In many contexts – heavy work machines, emergency response, control centres – human operators face complex and demanding situations where their decisions can have far-reaching consequences on productivity, environment, and even human lives. In order to deal with such challenges, the operator needs full situational awareness, which can be achieved by sensing relevant visual data about the operating environment, refining it into mission-critical information, and presenting it in an immersive, intuitively comprehensible manner. This can be achieved by Immersive Visual Technologies (IVT) delivering ultra-realistic and interactive visual experience. The development of such IVT will be the main target of the ImmerSAFE project.
ImmerSAFE is a four year (2018-2021) H2020 Marie Sklodowska-Curie Innovative Training Network that brings together 9 beneficiaries and 5 partner organizations from Finland, Sweden, Norway, Croatia, Italy, and Switzerland, with the aim of training a new generation of multi-disciplinary experts, who have an understanding of the core imaging technologies, the requirements set to them by the safety-critical applications and who can account for the human user in the design of such systems.
The research will be supported by an extensive training program consisting of webinars, training schools and ImmerSAFE tech days. At the end of the project, the newly trained experts will be able to seize the great opportunity for innovations offered by the emerging field of IVT for Europe’s high-tech industries.
|First Name||Last Name||Title|
|Soheila||Sheikh Bahaei||Doctoral student|
|Gunnar||Widforss||Senior Project Manager|
|Taufik Akbar||Sitompul||Industrial Doctoral Student|
A novel physiological-based system to assess drivers’ stress during earth moving simulated activities (Dec 2022) Daniele Bibbo , Moses Mariajoseph, Barbara Gallina, Marco Carli Artificial Intelligence (Section of Electronics) (AI-Electronics)
Towards Qualitative and Quantitative Dependability Analyses for AR-equipped Socio-technical Systems (Nov 2021) Soheila Sheikh Bahaei, Barbara Gallina 6th International Conference on System Reliability and Safety (ICSRS-2022)
A Metamodel Extension to Capture Post Normal Accidents in AR-equipped Socio-technical Systems (Sep 2021) Soheila Sheikh Bahaei, Barbara Gallina 31st European Safety and Reliability Conference (ESREL-2021)
A Case Study for Risk Assessment in AR-equipped Socio-technical Systems (Jul 2021) Soheila Sheikh Bahaei, Barbara Gallina, Marko Vidović Journal of Systems Architecture (JSA, 114)
Using Artificial Neural Network to Provide Realistic Lifting Capacity in the Mobile Crane Simulation (Jun 2021) Simon Roysson , Taufik Akbar Sitompul, Rikard Lindell 22nd Engineering Applications of Neural Networks Conference (EANN 2021)
|ACADEMY OF THE NATIONAL FIRE CORPS (ISTITUTO SUPERIORE ANTINCENDI)||Academic|
|NORWEGIAN UNIVERSITY OF SCIENCE AND TECHNOLOGY||Academic|
|UNIVERSITÀ DEGLI STUDI ROMA TRE||Academic|
|UNIVERSITY OF HELSINKI||Academic|
|University of Zagreb Faculty of Electrical Engineering and Computing||Academic|
|VTT RESEARCH CENTRE OF FINLAND LTD.||Academic|
|FORUM FOR INTELLIGENT MACHINES RY||Industrial|