Alexandra Kolosova

Globally, fish have a market value of 150 billion EUR per year. In addition, the implementation of the European Water Framework and Habitats Directives underscores the necessity for long-term environmental monitoring across the European Union. Economically and ecologically significant fish species, such as Salmon and the critically endangered European Eel are both native to Estonia, and their life cycles require migration from marine to freshwater environments. Current academic solutions for fish monitoring are too slow and expensive, and commercial solutions with AI still rely on manual processing of thousands videos at each location. The "AquaID" project aims to develop viable systems capable of automatically detecting and counting wild fish with significantly enhanced performance. This will be achieved through the utilization of custom hardware and underwater artificial intelligence methods developed at TalTech, in collaboration with international academic and commercial partners.

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.

Data has become the most valuable resource for the automation and optimization of tasks arising both in the private and public spheres. The proposed research area/project aims at strengthening both the synergy and quality of the current research of Taltech in this area, while significantly enhancing the capabilities of Uni to cooperate with Estonian industry and public sphere by joint work, consultations, continuous and regular education. The focus of the project is on using machine learning for data science: ML, in particular deep learning, has shown the most promise in advancing the capabilities of future software systems and empowering the whole business of software development. The concrete goal is to increase the manpower and competence in machine learning, while enhancing and cooperating with the existing areas of data science like data and rule mining, data semantics and knowledge representation, natural language data queries, data integration, statistics and data management.