| Abstract Submission No. | ABS-4.1-0042 |
| Title of Abstract | NeelaNetra: Fisheries Intelligence in the Indian EEZ |
| Authors | Joel Peter Joseph*, Dr. Madhu V R |
| Organisation | Govt Model Engineering College |
| Address | F1 Prs grace Trivandrum, Kerala, India Pincode: 695003 E-mail: peterjoeljoseph@gmail.com |
| Country | India |
| Presentation | Oral |
| Abstract | India's fisheries sector sustains over 28 million livelihoods and contributes nearly 8% of global fish production, making it a critical driver of the nations Blue Economy. However, the rise of Illegal, Unreported, and Unregulated (IUU) fishing threatens resource sustainability, undermines governance, and poses risks to maritime security. Traditional monitoring systems struggle to integrate diverse vessel and environmental data, limiting effective detection and policy support.This work presents NeelaNetra, an AI-powered framework that leverages Global Fishing Watch AIS data for fisheries intelligence within India�s Exclusive Economic Zone (EEZ). The system integrates XGBoost for vessel and gear-type classification, ResNet for AIS trajectory analysis, and bathymetric shapefile visualization to estimate fishing effort and detect unauthorized activity. By fusing heterogeneous datasets, NeelaNetra enables real-time monitoring, and would help in enforcement, and will guide in evidence-based policymaking. The frame work can help strengthen marine governance and support long-term sustainability in the Blue Economy through data-driven fisheries management. |
| Keywords | Fisheries governance, Blue Economy, IUU fishing, AIS data, XGBoost, ResNet, Vessel classification, Trajectory analysis, Bathymetric visualization, Fishing effort estimation, Maritime security, Data-driven decision-making. |