Development of an IoT-based monitoring system for water quality in tilapia farming

Shafie, Sharizal (2024) Development of an IoT-based monitoring system for water quality in tilapia farming. Project Report. Universiti Teknikal Malaysia Melaka, Melaka, Malaysia. (Submitted)

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Abstract

Aquaculture is largely used to feed the globe, especially fish. Water quality issues plague tilapia aquaculture. Tilapia farms need IoT water quality monitoring. This gadget improves yield by monitoring water conditions in real time. IoT helps farmers enhance efficiency, meet market demands, and sustainably produce fish. This project will boost tilapia production using an IoT-based water quality monitoring system. Studying IoT devices, water characteristics, cost-effectiveness, and environmental impact. IoT-based monitoring may help tilapia farms grow sustainably and meet protein needs. By addressing water quality challenges caused by pollution, low oxygen levels, and environmental changes like temperature and water availability, effective treatment, waste management, and monitoring systems may make tilapia aquaculture more sustainable and consistent. Tilapia farming at Alai, Melaka is the key experiment in this study. A comprehensive approach is needed to reverse tilapia productivity. Assessing the pond's water quality regularly helps find and fix problems. A monitoring system may enhance tilapia aquaculture output and sustainability. Next, secondary studies examining existing data underline the need of monitoring water quality factors including temperature, dissolved oxygen, and pH to optimise tilapia development. The water quality parameters for temperature, DO, and pH of the tilapia farming monitoring system are 20–35 °C, 3.2–4.7 mg/L (morning), 5.4–6.4 mg/L (afternoon), and 6.5–8.3 respectively. The proposed method involves the installation of sensors through a monitoring device, together with the establishment of an experiment which guarantees controlled conditions for the purpose of data collecting that is correct. For the purposes of connection with the Blynk application, a microcontroller (Arduino Uno) and an ESP8266 module are used for the purposes of data collecting, processing, and transmission. an accurate into temperature changes, pH inconsistencies, and dissolved oxygen levels are revealed by the results and analysis, which highlights the significance of sensor calibration. The results from this study of this research highlight the necessity of carrying out water quality monitoring in order to successfully cultivate tilapia. Both the technique and the monitoring system that have been developed have the objective of providing important data that can be used to optimize conditions, increase production, and ensure the sustainability of tilapia farming. However, the findings highlight the need of spending additional attention to sensor calibration in order to get accurate and dependable results in the implementation of efficient tilapia farming procedures. Overall, dependability, and expansibility demand better analytics and machine learning. IoT-based water quality monitoring might improve tilapia aquaculture, productivity, and sustainability.

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