Projects

Platform work is a growing form of employment in Estonia, impacting social security options, career paths, and traditional forms of employment. It is essential to understand the economic and social outlook of workers engaged in platform work and the future of this sector in Estonia, in relation to developments in the European Union. This interdisciplinary project, which brings together social scientists, legal scholars, and economists, offers insights into the field of platform work and its broader impacts on the Estonian economy through various quantitative and qualitative methods. The central outcome of the work is a scenario-based analysis of the potential future development of platform entrepreneurship in Estonia, including an examination of emerging risks and opportunities-, considering regulatory developments in Europe, macroeconomic trends, and technological advancements. It also considers the impact of different scenarios on society, including the potential increase in vulnerability. The report produced within the framework of the project, and the related activities carried out within the project are based on the need to understand platform work more broadly while also considering its potential impacts on the development of social security in Estonia.

The general objective of the EquiTech project is to enhance capacity of public authorities in Estonia and Lithuania in addressing risks of bias and discrimination in ADM procedures. This will be achieved by developing research, support materials, trainings and media campaign. This will be reached by: 1. Desk research on gaps in policies and legal frameworks on AI in Estonia and Lithuania together with mapping of potential risks of discrimination and bias in ADM systems deployed by Estonian public authorities. 2. Development of practical toolkits to address potential risks for discrimination and bias in design and deployment of ADM systems; 3. Capacity building with inclusion among project stakeholders and target groups through trainings, study trips, international conference and academic webinars; 4. Raising public awareness on the risks of discrimination and bias in public sector ADM systems. As a result, we will minimize the probability of discrimination and bias in Estonian and Lithuanian ADM systems and set an example to other member states, contributing to the national action plans against racism and strategies against antisemitism, anti-Muslim hatred and xenophobia, LGBTIQ-phobia and all other forms of intolerance.

The DEUCE Project aims at better enforcement of judicial decisions (judgments, authentic instruments, and court settlements) issued in the context of cross-border pecuniary claims. It particularly focuses on the creation of a Roadmap of the 26 EU Member

CREA3 aims to introduce Artificial Intelligence (AI) driven tools to assist EU citizens in resolving disputes by applying innovative game theoretical (GT) algorithms. To improve access to justice and interaction with the rule of law, we seek to develop a strategy that addresses harmonisation across digitalisation and predictive algorithms. This approach, which combines legal research with extensive text-mining techniques, is novel since it will explore the idea of testing and evaluating how well family law systems in six EU legislations adhere to the new forthcoming “Regulation on the digitalisation of judicial cooperation and access to justice in cross-border civil, commercial and criminal matters”.

The project focuses on the DAL technology developed at TalTech, which aims to purify Kraft lignin to a very low ash content (≤0.05%). DAL uses green solvents and has a simpler process than competing technologies. Within the project, the technology’s innovation readiness level (CRL and BRL) will be increased by collecting market feedback, developing a business model, and strengthening the necessary competencies. As a result, the commercialisation potential of the DAL technology will increase.

This project focuses on the development and integration of Extended Reality and existing digital tools to support advanced engineering education in manufacturing. The purpose of the XREN is to bring back the results of research activities in the field of digital manufacturing to the engineering students. Since, process modelling, analysis, virtual and augmented reality, as well as the role of the human workers in the factories have been among the main research topics in manufacturing. Therefore, the project aims to experiment, test and validate learning approaches based on XR technologies, focusing the attention on: • Development of a VR environment to support learning activities in the area of manufacturing, namely in the design and analysis of manufacturing systems. • Development of an AR approach to support learning activities in the area of mechanical design and maintenance process. • Develop approaches and methodologies to analyze and evaluate the learning mechanisms based on these technologies.

The project will develop a smart, adaptive electric drive that increases the energy efficiency and reliability of electric vehicles. The innovative solution combines artificial intelligence-based control with advanced sensor technology, allowing the drive to adapt in real-time to changes in traffic and road conditions. The project will produce a laboratory prototype, a user-friendly software solution for data processing, and comprehensive documentation that will simplify the implementation of the system.

The objective of the project is to develop a semi-industrial prototype of a milling and separation technology for the treatment of clothing, textile, and footwear waste, including waste streams containing plastic and metal fittings. The project scales up laboratory-developed technologies to semi-industrial level and establishes infrastructure for continuous process optimisation. The broader aim of the project is to support the principles of the circular economy, increase the value of textile waste, and advance research and development results toward a market-ready technology. The planned activities include engineering design, the development and integration of mechanical components, testing with various types of waste materials (including clothing, leather, plastics, and wool), as well as the evaluation of the technology’s reliability and separation performance. The creation of the prototype will help translate research outputs into practical application and will prepare the groundwork for subsequent technology licensing or product development.

Fish-AI is a real-time automatic video-based fish monitoring system developed by TalTech that automates reporting in accordance with EU requirements and significantly reduces labor costs. The system is compatible with various underwater cameras, detects different water conditions, and is able to adapt to them.

This project develops a new real-time computer vision system for underwater freshwater camera systems. The methods include edge fish detection as well as an automated server-based platform for fish species, size and migration behaviour. In addition to the hardware and software models, the project also provides a web-based user interface to configure, view preview images and videos, annotate, retrain and update computer vision models.

The project will develop a computer simulation model that will enable the assessment of fish passage conditions through hydroelectric power plant turbines. The use of simulations will significantly reduce the need for field tests, allowing for more efficient use of time and money and a broader analysis of scenarios.

A cloud-based digital health platform for private clinics in East Africa will be developed, focusing on optimizing workflows, monitoring chronic patients, and managing patient care. A distinctive feature of the platform is the combination of a mobile application and an SMS-based triage solution, allowing access for patients with limited digital capabilities. The product is being piloted in Kenya, where a shortage of doctors and a growing population create strong demand for efficient, labor-saving solutions. The solution is based on the logic of primary care digital models tested in Estonia, adapted to the local context.

The goal of the project is to develop and integrate a personal student assistant based on large language models (e.g. GPT) into the learning environment of Tallinn University of Technology (TalTech). The assistant will be connected to the university's Moodle learning environment and will be able to provide fast and personalized feedback, helping students with course completion and solving assignments.