Project objectives
The aim of the TATTI project is to improve occupational safety in companies and other working environments in the Satakunta region by developing and piloting solution models based on artificial intelligence, robotics, machine vision, and automated identification technologies. The project particularly supports safety-critical sectors such as manufacturing, the food industry, and the social and healthcare sector, where the development of occupational safety has a direct impact on employee wellbeing, operational efficiency, and organisational competitiveness. At the same time, the project lowers the threshold for regional companies to adopt new technologies for improving occupational safety and strengthens their capabilities to implement predictive and automated safety practices.
A key objective of the project is to shift occupational safety management from manual and reactive approaches towards automated and predictive safety management. The goal is to reduce workplace accidents and safety deviations, support safety in multicultural work communities, strengthen the region’s security of supply, and create new business and RDI opportunities around safety technologies. The project also establishes a lasting foundation for research, development, and innovation collaboration in automated occupational safety between SAMK, regional companies, and other stakeholders. This ensures that the solutions and practices developed during the project can be embedded into the region’s established development activities and later expanded to new sectors and international contexts.
Contact information:
Project manager
Ville Konttinen
tel. 050 434 5527
ville.konttinen@samk.fi
Project activities
The project begins with an assessment of the current state of occupational safety, critical risks, and development needs in collaboration with companies and experts in the Satakunta region. The assessment identifies working environments where AI- and automation-based solutions can improve safety, and is complemented by workshops in which key safety challenges are defined. Particular attention is also given to language and cultural differences related to an international workforce.
Based on this assessment, the project will design and implement 3–5 solution models aimed at improving occupational safety, utilising artificial intelligence, machine vision, automated identification, and robotics. These solutions may, for example, monitor the use of personal protective equipment, detect safety deviations in real time, track risk factors in the working environment, and generate automatic alerts in hazardous situations.
The solution models will be piloted in real working environments, particularly within manufacturing, the food industry, and the health and social care sectors. The pilots will evaluate the usability, effectiveness, cost-efficiency, and applicability of the solutions across different types of organisations. Based on these results, the solutions will be further developed and their broader scalability assessed.
In addition, the project will organise workshops, demonstrations, and communication activities to disseminate the results to regional companies and other stakeholders. The aim is to ensure that the solution models and best practices developed during the project become embedded in regional development activities even after the project has ended.
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