railway, trains, tracks, AI,

Today’s freight trains are massive marvels of engineering. At nearly half a million pounds, they can travel up to 70 miles per hour and take over a mile to come to a complete stop. But that size and speed can lead to devastating consequences with accidents or derailments. 

Last year’s massive derailment in East Palestine, Ohio, led to the introduction of the bipartisan Railway Safety Act of 2023. But while that legislation works its way through Congress, railway accidents, injuries and fatalities continue. The number of train accidents increased in 2023 to 4,845, including more than 600 deaths. Even though the total number of derailments declined by about 2.6% from 2022 to 2023, there were still nearly three derailments a day nationwide. 

How can we protect this critical piece of our supply chain and make the railways safer for workers and the people who live near the tracks? A combination of two cutting-edge technologies — AI and edge computing — promises to revolutionize railway safety and usher in a new era of smart, connected rail systems. 

Section 7 of the Railway Safety Act of 2023 introduces the topic of a “defect detection system” as a means of identifying and understanding the severity of known safety conditions. This presents a prime opportunity for edge and AI to make a difference. Sensors and cameras placed along the track every three miles or so scan the entirety of the train as it passes by, measuring and analyzing its condition in real time. Using AI models, the system can detect potential issues, such as wheel bearing failures, within seconds or minutes—long before they escalate into disasters. 

This approach represents a significant shift from traditional methods. Instead of relying on periodic inspections or centralized data analysis, edge computing allows for immediate, on-site processing of vast amounts of data. Edge computing, in essence, brings the power of data processing and analysis closer to where the data is generated – in this case, right along the railway tracks. This decentralized approach reduces latency, improves real-time decision-making and minimizes the need for constant high-bandwidth connections to central servers. The AI models running on these edge devices, continuously learning and improving over time, become increasingly adept at identifying anomalies and potential safety hazards. 

This shift towards edge computing in railway safety is part of a broader trend across industries, where the need for real-time data processing and analysis is pushing computing power to the edges of networks, ushering in a new era of smart, connected systems that can respond instantly to changing conditions. 

Transforming Traditional Practices 

The potential applications of AI in railway safety extend far beyond real-time monitoring. The Federal Railroad Administration and rail companies are currently exploring a range of AI-powered solutions, including automated track change detection, digital twins and real-time traffic management. These technologies promise to address multiple safety factors simultaneously, from reducing human error to improving infrastructure monitoring and enhancing mechanical failure prediction. 

On the Right Track 

Despite its immense potential, the adoption of AI in the railroad industry is still in its early stages. Regulatory hurdles, the need to meet stringent safety standards, and cybersecurity concerns present significant challenges. Not to mention the sheer scale of operating sensors every couple miles in a network of tens of thousands of track nationwide. Moreover, the industry faces a delicate balance between embracing automation and addressing concerns about job displacement. 

As we await legislation like the Railway Safety Act to become law, the integration of AI and edge computing into railway safety strategies becomes increasingly relevant. These technologies offer a path to implement many of the act’s proposed measures, such as enhanced defect detection and stricter safety precautions for hazardous materials. 

The future of America’s railways lies at the intersection of traditional infrastructure and cutting-edge technology. By leveraging AI and edge computing, the industry has the opportunity to not only reverse the trend of increasing accidents but to set new standards for safety and efficiency in transportation.