Contact person
Mikael Mangold
Forskare
Contact MikaelPrediction of hazardous materials in the building stock though machine learning
Hazardous materials (e.g. asbestos and PCB) is a health risk and when encountered during renovation processes increases costs and lead times. In this project information about where hazardous materials have been found will be gathered, systematized and connected to comprehensive registers about the building stock. Machine learning makes it possible identify patterns and make predictions of where hazardous materials might be found in the entire Swedish building stock.
Wu, Pei-Yu, Kristina Mjörnell, Mikael Mangold, Claes Sandels, and Tim Johansson. 2021. “A Data-Driven Approach to Assess the Risk of Encountering Hazardous Materials in the Building Stock Based on Environmental Inventories.” Sustainability 13 (14): 7836.
Wu, Pei-Yu, Kristina Mjörnell, Claes Sandels, and Mikael Mangold. 2021. “Machine Learning in Hazardous Building Material Management: Research Status and Applications.” Recent Progress in Materials 3 (2).
Summary
Project name
Prediction of hazardous materials
Status
Completed
Region
Västra Götaland Region
RISE role in project
Coordination and execution
Project start
Duration
4 years
Total budget
4.5 MSEK
Project members
