Oil spills detection
By collecting data from all available sources, primarily satellite images in different spectral domains, from general terrestrial sources such as weather data, air and water quality, and from user hardware - any type of unmanned vehicles (aerial, ground and water drones), a multidimensional dataset is created with time being the final dimension. Continuous analytics are performed on such a dataset, mainly supported by AI machine learning, searching for anomalies. Anomalies are defined as deviations from the standard long-term average for any point in space.
AI and machine learning create classification models that will gradually recognize the nature and properties of individual anomalies, thus assisting the end-user in making quick decisions about the actions to follow. Initially, the project starts with detecting the state of water surfaces, which can be the general state of the sea, such as cleanliness and temperature, detecting, for example, oil spills, monitoring vessels that are under the AIS system or not, detecting smugglers, illegal vessels, fish poaching and immigrants, security issues - pirate vessels, and finally, the defense sector, i.e., defining patterns and recognizing military vessels regardless of which country they belong to.
Finally, although satellite data may sometimes be slow to obtain, water surface analytics, due to the relatively low speed of object movement on it, still allow for time critical response – where response have sense. If unmanned vehicles with higher speed and spatial data sampling resolution are introduced into such scenarios (e.g., aerial drones), a higher level of promptness in anomaly recognition and response time improvement can be achieved.
In the ultimate scenario, multiple redundant communication channels and sensor systems (water, ground, air and space) would be used, and data would be distributed to cloud or cyber-secured solutions, depending on the required level of data security. This would involve replicative database servers and protected VPN/WAN solutions.
Anomaly search AI models would be continuously improved and, at some point, such models could be applied to terrain models, which would ultimately enable the creation of a universal solution that would not only protect the sea but also terrestrial critical infrastructure and cross-terrain mobility. Similarly, in the future, the satellite fleet is expected to expand, with greater precision, faster data availability, and a higher volume of various data of interest.
Using that approach, an increase in awareness of the quality of life, ecology and environment, and overall safety is expected.