SOURCE-LINKED INTELLIGENCE

Vehicle-Sensing Digital Twin for Highway Maintenance Decision-Making

CORDIS · observation · Publication date unknown

ant 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

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recordType

award

status

SIGNED

region

EU

value

260347.92

unit

EUR