Enhancing Railways with AI: Highlights from Mass-Trans Innovation Japan 2025 - Japan Railway Journal

Mass Trans Innovation Japan 2025: AI-Driven Railway Technologies

Key Concepts:

• AI-powered Facial Recognition Access Gates: Contactless access control using facial recognition technology.
• Generative AI Guidance Systems: AI-driven passenger guidance utilizing avatars.
• AI-based Level Crossing Detection: Systems using cameras and image recognition to detect people lingering in rail crossings.
• AI-powered Train Congestion Measurement: Utilizing depth cameras and AI to determine real-time train car occupancy.
• HMAX (Hypermobility Asset Expert): A centralized AI-driven data analysis system for managing railway infrastructure and assets.
• Big Data: The large volume of data collected by railway organizations, crucial for effective AI implementation.
• Automated Obstruction Warning Signal Inspection: AI-driven systems for inspecting and maintaining level crossing signals.

1. Event Overview & General Trends

The Mass Trans Innovation Japan 2025, held at Makuhari Messi in Chiba Prefecture, showcased innovations from 616 companies and organizations. A prominent theme throughout the event was the increasing integration of Artificial Intelligence (AI) into various aspects of railway operations. Experts noted that AI, particularly when combined with “big data” collected by railway organizations, has the potential to fundamentally improve the railway system. As stated by one of the commentators, “if used properly, AI is the technology to change the railway system forever in a much much better way.” Demonstrations included thermit head repair welding, humanoid robots for high elevation work, and driver training simulators.

2. AI in Passenger Services

Several exhibits focused on enhancing the passenger experience through AI. A notable example was an AI-supported facial recognition access gate, capable of processing up to 100 people per minute without physical barriers. Tokyo Metro demonstrated an industry-first AI-powered system for measuring train congestion. This system addresses the challenge of accurately gauging occupancy, especially with increased through-services from other operators. Previously relying on car weight and ticket gate data (which became unreliable with inter-operator services), the new system utilizes depth cameras to analyze images of train car interiors. The camera measures distance as a color gradient (blue-red) to determine crowding levels, with analysis completed within 4 seconds. This data is then displayed in a smartphone app and on concourse displays, providing passengers with real-time congestion information. Since December 2024, live congestion data has been displayed in two stations.

3. AI for Enhanced Railway Safety

A significant focus was placed on utilizing AI to improve railway safety, particularly at level crossings. Sabu Railway has adopted an AI-based detection system at pedestrian crossings. This system uses cameras and image recognition to identify individuals remaining within the crossing after the barriers are lowered. This addresses a critical safety gap at smaller crossings where emergency buttons may not be readily accessible. Since its introduction in November 2022, six Sabu Railway crossings have been equipped with these AI cameras. Furthermore, AI technology is being developed to automatically identify white canes and wheelchairs, enabling faster and more reliable assistance for passengers with disabilities.

4. AI in Railway Maintenance & Infrastructure Monitoring

The exhibition highlighted several AI-driven solutions for railway maintenance, addressing challenges like aging infrastructure and a shortage of skilled workers. JR Central is trialing an AI-based system to automatically inspect obstruction warning signals at level crossings, a task currently performed manually by workers inspecting 8,000 signals. Onboard AI cameras will conduct more frequent and accurate inspections, reducing workload and costs.

A comprehensive system called HMAX (Hypermobility Asset Expert) was also showcased. Developed by a manufacturer of railway technologies, HMAX centralizes the management of trains, tracks, signals, and facilities using AI-driven data analysis. Sensors and cameras installed on trains collect data on infrastructure, which is then analyzed by AI to detect damage. HMAX is already in use in Europe and the UK on over 2,000 train sets and is being implemented by Tobu Railway in Japan. A robotic camera demonstration showed AI detecting damage on train bogey frames, automating a traditionally manual inspection process.

5. Data Standardization & Future Outlook

Commentators emphasized the importance of standardizing data collection and exchange between railway organizations to maximize the benefits of AI. They noted that while AI applications may vary depending on specific conditions, a unified data approach is crucial, especially for maintenance applications. As one commentator stated, “we should also think about standardizing data and make those data able to be exchanged between different organizations and that will make the amount of data that can be utilized to be much larger than uh when we don't do it.”

6. Technical Terms & Concepts

• Thermit Welding: A welding process using a chemical reaction to create high heat for joining metal rails.
• Bogey: The undercarriage of a railway vehicle, supporting the wheels and axles.
• Level Crossing: An intersection where a railway line crosses a road or path.
• Depth Camera: A camera that captures distance information, used here to measure train car occupancy.
• Image Recognition AI: AI algorithms capable of identifying objects and patterns within images.
• Generative AI: AI models capable of generating new content, such as avatars for guidance systems.

Conclusion:

Mass Trans Innovation Japan 2025 clearly demonstrated the transformative potential of AI within the railway industry. From enhancing passenger services and improving safety to streamlining maintenance and infrastructure monitoring, AI-driven technologies are poised to revolutionize railway operations. The event underscored the importance of big data, data standardization, and continued innovation to fully realize the benefits of AI and address the challenges facing Japan’s railway system. The overall sentiment was optimistic, with experts confident that AI will play a crucial role in shaping the future of railways in Japan and beyond.