[Rebroadcast] Webinar: 'AI Utilization for Bridge Inspection and Damage Detection - Learning from Ota Ward's Approach to Transforming Inspection Processes'
Canon Marketing Japan will rebroadcast a webinar on AI utilization for bridge inspection and damage detection, addressing aging social infrastructure and labor shortages. It will explain the challenges and solutions for AI implementation, the effectiveness of smart maintenance through Ota Ward's case study, and introduce related cloud services.
📋 Article Processing Timeline
- 📰 Published: April 10, 2026 at 18:00
- 🔍 Collected: April 10, 2026 at 09:01
- 🤖 AI Analyzed: April 20, 2026 at 07:51 (238h 49m after Collected)
## Press Release Information
### ■ AI Utilization for Infrastructure Inspection and Maintenance Required in an Era of Labor Shortages
While social infrastructure developed during Japan's period of rapid economic growth continues to age, the construction industry faces increasing difficulty in securing personnel for inspection and maintenance due due to the aging of skilled technicians and a shortage of young workers.
To address these challenges, the Ministry of Land, Infrastructure, Transport and Tourism (MLIT) has announced a policy to permit the use of digital technology for regular inspections of bridges and tunnels, provided that "results equivalent to close-range visual inspection can be obtained." This has made new inspection methods combining AI and image analysis a realistic option on-site.
### ■ Challenges in On-site Implementation of AI Technology
However, despite the annual improvements in the accuracy and practicality of AI technology, its full-scale adoption on-site has not progressed as expected.
Behind this are technical challenges such as a shortage of AI talent, significant variations in image quality depending on the shooting environment and the condition of the inspection target, and how to ensure the consistency and reliability of results between close-range visual inspection and AI-based damage detection. Furthermore, on-site ingenuity is required, such as addressing areas difficult to photograph remotely or with drones (e.g., the underside of bridge girders or confined spaces), and establishing stable shooting methods.
To overcome these challenges and establish the use of AI, not only practical, site-led responses but also a comprehensive cooperative system based on mutual understanding with the local governments that commission and operate these tasks is essential.
### ■ Learning from Ota Ward's Initiatives to Transform Inspection Processes
This seminar will explain the effectiveness of AI-based damage detection, current challenges, and future prospects, based on an overview and results of smart maintenance initiatives in bridge inspection conducted by Ota Ward, Tokyo. It will also organize maintenance management challenges such as "labor," "reliability," and "record utilization" in inspection work, and introduce how local governments and private companies have shared these challenges and implemented the latest technologies through public-private partnerships.
At the end of the session, we will introduce "Inspection EYE for Infrastructure Cloud Edition," a cloud service that supports damage detection in such inspection tasks.
This content is particularly recommended for construction consultants, general contractors, railway/power/highway related companies, and local government officials involved in bridge inspection and infrastructure maintenance who are considering on-site reforms utilizing new technologies.
### ■ Organizer/Co-organizer
Canon Marketing Japan Inc.
### ■ Cooperation
Ota City Office
Open Source Utilization Research Institute Co., Ltd.
Majisemi Co., Ltd.
### ■ AI Utilization for Infrastructure Inspection and Maintenance Required in an Era of Labor Shortages
While social infrastructure developed during Japan's period of rapid economic growth continues to age, the construction industry faces increasing difficulty in securing personnel for inspection and maintenance due due to the aging of skilled technicians and a shortage of young workers.
To address these challenges, the Ministry of Land, Infrastructure, Transport and Tourism (MLIT) has announced a policy to permit the use of digital technology for regular inspections of bridges and tunnels, provided that "results equivalent to close-range visual inspection can be obtained." This has made new inspection methods combining AI and image analysis a realistic option on-site.
### ■ Challenges in On-site Implementation of AI Technology
However, despite the annual improvements in the accuracy and practicality of AI technology, its full-scale adoption on-site has not progressed as expected.
Behind this are technical challenges such as a shortage of AI talent, significant variations in image quality depending on the shooting environment and the condition of the inspection target, and how to ensure the consistency and reliability of results between close-range visual inspection and AI-based damage detection. Furthermore, on-site ingenuity is required, such as addressing areas difficult to photograph remotely or with drones (e.g., the underside of bridge girders or confined spaces), and establishing stable shooting methods.
To overcome these challenges and establish the use of AI, not only practical, site-led responses but also a comprehensive cooperative system based on mutual understanding with the local governments that commission and operate these tasks is essential.
### ■ Learning from Ota Ward's Initiatives to Transform Inspection Processes
This seminar will explain the effectiveness of AI-based damage detection, current challenges, and future prospects, based on an overview and results of smart maintenance initiatives in bridge inspection conducted by Ota Ward, Tokyo. It will also organize maintenance management challenges such as "labor," "reliability," and "record utilization" in inspection work, and introduce how local governments and private companies have shared these challenges and implemented the latest technologies through public-private partnerships.
At the end of the session, we will introduce "Inspection EYE for Infrastructure Cloud Edition," a cloud service that supports damage detection in such inspection tasks.
This content is particularly recommended for construction consultants, general contractors, railway/power/highway related companies, and local government officials involved in bridge inspection and infrastructure maintenance who are considering on-site reforms utilizing new technologies.
### ■ Organizer/Co-organizer
Canon Marketing Japan Inc.
### ■ Cooperation
Ota City Office
Open Source Utilization Research Institute Co., Ltd.
Majisemi Co., Ltd.