Machine Learning for the prevention of occupational accidents in the construction industry
|Coordinator||Mälardalens högskola - Akademin för innovation, design och teknik, Västerås|
|Funding from Vinnova||SEK 182 574|
|Project duration||November 2018 - April 2020|
|Venture||Personal mobility between societal sectors|
|Call||Funding for staff exchange and artificial intelligence (AI)|
Purpose and goal
The collaboration aims at strengthening NCCs activity on developing a system for the prevention of occupational accidents. Through a newly established collaboration with Mälardalens University (MDH), it is envisioned to strengthen the development of a machine learning application. This is done through the contribution of Associate Professor Shahina Begum. She will contribute, support and critically scrutinize the development activity within NCC. At a time MDH can develop its competence within practical applications of AI.
Expected results and effects
Occupational accidents continue to be a problem in the building sector and even a minor reduction would imply remarkably better productivity in NCC and reduced health care costs for society. NCC has registered a large number of accidents and incidents. And the research in accidents has developed advanced causation models. These two elements constitute an appropriate basis for a machine learning system. MDH will support a series of important steps in the machine learning systems development for the prevention of occupational accidents.
Planned approach and implementation