AQUAVISION:AI POWERED FISH SPECIES DETECTION AND DISEASE ANALYSIS

Abstract: Misclassification of fish species presents a critical challenge to aquaculture, impacting operational efficiency, biodiversity conservation, and sustainable fisheries management. Accurately identifying fish species is essential for preserving ecological balance and enhancing breeding programs. Similarly, delayed detection of fish diseases can lead to devastating consequences, including mass fish deaths, substantial financial losses, and heightened risks of disease outbreaks in aquaculture farms. Traditional methods for identifying fish species and diagnosing diseases largely depend on manual observation, which can be slow, prone to errors, and impractical for large-scale operations. To address these limitations, our system employs an advanced, automated approach to streamline fish species classification and early disease detection. By leveraging cutting-edge image processing and intelligent pattern recognition techniques, the system delivers fast and accurate results. Enhancements in image quality facilitate superior feature extraction, which improves classification and detection outcomes. This automation minimizes reliance on manual inspections, reducing the likelihood of human errors while enabling aquaculture farmers to monitor fish health more effectively. By integrating intelligent technology into aquaculture management, this solution aims to transform fish farming practices. It supports sustainability by promoting healthier aquatic ecosystems, reducing disease-related losses, and contributing to more efficient and eco- friendly fish farming operations.

Keywords: Artificial Intelligence (AI), Deep Learning, Aquaculture, Fish Species Classification, Fish Disease Detection, Convolutional Neural Network (CNN), Transfer Learning, Computer Vision, Image Processing, EfficientNet, MobileNetV2, Grad-CAM, Explainable AI (XAI), Fish Health Monitoring, Smart Aquaculture, Disease Analysis, Machine Learning, Image Classification, Aquaculture Management, Automated Detection, Flask Web Application, SQLite Database, Real-Time Monitoring, Fish Farming, Aquatic Disease Detection.