Project description
Using real-time data to keep highways in shape
Highway maintenance today relies heavily on manual inspections. But this is a slow, costly process that can delay repairs and inflate expenses. As Industry 4.0 reshapes sectors with AI and digital twins, the challenge lies in acquiring sufficient data to monitor vast road networks without installing expensive sensors everywhere. Supported by the Marie Skłodowska-Curie Actions programme, the VSDT-HiDM project aims to solve this by tapping into sensor data from passenger vehicles, notably from Mercedes-Benz cars, to provide real-time updates on highway conditions. By integrating this data into digital twins, the project will develop decision-making tools tailored for highway operators, improving maintenance planning and efficiency. This approach promises to revolutionise how roads are managed.
Objective
Currently, highways, as one of the major financial community assets, predominantly rely on manual surveys by inspectors for their maintenance, followed by necessary repair actions taken by asset managers; a static process that causes significant delays and cost inefficiencies. As the world experiences its fourth industrial revolution, commonly known as Industry 4.0 (I4.0) practitioners are beginning to engage with I4.0 technologies like artificial intelligence (AI) and digital twins (DT). Such technologies are automating and digitizing previously analogue processes, enabling modern and sustainable asset management. However, their adoption is often based on big data, and the availability of such data for vast highway assets is a problem; deploying sensors across extensive highway networks is costly. To solve this, we propose using sensor data from passenger vehicles to monitor highway assets, serving as a link between I4.0 and highway maintenance. On the other hand, I4.0 will have limited value if they focus solely on building information modelling (BIM) and data storage. This requires an information-knowledge-action framework to plan long-term maintenance strategies, thereby realizing the economic value of information and achieving sector renewal. This project will: a) develop an interface to integrate sensor data from passenger vehicles into DT to access real-time updates on highway assets (data from Mercedes-Benz); b) propose a holistic model to support decision-making based on the updates. The model and surrounding findings will be transformed using co-design methods into a suite of industry-targeted tools tailored to the National Highways (NH) asset operators. I will move to University of Cambridge to complete this fellowship. Didimi will participate as an associated partner, providing access to proprietary data from Mercedes-Benz (MB) passenger vehicles and key point of contacts (POCs) from the pilot highway operator NH team and the maintenance team Costain.
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CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- social sciences political sciences political transitions revolutions
- engineering and technology electrical engineering, electronic engineering, information engineering electronic engineering sensors
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Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
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Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA)
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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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CB2 1TN CAMBRIDGE
United Kingdom
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