Monitoring Marine Oil Spills with Smart Technologies

Marine and coastal ecosystems suffer greatly from oil spills. Accuracy constraints., problems with real-time monitoring., and environmental variability make early identification and mitigation difficult. AlexN et and LeN et architectures., two recent developments in deep learning., have promise for resolving these issues. These models look for complex patterns connected to oil slicks by analyzing satellite data and remote sensing photos. However., challenges including integration into real-time systems., computing demands., and data variability continue to exist. To improve the effectiveness and precision of oil leak detection., this study suggests a strong framework that makes use of deep learning. To enable real-time monitoring and prompt environmental responses., the system makes use of sophisticated neural networks and a large amount of data. This creative strategy has the potential to completely transform oil spill control., encouraging the preservation of ecosystems and efficient disaster prevention.