Machine Learning for the prevention of occupational accidents in the construction industry

Reference number
Coordinator Mälardalens högskola - Akademin för innovation, design och teknik, Västerås
Funding from Vinnova SEK 182 574
Project duration November 2018 - April 2020
Status Ongoing
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


External links

The project description has been provided by the project members themselves and the text has not been looked at by our editors.

Last updated 27 October 2018

Reference number 2018-04352

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