Name: Dr Varun Kumar Reja
Academic Division: Civil Engineering
Research Group: Digital Roads for Future
Fellowship period: 15 June 2023 – 14 June 2026
Email: vkr25@cam.ac.uk
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Strategic Themes Infrastructure Management Supported by Digital Twins Creating virtual replicas of physical infrastructure, such as buildings, roads, bridges, or utility systems, using advanced technologies like sensors, AI, and IoT. Digital Twin Integration for Circular Construction Investigate the use of digital twins in circular construction automation to improve material tracking, waste reduction, and optimize resource allocation throughout the construction lifecycle. Computer Vision Based Infrastructure Assessment Using advanced image processing / point cloud processing techniques to analyse and evaluate the condition and performance of various physical infrastructure, such as roads, bridges, buildings, and utility systems. |
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Research Project Title: Mapping National Highway Requirements: Digital Twins for Road Operation and Maintenance Theme: Digital Twins Abstract: Highway digital twins have emerged as powerful tools for asset maintenance, allowing for real-time monitoring and predictive analysis of infrastructure conditions. However, establishing the information requirements to implement these digital twins effectively remains a critical challenge. This research addresses this gap by identifying and delineating the essential information requirements to optimise highway digital twins for asset maintenance. The methodology employed in this research involves a comprehensive approach that combines both quantitative and qualitative techniques. Initially, a thorough review of existing literature on highway digital twins and asset maintenance was conducted to identify standard practices and emerging trends. Subsequently, interviews and surveys were conducted with relevant stakeholders, including highway authorities, engineers, and technology experts, to gather insights into their information needs and preferences regarding digital twins. Data analysis techniques such as content analysis and thematic coding were then employed to distil critical findings and identify recurring themes. Several essential information requirements for highway digital twins emerged through synthesising literature review findings and stakeholder input. Our model for establishing information requirements is based upon multiple road assets, each having their own maintenance stages influenced by several factors, and these factors are modelled based on time-stamped information requirements. By delineating these requirements, highway authorities and infrastructure managers can better harness the potential of digital twins to improve maintenance practices, enhance operational efficiency, and ultimately prolong the lifespan of highway assets. Moreover, the emphasis on interoperability and data standardisation highlights the need for collaborative efforts and industry-wide standards to ensure the seamless integration of digital twin technologies into existing infrastructure management frameworks. Further research and development in this area are essential to address evolving challenges and capitalise on emerging opportunities in intelligent infrastructure management. Alignment with SDG: This research contributes to SDG 9: Industry, Innovation, and Infrastructure and SDG 11: Sustainable Cities and Communities. Project TRL: The current research is positioned at a TRL 4-5, focusing on validating key findings through controlled environments and stakeholder engagement. Acknowledgement of Data and Collaborations: This research utilises the CAMHighways dataset, supplied for experimental purposes. Additionally, qualitative data has been gathered through interviews with experts from highway authorities and industry professionals.
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