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Value-driven AI-enhanced Construction Waste Management

Project description

AI solutions for construction waste management

Construction waste (CW) has a significant impact on environmental sustainability. Despite high recovery rates, a considerable amount still ends up in landfills. With the support of the Marie Skłodowska-Curie Actions programme, the iCWaste project will promote sustainable construction by leveraging advanced AI technologies and waste management strategies. It will accurately assess construction waste, identify waste generation points, and develop effective management strategies, emphasising materials reuse and designs for disassembly. It will establish new indicators to evaluate efficiency and sustainability, create AI-driven decision-support systems for construction managers, and promote resilient construction in the EU and UK.

Objective

Construction waste (CW) is a significant issue for environmental sustainability and economic efficiency. In the UK, construction, demolition, and excavation waste made up 62% of the total waste generated, amounting to 137.8 million tonnes​. Across the EU, construction and demolition waste represented the largest waste stream, with 374 million tonnes recorded. While recovery rates are high, much of this waste ends in landfills or is repurposed in low-grade applications, highlighting the need for improved recycling quality to better align with circular economy principles that advocate for the reuse and recycling of waste. Effective management of construction waste not only supports sustainable practices but also contributes to achieving the UN Sustainable Development Goals (SDGs), particularly SDG 12, which emphasises responsible consumption and production.
Our research project is at the forefront of advancing sustainable construction by leveraging cutting-edge AI technologies and innovative waste magement strategies. The project aims to advance sustainable construction by leveraging AI technologies. It will precisely determine construction waste at the project level, identify waste generation points, and develop effective waste handling strategies. The project will also develop new KPIs for construction waste management to assess the efficiency of waste handling practices, resource utilisation, and project sustainability. Additionally, AI-driven decision-support systems will be developed to provide actionable insights for construction managers. The project emphasises sustainable construction practices, including materials reuse and building design for disassembly and reassembly. It will also establish guidelines, best practices, and policy frameworks to facilitate the adoption of sustainable construction methods across the industry. The project aims to catalyse a global shift towards resilient and sustainable construction in the UK, EU, and beyond.

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Programme(s)

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Topic(s)

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Funding Scheme

Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.

HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European Fellowships

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Call for proposal

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(opens in new window) HORIZON-MSCA-2024-PF-01

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Coordinator

UNIVERSITY OF NORTHUMBRIA AT NEWCASTLE
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.

€ 276 187,92
Address
SUTHERLAND BUILDING COLLEGE STREET
NE1 8ST NEWCASTLE UPON TYNE
United Kingdom

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Region
North East (England) Northumberland and Tyne and Wear Tyneside
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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