Data intelligence to ensure quality of recycled materials
The European Reconstruct project is testing data intelligence models at the Sorigué recovery plant in Tarragona to track the traceability of recycled materials.
The Sorigué recovery plant in Botarell, Tarragona, is being used as a test site to develop a data intelligence model that adds value to recycled materials as part of the European Reconstruct research project.
This innovation project funded by the European Union in which Sorigué is one of the partners aims to leverage construction waste to produce low-carbon components that can be reused in new building projects. The Institute of Construction Technology (ITeC) is leading the consortium made up of the 16 organisations from five countries involved in the project.
Data intelligence
Reconstruct is currently taking its first steps towards developing artificial intelligence-based sourcing models for collecting and characterising construction waste. It is testing out compiling, designing and validating these AI models at Sorigué’s plant and at a facility in Barcelona belonging to Comsa.
At this plant, Sorigué manages various types of construction waste from concrete and bricks to bituminous mixtures and minerals. Each waste is sorted, cleaned and processed for maximum value by harnessing industrial processes and state-of-the-art technology. The outcome is a sustainable and cost-effective line of recycled aggregates that delivers a wide range of applications.
The site’s features are ideally suited to the needs of the Reconstruct project as it allows for training artificial intelligence for automatic material flow recording.
Visit to the test sites
In May, visits were made to both the Sorigué plant and the Comsa site during the experimental campaign conducted by Italy’s Marche Polytechnic University (UNIVPM).
These visits featured a tour of the facilities and on-site tests. Other project partners including ITeC, Brunel University of London, Iris Technology Solutions, Symbiosis Industrial and ICCS were in attendance.
“‘The experimental tests were pivotal to successfully design future long-term sensor systems in areas of interest for construction and demolition waste management and sorting operations and also for designing artificial intelligence models to quantify and characterise CDW,” says Gloria Cosoli, postdoctoral fellow in Industrial Engineering and Mathematical Sciences at UNIVPM.
This new stage of Reconstruct is crucial to ensure best reuse of materials that would otherwise be discarded and also for identifying and locating where these resources can be sourced to find better circularity pathways in the industry.