News Release 2025
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April 11, 2025 Award
Fare Collection System Using Contactless Smart Cards Honored with the “Denki no Ishizue” Award by the Institute of Electrical Engineers of Japan
The Railway Technical Research Institute (RTRI), East Japan Railway Company (JR East), and Sony Corporation, who jointly developed the Fare Collection System Using Contactless Smart Cards (see Fig. 1), are pleased to announce that the system has been honored with the 18th “Denki no Ishizue (Foundations of Electricity)” Award, an electrical technology commendation, by the Institute of Electrical Engineers of Japan (IEEJ). The award ceremony was held on March 19, 2025, at the Meiji University’s Academy Hall, Surugadai Campus (see Fig. 2 and Fig. 3).
The Railway Technical Research Institute (RTRI), East Japan Railway Company (JR East), and Sony Corporation, who jointly developed the Fare Collection System Using Contactless Smart Cards (see Fig. 1), are pleased to announce that the system has been honored with the 18th “Denki no Ishizue (Foundations of Electricity)” Award, an electrical technology commendation, by the Institute of Electrical Engineers of Japan (IEEJ). The award ceremony was held on March 19, 2025, at the Meiji University’s Academy Hall, Surugadai Campus (see Fig. 2 and Fig. 3).
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March 06, 2025 R&D
RTRI Develops Inspection Support System Using Images of Tunnel Walls
The Railway Technical Research Institute (RTRI) has developed an inspection support system using images of tunnel walls (hereinafter referred to as “this system”) to conduct tunnel inspections efficiently. This system uses AI to extract deteriorations from images of tunnel walls and identify the overall soundness of tunnels, and projects areas that require special attention and intensive investigations on the actual wall surface, thereby supporting the investigation process.
The Railway Technical Research Institute (RTRI) has developed an inspection support system using images of tunnel walls (hereinafter referred to as “this system”) to conduct tunnel inspections efficiently. This system uses AI to extract deteriorations from images of tunnel walls and identify the overall soundness of tunnels, and projects areas that require special attention and intensive investigations on the actual wall surface, thereby supporting the investigation process.