Prediction of Water Quality System for Aquaculture using Machine Learning
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Abstract
Indian aquaculture and fishing is one of the key stages of food production that provides healthy food security which also provides employment, livelihoods and contribute to the growth of Indian agriculture. Like all other aquatic organisms they also have a wide range of tolerance, so fish farming of any species requires certain conditions that must be met. Water quality is a critical factor in the processing of aquatic organisms. In this paper, we created an application using ML to predict water boundaries and monitor fish ponds. The water level is predicted in an hourly manner to ensure the growth and survival of aquatic life. The web application is built using Flask to alert the user to critical situations. The impact of water parameter changes can be effectively treated if the information is analyzed and water quality is expected ahead of time.
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