WATER QUALITY PREDICTIONS AND PRAWN SUITABILITY ANALYSIS USING IMAGE-BASED MACHINE LEARNING

Water Quality Predictions and Prawn Suitability Analysis is a machine learning approach to predict water quality parameters and prawn suitability by analyzing the color features from images of water. This system can predict key water parameters such as Turbidity, pH, Dissolved Oxygen (DO) and Temperature which are critical for prawn cultivation. The project integrates computer vision techniques to extract image features, and leveraging the machine learning models to train the extracted features for predicting water qualities and suitability. A Random Forest based multi-output model is employed for predicting water parameters, while a classifier predicts the overall suitability of the water for prawn cultivation. This approach aims to provide an efficient and scalable solution for real-time water quality monitoring in aquaculture, contributing to sustainable and optimized prawn farming practices.