Keywords: remote railway inspection, boots off ballast, artificial intelligence, unattended track geometry monitoring, risk?based maintenance, automatic detection.

Track maintenance practices in the UK have changed little over the past two centuries and continue to rely heavily on manual inspection and intervention. However, traditional approaches are increasingly challenged by rising costs, limitations in effectiveness and efficiency, growing demands for infrastructure availability and reliability, and a greater frequency of extreme weather events. These pressures raise a fundamental question: how can we continue to keep our staff safe? Carrying out physical inspections in 40?°C heat or during prolonged periods of heavy rainfall presents both safety risks and productivity constraints. Moreover, the physically demanding nature of trackside work, combined with the limited use of modern technology, is increasingly viewed as an unattractive career proposition by younger generations, contributing to ongoing skills and resource shortages. This paper presents a technical overview of Network Rail Eastern Region’s Boots Off Ballast programme, an operational transformation aimed at reducing unnecessary trackside exposure through remote inspection technologies. The programme integrates artificial intelligence, advanced video analytics, and unattended track geometry monitoring to enable condition? and risk?based maintenance. Case studies demonstrate how these tools improve defect detection, enhance decision?making, and deliver measurable safety, performance, and productivity benefits. Collectively, Boots Off Ballast represents a strategic shift toward a safer, smarter, and more sustainable model for maintaining the UK rail network.

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