Problem Statement Title Detecting oil spills at marine environment using Automatic Identification System (AIS) and satellite datasets Description Background: The impact of oil spills at sea is multifaceted, affecting the environment, economy, public health, and society at large. Preventing spills through stringent regulations, improved technology, and better safety practices is crucial to mitigate these devastating effects. Automatic oil spill detection using Automatic Identification System (AIS) and satellite datasets is essential for environmental protection, public health and safety, economic stability, regulatory enforcement, technological advancement, and operational efficiency. This approach enables timely and effective responses to oil spills, mitigating their impact and promoting sustainable maritime practices. Integrating AIS and satellite datasets significantly enhances the early detection of oil spills at sea by combining real-time vessel tracking with advanced remote sensing capabilities. Detailed description: The automatic identification of oil leaks and spills from ships and vessels using AIS (Automatic Identification System) and satellite datasets involves integrating real-time tracking and advanced remote sensing technologies to monitor marine environments effectively. AIS provides crucial information such as the vessel's unique identifiers (IMO number, call sign), real-time positional data (latitude, longitude), speed over ground (SOG), course over ground (COG), heading, type of vessel, dimensions, draught, destination, estimated time of arrival (ETA), and cargo details. To detect a vessel in distress, AIS data have to be monitored for anomalies, such as sudden changes in speed or course, erratic movements, or unexpected stops. These irregularities can signal potential distress, prompting further investigation. Once detecting the distress, the same location/vessel have to be monitored using space borne satellite datasets for oil leaks, orientation of the vessel and its change in datum. The integration of AIS data with satellite datasets, enhances the ability to detect oil leaks early and can respond to situations efficiently. As far as study area, any of the below options may be considered. Option 1 : off Mumbai: https://drive.google.com/file/d/1HUisEfMA20ilODdeoRYVneG2i1ZbRBNB/view?usp=drive_link Option 2 :Gulf of Mexico – North American waters: https://drive.google.com/file/d/1_iEcojaZNaezOqKwxHtCenjgOW58lPgA/view?usp=drive_link Expected solution: Automated oil spill detection system for early detection of oil spills A software/tool/system to be developed for detecting oil spills/vessel in distress with suitable methodology that involves programming in python. The tool/system should detect the anomalies in AIS around the vessel. The distress/anomaly zone has to be monitored for oil spills using Satellite datasets. This can help in early detection of oil leak from a ship or vessel. The information can be passed on to the regulatory authorities for quicker and efficient response.
RUN python main.py and upload images from src/uploads