Detect and Segment Oil Spills Using Computer Vision

Oil spills pose significant environmental threats, affecting marine ecosystems and coastal communities, and cleaning them up is both challenging and costly. Leveraging computer vision offers a promising solution by enabling accurate measurements and assessments of oil spills through high-resolution aerial imagery. This technology allows experts to determine the most efficient cleanup methods based on the spill's characteristics, such as thickness and spread, using techniques like instance segmentation for detailed analysis. By training models with an impressive mean average precision score of 81.3% using datasets from Roboflow Universe, experts can effectively identify and classify different oil spill types. The integration of drones equipped with cameras and GSM modules further enhances this process by capturing and transmitting images for real-time processing, facilitating prompt and informed decision-making for spill mitigation. This comprehensive system not only improves resource allocation and cost-effectiveness but also supports ongoing monitoring and post-cleanup evaluations, ultimately leading to more effective environmental management and response strategies.