AquaAI
Smart Aquaculture Project (AquaAI) integrates computer vision, artificial intelligence, and the Internet of Things (IoT). The project automates key operational processes such as feeding, growth monitoring, health assessment, and environmental management by providing data-driven functions to improve efficiency, sustainability, and productivity.
A) Environmental Sensors
The project includes a comprehensive set of automated sensors integrated with the feeding device. These sensors (pH, Ammonia, Dissolved Oxygen, Temprature and Turbidity) measure key environmental parameters to ensure real-time monitoring of the pond environment.
B) Middleware System
The main task of this system is to collect data from the automated environmental sensors in fish ponds and make computational decisions. These decisions include estimating fish biomass and detecting fish behavioral patterns to identify both infectious and non-infectious diseases in the ponds.
C) Remotely Operated Underwater Vehicle
The ROUV , equipped with cameras, captures images and videos and provides biological data using computer vision and algorithms to estimate the total fish biomass. It also monitors actual fish movement and compares it with normal movement patterns on which the AI model was trained to detect infectious and non-infectious diseases.
D) Automated Feeding Device
The automated feeder receives the appropriate feeding schedule and determines the feeding in real times through the middleware system to ensure proper feeding and.prevent mortality of tilapia fish
