quality by employing an Arduino-based Controller board and IoT Technology. The IoT system comprises sensors for Temperature, Turbidity, pH, and Conductivity, which assess crucial parameters of water quality such as temperature, turbidity, pH, and conductivity. Additionally, it includes a compact computer board that analyses the data and transmits visual signals to the fish farming management. Regularly screening and comparing water quality measures is typically advised. The collected data will be transmitted to the Node MCU and presented on the farmer's mobile device via the Blynk server. Consequently, the farmer no longer wants to hire workers.