Integrating Digital Twin and Asset Management System for Enhanced Pavement Infrastructure Maintenance

Aligned with the “Future of AI Technologies in Maintenance Training & Education,” our paper illustrates the methodology needed to bridge the gap between technological advancements and effective training and education in pavement infrastructure maintenance, by developing a maintenance decision tool through the seamless integration of asset management systems (AMS) with digital twin technology (DT). This approach empowers decision-makers with accurate and efficient maintenance planning capabilities. In summary, our goals intricately intertwine with the future of Artificial Intelligence (AI) technologies in maintenance training and education, highlighting the need for upskilling and integrating technology-driven methodologies into the educational landscape. The efficient management of pavement infrastructure is crucial for ensuring safe and sustainable transportation networks. In this context, the integration of cutting-edge technologies holds immense potential to redefine maintenance practices. This paper delves into the integration of Digital Twin technology with Asset Management Systems (AMS) as a pioneering approach to optimize pavement infrastructure maintenance. Digital Twin technology, acting as a virtual replica of physical assets, has revolutionized the way infrastructure is monitored and managed [1]. Complementing this, Asset Management System (AMS) is a systematic process of maintaining, upgrading and operating assets, combining engineering principles with sound business practice and economic rationale, and providing tools to facilitate a more organized and flexible approach to making the decisions necessary to achieve the public’s expectations providing a systematic framework for effective asset maintenance [2]. This paper outlines merging of these two systems, yielding a methodology for developing a maintenance decision tool through the seamless integration of pavement management systems with digital twin technology. This approach empowers decision-makers with accurate and efficient maintenance planning capabilities Through a real case study conducted on a significant road segment in Jeddah Municipality, Saudi Arabia, the paper showcases the possible benefits of this integration. The case study explores data acquisition, manipulation, and modeling processes. The integration further facilitates advanced analytics, and maintenance decision planning. As the transportation industry seeks innovative solutions to enhance infrastructure sustainability, the integration of DT technology and AMS emerges as a promising avenue.