Centre for environmental sensing and intelligence

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.

The project aims to redesign the current RAPID sensors to make them more fault-tolerant. This makes the testing of underwater sensor devices faster, easier, and more reliable. These sensors help researchers understand the physical conditions fish experience in hydropower plants. Currently, testing the sensors is slow and requires expert knowledge. This project will create a simple computer program that allows anyone to check the sensor's condition in just a few seconds. The results will help make future sensor systems more robust and easier to use in the field.