Japan is facing the urgent challenge of aging infrastructure, amidst ineffective linking of on-site experience and expertise with vast amounts of digital data in maintenance operations. This is especially the case for bridges across Japan. With a large number of bridges constructed during the rapid economic growth period, aging simultaneously, extensive inspection data and repair histories have been managed disparately across paper ledgers or departmental systems thus far, leading to inadequate integration between the experience of skilled engineers and digital data.
To address this inefficiency, it is vital to leverage cutting-edge digital technology and establish a safer, more sustainable infrastructure management system, specifically as a part of the Strategic Innovation Promotion (SIP) Program Smart Infrastructure Management System.
Taking up this challenge, a team of researchers from Japan, led by Professor Ryuichi Imai from the Faculty of Engineering and Design, Hosei University, Japan, and including Dr. Kenji Nakamura, Faculty of Information Technology and Social Sciences, Osaka University of Economics; Dr. Yoshinori Tsukada, Faculty of Engineering, Reitaku University; Dr. Toshio Teraguchi, Faculty of Economics, University of Marketing and Distribution Sciences; and Dr. Chikako Kurokawa, Advanced Technologies Research Laboratory, Asia Air Survey Co. Ltd., has recently addressed the separate and difficult management of bridges' 3D geometry data and their maintenance information such as inspection results and repair history in siloed systems. Their novel findings were made available online on October 5, 2025, published in Volume 40, Issue 27 of the journal Computer-Aided Civil and Infrastructure Engineering on November 14, 2025.
This study introduces a novel integrated data model that merges two international standards—IFC (Industry Foundation Classes) for construction and Building Information Modeling (BIM), and CityGML for geospatial information. The resulting framework enables the unified, one-source management of both 3D geometric data and maintenance information (such as inspection results and repair history). This integration is expected to significantly streamline and enhance maintenance workflows, including inspection, diagnosis, and repair planning for aging bridges.
"Our work would allow infrastructure managers, specifically local governments, to accurately grasp damage locations found during inspections and past repair histories for the numerous bridges under their jurisdiction, all visualized on 3D models. For example, they can instantly check information—either on-site or in the office—like, 'Is this damage located in the same spot that was repaired 5 years ago?' This enables them to make precise, data-driven decisions about repair priorities and the most suitable repair methods. This is expected to lead to improved infrastructure safety and longevity and efficient use of public funds," remarks Prof. Imai.
In 5 to 10 years, the team expects the integrated data model from their research to be widely adopted as a standard by local governments nationwide, leading to the creation of digital twins for social infrastructure, starting with bridges. On these digital twins, AI-driven deterioration forecasting simulations would become possible. This would accelerate the shift from reactive maintenance, or fixing things after they break, to predictive maintenance, or repairing at the optimal time before they fail. This will help prevent critical accidents like bridge collapses and extend infrastructure lifespan, contributing to a society where people can live more safely and sustainably.
Furthermore, during disasters, it will enable the immediate assessment of which bridges are passable, supporting rapid evacuation and recovery efforts.
"In effect, our technology—aimed at connecting field expertise with digital data and realizing future maintenance where infrastructure is collaboratively monitored across communities—can pave the way to a society where future generations can live more securely," concludes Prof. Imai.
