Name: Dr Mengtian Yin
Academic Division: Civil Engineering
Research Group: Digital Roads for Future
Fellowship period: 15 June 2023 – 14 June 2026
Email: my424@cam.ac.uk
Research Interests
Dr Mengtian Yin's key research interests lie in the areas of construction automation, building informatics, and digital infrastructure management. Specifically, he likes to explore (a) conceptualization and knowledge modelling of digital twins for road infrastructure and (b) digital twin-enabled process automation for highway maintenance.
Strategic themes:
Design a conceptual framework of road digital twins for highway maintenance.
Architecture design and data modeling for digital twins using knowledge representation languages.
Implementation of road digital twins integrating key use cases for highway maintenance.
Deployment of graph databases, clouds, and APIs to enable future-proofing digital twin systems for highway operation and maintenance.
Research Project
Title: Mapping National Highway Requirements: Digital Twins for Road Operation and Maintenance
Theme: Digital Twins
Abstract: A digital twin (DT) for highway infrastructure has the potential to integrate fragmented assets and operational data for comprehensive management, analysis, and augmentation. However, there is a lack of a unified definition of road DT and standardised data models to specify the information requirements for DT-enabled highway maintenance processes. It is unknown what the basic features of a road DT are and what it can be used for in the maintenance of highway assets. To fill these gaps, this research project aims to explore the minimum viable products (MVP) of a road digital twin, including (a) data requirements and representations; and (b) system architecture and implementations. The objectives of this research are twofold. First, conceptualise the road DT and conduct data modelling for digital twin-based road inspection and maintenance, including the development of the Foundation Data Model (FDM) and Reference Data Library (RDL) for digital twins. Second, explore the appropriate DT cloud architecture in the context of road inspection and maintenance. This would begin with devising a technology-agnostic abstract layer that treats the DT as a graph, which may be implemented using any type of database. Then, different cloud databases will be compared to identify the optimal DT implementation strategies. Finally, the DT prototype will be evaluated in real-world use cases to assess its practical value.
Bio:
Dr. Mengtian Yin is a Marie Skłodowska-Curie Future Roads Fellow at the Department of Engineering, University of Cambridge. His research project focuses on the conceptualization and implementation of the minimum viable products (MVP) of highway digital twins, with product models and process models created and validated. He recently obtained his PhD in Real Estate and Construction at the University of Hong Kong. His PhD research was centered on the development of AI-driven Natural Language Interfaces (NLIs) for efficient data retrieval from Building Information Models (BIMs). This involved the creation of ontology learning and semantic parsing models based on language models and graph networks. He has experience transferring research innovations into industry applications. Dr. Yin was the technical director of the AutoBIM project at Hong Kong MTR Corporation, where he developed novel solutions for automatically transforming 2D mechanical, electricity, and plumbing (MEP) drawings and textual documents into BIM models with rich asset information. Currently, his research work has been published in several top peer-reviewed journals (Google scholar: https://scholar.google.com/citations?user=H2jn02YAAAAJ&hl=en&oi=ao) and has been awarded three Chinese invention patents.