Impact of Artificial Intelligence in this Changing Railway Industry

The impact of Artificial Intelligence on the Railway Industry is huge and is developing day by day.

The pace of technological advancements is rapidly accelerating. According to the European Network on High Performance and Embedded Architecture and Compilation (HiPEC), society is entering the artificial intelligence (AI) era, driven by the Fourth Industrial Revolution, where computers are taking on new forms and embedding them into people's daily lives.

The advances in digital technologies such as AI, big data analytics, Internet of Things (IoT), and blockchain, bring the concept of seamless mobility and efficient interconnectivity to a reality.

Data analytics and artificial intelligence in railways have a big contribution to the development of society. The national transporter is planning to use AI and big data analytics in train operations, passenger ticket booking, maintenance of systems, freight operations, and railways assets.

The data will be analyzed with the help of AI, IoT, and analytics and used in the Passenger Reservation System (PRS). Unlike the present system of carrying out maintenance in a periodic manner, a predictive asset maintenance system will continuously monitor the condition of equipment and generate the required alerts. This will not only reduce the cost of maintenance but also help to cut down the load on maintenance of assets.

Some of the ways through which we get to see the impact of Artificial Intelligence in railways:

• Restricted area monitoring and access control- AI tools can not only keep a track of the number of people visiting a railway facility but also those entering, exiting, or loitering around in restricted access areas. For instance, railway control rooms, maintenance and storage areas, or sites of under-construction projects can be monitored effectively, 24/7 through automatic AI analytics integrated CCTVs. The cameras operate on facial identification and vehicle number plate identification parameters to identify whether a person or vehicle entering/exiting the premises or restricted areas is authorized or not. It would also have the capability of identifying, warning through integrated PAS, or reporting people loitering suspiciously or vehicles parked illegally/haphazardly.

• Manipulation of CCTV systems – Integration of AI with CCTV systems can enhance their surveillance capabilities by several notches, and also enable them to self-diagnose and report an operational problem or attempted system tampering. For instance, AI-integrated video analytics would be able to report if a camera's video signal is lost, its view is blocked, the viewing angle is changed or the camera is defocused/blurred causing disruption in the video monitoring abilities. Thus, the technicians and security teams can actively respond to such problems and rectify them quickly.

• Predictive maintenance for rolling stock- The goal is to model defects in the wheels of railway carriages. Relevant measurements are taken by detectors embedded under tracks, which measure the peak load exerted by railway carriages as they pass over the tracks.

• Passenger safety-It has some special requirements because of the large distances covered by trains. Accurately locating passengers during an emergency is critical. The ubiquitous nature of smartphones presents an opportunity to provide more accurate help in such situations. Smartphone applications could be used to replace emergency chains on trains; this would not only help passengers with restricted movement but also stop rogue chain pulling incidents. Other sensors, such as RFID or QR codes, could be used for access to coaches and compartments, ensuring only legitimate passengers can board trains. Safety-driven applications such as those developed by metro operators can be leveraged on a nationwide basis as a starting point.

It is clear AI and big data analytics systems can be powerful and solve the critical challenges that railways are facing today. Experts recruited for the study came up with future concepts of AI-driven solutions that can revolutionize the industry such as 'smart stations' and 'Real-Time Customer Sentiment Tracking' through AI-powered video analytics.

Transport provides in-depth descriptions of AI use-cases in public transport, detailed guidelines on key building blocks of AI in railways, and solutions to overcome the common challenges of AI projects, as well as an overview of the potentials of AI when combined with other technologies such as IoT and blockchain.

However, AI is no silver bullet and faces limitations like any other technology. Data is the foundation of all AI systems – quality, quantity, integrity, and legality are all important factors.