Toward an Era of "Continuous Monitoring" of Infrastructure — A Sewer Pipe Inspection Robot Developed by National College of Technology Students and New Social Design for the AI Era326

Much of Japan’s infrastructure, built during the period of rapid economic growth, is now more than 50 years old, making it difficult to assess its overall condition using conventional methods. Incidents such as the road collapse that occurred in Yashio City, Saitama Prefecture, have highlighted the challenges of maintaining aging infrastructure as a pressing social issue. In response to this challenge, we will examine infrastructure maintenance in the AI era by looking at examples of the latest technologies—including the “Sewer Inspection Robot” developed by Toyota National College of Technology, which won the Grand Prize at DCON2026—and by adopting the perspective that “a single design can change the whole system.”

The Practical Skills of National College of Technology Students That Save the Day in Infrastructure Crises

The team “Kanro AI” from Toyota National College of Technology won the Grand Prize at the “7th National College of Technology Deep Learning Contest (DCON2026)” held in May, The “Pipe Eye” automated sewer inspection robot, developed by the “Kanro AI” team from Toyota National College of Technology—which recorded a corporate valuation of 560 million yen—automatically navigates through sewer pipes, detects abnormalities using image recognition, and handles the entire process, including generating reports.

I visited the venue that day, and what impressed me most was their unwavering commitment to a “hands-on approach” and their “speed of implementation.” When I asked about the robot’s mobility—specifically, “Can it still move if water starts flowing?”—they immediately replied, “It’s not a problem because the water level is only about 2 centimeters deep.” They had a thorough understanding of the on-site environment, built the robot in just half a year, and had already conducted repeated tests at about 10 actual job sites.

Unlike existing systems, where discussions tend to get bogged down in the idea that “this is where it gets tricky,” these students aren’t held back by constraints—they roll up their sleeves and get right down to implementing solutions. Witnessing this down-to-earth yet overwhelming practical ability firsthand, I became convinced that “the future of infrastructure maintenance should rely on the education provided by National Institutes of Technology.”

Toward an Era of Continuous Infrastructure Monitoring Using AI and Sensors

To overcome the current situation where infrastructure cannot be fully monitored by human effort alone, a system that automatically collects vast amounts of data and analyzes it using AI is essential. The technology to achieve this is currently developing rapidly.

In the space sector, ultra-high-precision time synchronization technology—developed by companies such as Shimadzu Corporation—is helping to improve the accuracy of satellite observations. Building on this technology, a system that combines radar observation data from satellites with AI analysis to detect signs of water pipe leaks across wide areas has already been put into practical use in Toyota City, Aichi Prefecture. On the ground as well, practical applications are advancing—such as Hitachi’s AI solution “HMAX”—which involves installing cameras and sensors on railway cars during regular service to automatically detect anomalies and apply the findings to railway maintenance. Furthermore, as a future direction, there are discussions about a concept involving equipping moving vehicles—such as garbage trucks that travel fixed routes daily—with sensors to routinely collect and analyze road data. Through the collection and processing of vast amounts of data, we are entering an era where continuous monitoring and prediction are becoming a realistic possibility.

The Challenges of "Legacy Systems" and System Design Based on "General Design Theory"

However, when attempting to introduce such new technologies into society, the challenge lies in coordinating them with existing systems—including concerns about changes in employment and the division of labor. Continuing to rely on stopgap measures that involve only partial adjustments to existing systems in response to aging infrastructure carries the risk of leading to inefficiency for society as a whole.

For example, “forests,” which account for 70 percent of the country’s land area, are also a key form of infrastructure (social common capital). Currently, as a result of neglected mountains and abandoned farmland, serious wildlife damage—such as bear sightings—is occurring. Rather than relying solely on stopgap measures like “increasing the number of hunters,” we need to redesign the very structure of the problem itself.

Technologies such as Pipe Eye and HMAX should not be viewed merely as inspection tools, but rather as part of a broader social design aimed at “maintaining society as a whole with limited manpower.” Here, the concept of “General Design Science,” proposed by Hiroyuki Yoshikawa, former President of the University of Tokyo, becomes crucial. This approach views the entire system as the object of design and leads to the idea that “a single design can change the whole,” thereby avoiding a situation where individual optimizations result in an overall suboptimal outcome.

Together with the Next Generation, Mastering AI as an “Infrastructure of Knowledge”

We’ve entered an era where infrastructure inspections can be conducted automatically—with vehicles driving and taking measurements on their own, identifying key areas, analyzing them using AI, and even generating reports. Furthermore, there’s even the possibility that the very nature of traditional reports—and the very concept of inspection work itself—may change.

What matters is how we interpret these changes of the times and how we redesign society as a whole. The time has come to develop a new model for the maintenance and management of infrastructure in collaboration with the next generation of young people—who are mastering technologies such as AI and taking proactive steps to address social challenges. (Hiroshi Komiyama, Chairman of the Platinum Vision Network and Honorary Editor-in-Chief of *Forest Circular Economy*)

*Related Links*
DCON2027 [Official] 8th National National College of Technology Deep Learning Contest

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• SOC
• Institutional capital