Jürgen Soom

This project is based on the new paradigm of "flow as information", a groundbreaking approach for underwater sensing of multiscale flows in Nature. It will lead to new, optimized devices and methods to measure, classify and explore the underwater environment when traditional methods are too expensive or simply do not work. Flow as information is inspired by aquatic animals who have evolved advanced sensory systems which combine sensing and information processing into a single framework. The proposal will advance TalTech's underwater sensing technologies from working prototypes (TRL3 to TRL5) to tests in relevant operational environments (TRL6), and support technology transfer to Estonian and international firms. These devices and methods will provide researchers, industry and authorities with new and reliable sources of flow data during extreme climate and weather events where conventional devices fail and when critical infrastructure is at risk, such as during storm surges and floods.

The aim of this applied research is to improve the usage of radars for autonomous navigation of unmanned land vehicles in off-road scenarios. As radars use radio waves for their operation, they have several advantages over optical sensors such as cameras and lidars. For example, weather phenomena such as snow, rain, fog, etc. have much less impact on the performance of radars than optical sensors. Also, radars are not disturbed by dirt and other small debris, making them an ideal sensor for off-road navigation. However, radars do have one major drawback: the resolution of the point cloud they generate is significantly lower than that of, for example, lidars. This research will explore ways to improve the quality of data from radars using artificial intelligence and other appropriate algorithms.

With a current market value of 150 billion EUR/year, fish are among the most economically valuable species on the planet. The implementation of the European Water Framework and Habitats Directives ensure that long-term environmental monitoring is in demand across the EU. Economically valuable fish species include Salmon and critically endangered European Eel (native in Estonia). They must migrate from the sea into rivers as part of their lifecycle. Existing solutions for fish monitoring are expensive, requiring manual processing of 1000s of hours of video for each location. The "ExoFish" project will provide a highly needed and valuable commercial system capable of automatically detecting and counting wild fish with significantly better performance at 50% of the cost of existing technologies, by utilizing custom hardware and underwater artificial intelligence methods developed at TalTech in collaboration with the Estonian Environmental Agency and international commercial partners.