Airborne Sensor Systems. Real-time detection, verification and classification of type of oil in the water. For use on UAV (drones), helicopters, and airplanes.
We designed the ELF OWL™ with aerial operations in mind, particularly coastal monitoring from the air, but also for ocean monitoring. The construction of the sensing laser (a customized model of the excimer laser) was redesigned for weight minimization and lower electromagnetic interference to other electronics equipment onboard of a UAV.
The principal layout of AIR OWL™ consists of modules for oil spill sensing from the air, and detection of the echo-signal with following analysis.
A Real Time Controller (RTC) is responsible for proper handling of simultaneous and time critical events, and a Space & Time Awareness Module (STAM) serves for binding each spectrum to GIS database. The AIR OWL™ display data in a map that adds qualitative and quantitative information on oil pollution for real-time observation and decision making.
The AIR OWL™ display qualitative and quantitative data on oil pollution in real-time. An Onboard Mission Management System (MMS)serves as an external operator console integrating the basic control of the AIR OWL™ and data reception and visualization. The MMS sends the commands and receive the observation data layer for the full picture.
Algorithms, convolutional neural networks and deep learning models can assist in the analysis of satellite images for early detection. Prediction models can provide useful event forecasts and help in the cleanup and handling process.
Monitor large areas quickly, identify subtle patterns and provide real-time updates for immediate action. By utilizing these models we can predict oil spill movement based on factors like ocean currents and wind, allowing for proactive measures. Machine learning can also suggest the best cleanup methods and improvements by analyzing past operations and environmental conditions.
When developing predictive models and AI systems using machine learning, access to relevant, high-quality sensor data is essential for accurate analysis and meaningful correlations.
Sensor data are visualized in real-time via OWL™ MAP. Combine data with other layers of information, e.g. automatic identification of ships (AIS) and weather data.
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“The operational use of this technology has the potential to improve the verification of suspicious oil features, the detection of oil in the water column, reducing the need for conventional laboratory analysis.”
Cristina Maria Bentz
Ocean Visuals AS
Oslo Science Park
Gaustadalléen 21, 0349 Oslo - Norway
+47 21 50 71 00
post@oceanvisuals.no