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Digital, autonomous, Intelligent and Synchronous system for Continuous identification, Optimization and Value Extraction of Resources from the end-of-use built environment

Project description

Building a future of sustainable construction

Today’s deconstruction of buildings poses a challenge: how can we efficiently reclaim valuable materials while minimising environmental impact? To answer this question, the EU-funded DISCOVER project aims to revolutionise this process with an autonomous, intelligent system for identifying and analysing materials in end-of-life buildings. By harnessing robotics, AI algorithms, and continuous scanning technology, DISCOVER will provide building models with all the necessary information (promises) to optimise resource use, reduce environmental footprints, and promote circularity in construction. This approach transforms demolition sites into material banks and pioneers the integration of digital twins, (and) multi-criteria assessments and best demolition practices for sustainable urban development. With trials across Belgium, Poland, Portugal, and Spain, DISCOVER is set to reshape the future of construction practices across Europe.

Objective

DISCOVER aims to develop an autonomous, synchronous, continuous and intelligent identification and data analysis system for materials and products in existing end-of-life built works. The proposed approach will provide key stakeholders, including academia research performers, along with construction industry representatives, with data-driven insights to make deconstruction more efficient, optimise the use of resources, improve the environmental footprints and enhance the circularity of construction and demolition, unlocking the potential of end-of-life built works, which will become material banks. The expected outcomes include an autonomous robotic platform coupled with continuous identification tools to scan built works and provide synchronous quantitative and qualitative data from different materials, including complex and concealed elements. Artificial intelligence algorithms will allow a rapid analysis of the properties and characteristics of components, and feed the automated scan-to-BIM model creation. The multi-dimensional BIM, including selective demolition processes, labour productivity, and technical planning, will become a Digital Twin of the demolition site optimised by social, economic, and environmental multi-criteria assessments. This approach will highly contribute to significantly increasing the supply of traceable and sustainable construction materials and products for enhancing their wider market acceptance, following the waste hierarchy. The social impacts of digital transformation in the construction sector will be considered, and also new professional development tools for the relevant stakeholders will be proposed. The system will be tested in 4 different real demolition sites (Spain, Portugal, Poland and Belgium), offering a complete range of built work typologies and wide geographical coverage to demonstrate the replicability potential of DISCOVER, increasing the project dissemination capacity and awareness among the construction sector.

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Topic(s)

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HORIZON-RIA - HORIZON Research and Innovation Actions

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Call for proposal

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(opens in new window) HORIZON-CL4-2023-TWIN-TRANSITION-01-TWO-STAGE

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Coordinator

UNIVERSITAT POLITECNICA DE CATALUNYA
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 1 208 008,75
Address
CALLE JORDI GIRONA 31
08034 Barcelona
Spain

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Region
Este Cataluña Barcelona
Activity type
Higher or Secondary Education Establishments
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Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

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Participants (13)

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