AIML-Powered-Ship-Hull-Fouling-Detection-PS1

https://drive.google.com/file/d/1gJeY_0Cserqs8jcI62hPafPQ03h-c7dB/view?usp=drive_link
https://docs.google.com/presentation/d/1cg_6AACZJr25WQRKjrUkleRDdS7GZsOR/edit?usp=drive_link&ouid=107786314084603150995&rtpof=true&sd=true


This project introduces an AI-powered system for ship hull fouling detection, classification, and maintenance prediction. Biofouling, caused by the accumulation of organisms such as algae, barnacles, and slime on submerged hulls, leads to increased drag, higher fuel consumption, and elevated CO₂ emissions, resulting in significant economic and environmental costs. Conventional inspection methods are often manual, expensive, and error-prone, which highlights the need for an intelligent and automated approach. Our solution integrates underwater ROVs equipped with RGB and UV cameras to capture high-resolution, geo-tagged images of the ship hull. These images are preprocessed through distortion correction, noise removal, and normalization to enhance clarity and consistency. Deep learning models such as CNNs and U-Net are then applied for image segmentation to detect fouling regions, followed by classification into fouling types (algae, barnacle, slime) and growth stages (early, medium, advanced). The system computes a fouling density index and assigns a risk score to quantify severity in terms of drag penalties, fuel efficiency loss, and emission levels. In addition to detection, predictive maintenance forecasting is employed using machine learning models to estimate fouling growth trends and recommend optimal cleaning schedules, enabling cost-effective maintenance planning. The project also features 3D hull mapping and AR visualization, creating a digital twin of the ship hull with fouling hotspots overlaid for immersive and interactive inspection. Finally, automated reports and real-time alerts provide actionable insights to ship operators and fleet managers, ensuring proactive maintenance and sustainability. By combining AI, predictive analytics, and AR visualization, this system delivers a comprehensive, scalable, and eco-friendly solution for maritime industries, reducing operational costs while supporting greener shipping practices.