Intelligent sorting of construction waste

The construction and demolition industry is one of the world's largest producers of waste. Against the backdrop of growing requirements for sustainability and the circular economy, efficient waste management is increasingly coming into focus. Conventional sorting processes have their limits: they are personnel-intensive, error-prone and costly. Machine learning (ML) in combination with computer vision and robotics offers new approaches here. So far, however, there is a lack of empirical evidence that systematically compares the ecological and economic advantages of ML-based automated sorting systems with conventional methods. The study "Machine learning-based automated waste sorting in the construction industry: A comparative competitiveness case study" by Finnish scientists examines the extent to which MLAS can deliver better results in terms of recycling rates and material purity as well as in terms of cost structure. The study was published in "Waste management".