Water Quality Analysis for the Sustainability of Aquaculture Industry using IoT and Big Data

Abstract

The water quality is the most important parameter for aquatic species’ health and growth. The state is critical and is essential to monitor the water quality continuously in real-time. Poor water quality will affect health, growth and ability of the animal to breed. These also affected their yields value based on the amount and size of the animal. The main water parameters such Dissolved Oxygen (DO), pH, temperature, ammonia and Electrical Conductivity (EC) are monitored in real time. The data were acquired by the developed instrument and send wirelessly through wireless GSM communication module to cloud-based database. The data were retrieved, and the water quality parameters are classifying and predicted using deep learning algorithm. Results show that the performance of deep learning algorithm had improve system performance in monitoring the water quality. This system also provides alert signals to farmers based on condition of the water quality parameters. This will ensure suitable water quality for the animal in aquaculture system.