Smart System for Freshwater Pisciculture(Ornamental Fish Farming)

In recent times, there has been a significant surge in the advancement of information analysis technology specifically designed for underwater environments. This remarkable progress has brought about numerous advantages for the fields of aquatic resource exploration and aquaculture. Aquaculture is the breeding and harvesting of aquatic animals and plants. The rearing and breeding of fish under controlled conditions is called pisciculture. In this research, we present an automated system to improve technical facilities in Ornamental fish farming. We focus on Fish body length and weight prediction and Water quality measuring, Fish Behavioral Patterns Identification, Predicting the harvest and analyzing data, and can know whether the fish in the tank are alive or not using Machine Learning (ML) and Image Processing techniques. And this project invents a smart device, that contains (IoT) devices and sensors to capture images (by a camera), to obtain data on Ammonia (NH3), Nitrate (NO2-), Nitrite (NO3-), Temperature, Oxygen level (O2) and pH level in the water and we use food pallet to hold and release food according to the conditions. The distinguished data will upload to a cloud system and the web application will display the expected outputs. We use Convolutional Neural Networks (CNN) to analyze the water quality and, to identify different behavioral patterns of fish and identity whether the fish is live or not. Length and weight prediction identified behavioral patterns, identified live or dead fish, harvest prediction and other details also display through the known web application.