Projects

The project aims at validating the contemplated objectives and operation model of the Copyright Infrastructure Task Force (CITF) at hand of components of the AI and Copyright Use Case, and paving the way for the CITF to potentially become a Use Case Group of the Europeum EDIC, focusing on the interoperability and trustworthiness of rights data exchanged between rightsholders and rights users as well as among rightsholders.

The project aim is to build competencies in digital transformation for higher education institutions in Southeast Asia by developing digital strategic plan, improve the quality of learning and teaching methodologies and pedagogical approaches for digital learning.

SMART-PL is a 3-year project, focused on introducing a model of personalised learning, based on the virtual learning environment of Intellectual Tutoring "Learning with No Limits". Intellectual tutoring is a set of learning tools: SMART online platform for virtual personalised learning and formative student assessment; сo-working centre with equipment for organising hybrid learning, which increases the educational process's efficiency and gives both teachers and students more opportunities.

The general objective of this project is to create an "umbrella architecture" based on existing EBSI services. The architecture builds the basis for the realization of traceability application scenarios. Furthermore, TRACE4EU focuses on engagement with pan-European stakeholders and promotion of recommendations for further development of the EBSI eco-system.

One of the challenges that this demonstration project sought to solve was the robotic production of acoustic panels to reduce the time needed to manufacture these. The demonstration project tested the robotic screwing process for acoustic panels of different configurations, taking into account the different dimensions of the panels, the number of screws to be installed and their installation. This demonstration project linked robotics (UR10 collaborative robot), automation (screw feeder, automatic screwdriver, intelligent jig), AI tools (digital twin workstation, machine vision tools, simulation of robot work trajectory). The solution took into account the company's specific production processes and the requirements for acoustic panel parameters, as well as the possibilities for implementing fully automated production in the company or for deployment in other companies in the sector. Results of the demonstration project: realization of the product assembly operation, development of the assembly cell concept, selection of a suitable robot for the assembly operation, selection of the tools, simulation and testing, data collection, analysis and verification of the results.

The novelty of the demo project is the joint handling of non-form-retaining textile materials and solid frame materials by intelligent and flexible robot/assembly robot stations. The active control method detects the performance of the robot’s working organs and checks the quality assurance data with the real ones. Through the analysis and pattern recognition of the collected data, artificial intelligence must be able to make changes to the drafting process. During testing, data will be collected and algorithms created for artificial intelligence to make decisions.

In the course of this project, the concept and prototype of a device for measuring the shadow line of real 3D objects was created and tested both in a test and real environment. The system is used to prepare the most suitable transport packaging for the safe packaging of the objects in question. At present, the production process contains too much manual labor and the level of automation needs improvement. The created system allows to reduce the volume of manual work and also to increase the quality of work (avoid errors and increase accuracy).

The project "Testing of the Applicability of an AI-based Optimization Model for Production Processes using a Digital Twin of the Factory" focuses on creating digital models of the factory and using AI to identify and mitigate bottlenecks in production processes. By using Siemens Plant Simualtion software, the project simulates the factory's actual process times to create a digital twin, enabling production optimization without disrupting real manufacturing. The project utilizes an AI optimization model based on machine learning and data analysis to improve production throughput and resource efficiency.

The project aims to explore the adoption of open-source platforms for monitoring production lines and to develop a solution for monitoring Balsnack waffle production line. The objective is to extend the solution to other production lines after successful validation. The project created an integrated production monitoring solution that combines machine vision-based quality control with inputs from sensors. Machine vision facilitates visual quality control and product identification. Product identification will automatically provide the system with preset values that will be compared with inputs from sensors.

The purpose of this project is to address the problems related to expert workforce in the field of diagnosis, monitoring, and maintenance of the power systems and related components in the partner countries by bringing innovation in higher education teaching and learning methods in order to fill the expertise gap and enhance its relevance for the labour market and the society as a whole. The project will help Nepal and Bhutan to produce in-house human resources in the field of condition monitoring of power equipment making both the countries independent of external consultants. The main objective of the project is to implement real problem based teaching and learning methods in the curriculum of HEIs of the partner countries. This is possible thanks to the expertise and know how of the EU partner Universities and their long term teaching in this field. The project will also help the EU partners to renew their education in this field and build a sustainable flow of students in both directions

The project provides a comprehensive assessment of Estonia’s wood resources and the technological pathways for their high-value valorisation. It supports national goals to expand the bio-based economy and advance climate-neutral development. The project evaluates the availability of wood suitable for mechanical, microbiological, and chemical processing up to 2050, analyses relevant TRL 6–9 technologies, and identifies development directions that fit Estonia’s resource base, workforce capacity, and strategic priorities. The study maps domestic and potentially importable wood resources, considering species, assortments, environmental restrictions, and an annual harvesting volume of 10 million m³. It assesses resource availability across different forest owner groups, including the State Forest Management Centre (RMK), private forest owners, and industry-related large owners. It provides a concise overview of chemical and microbiological wood valorisation technologies and related product groups across technology generations. The analysis evaluates suitable fractionation and end-product manufacturing technologies for Estonia, taking into account resource scale, supply chain feasibility, human capital, investment needs, and climate policy obligations, including CO₂ sequestration and LULUCF methodology. It also examines additional resource requirements—such as other bio-based feedstocks, water and energy demand, and infrastructure needs—arising from the selected technological pathways. The project reviews current and future demand for engineering, chemical, and wood chemistry experts, drawing on OSKA analyses, and assesses laboratory and R&D infrastructure needs in connection with the establishment of the Wood Valorisation Focus Centre and Metrosert’s Bio-refinery Development Centre. The results provide an integrated overview of Estonia’s strategic options for wood valorisation and offer recommendations for building a competitive, high-value wood-based value chain that strengthens the national bioeconomy and supports long-term climate objectives.

The aim of the project is to assess the fish compatibility of the newly developed pump and to compare the damage rates of the fish during passage to an existing pump in the Kudensee pumping station.

The RAC project, short for “Testing and validating a Robot Activity Coordinator to enhance the well-being of the elderly at care homes,” was to explore the potential use of a robot assistant in the daily operations of a care home. To achieve this, an application suitable needed to be adapted to enable the TEMI robot-assistant to move efficiently within the for Pihlakodu care home environment, communicate with residents, staff, and guests, and share information. During the project, usage scenarios for the robot as an activity coordinator were first tested through collaboration between Pihlakodu and TalTech IT College. Following this, the necessary application (RAC) was adapted to enable the robot to support activity coordinators in their work. A key focus of this demo project was the thorough testing and validation of the application and the robot in the day-to-day care work process at the Viimsi and Tabasalu care homes: the robots, named Pipi and Olle, moved around the care home sharing important information and daily news with residents, supported social interaction – especially for residents with limited mobility – through humour and games, and assisted guests with finding their way inside the facility. By using the robot in the role of activity coordinator, the project tested the potential of robotics and AI to address staff shortages in care homes – particularly in the care of elderly residents who, for various reasons, cannot participate in group activities and require a more personalized approach. It is important to emphasize that the goal of the robot as activity coordinator was not to replace the role of the human, but to help and enhance work processes. The primary objective of the RAC project is to elevate the quality of life for bedridden elderly residents in care homes. By introducing an AI enhanced robot application as an Activity Coordinator, the project aims to alleviate some of the workload of human care staff while enhancing the overall well-being and satisfaction of both the residents and staff. The success of the RAC demo project could prove to be a shift in implementing emerging technologies such as AI and robotics in elderly care, generating interest from other institutions in the healthcare and elderly care sectors, both in Estonia and abroad, where seeking solutions to improve healthcare and care services in the reality of ageing society.