Keywords: smart sensing, smartphones, tram, light-rail, operation, infrastructure, data analysis.

In recent years, the demand for sustainable, reliable, and high-capacity public transport has increased, particularly in densely populated areas. Urban rail systems, including tram, light-rail and metro networks, can provide an efficient and sustainable means of transport for high-passenger volumes. However, these systems are often characterised by ageing infrastructure, rising energy, staff and material costs, and a shortage of qualified personnel. Together, these constraints increasingly limit operators' ability to maintain a high level of service quality, particularly with respect to infrastructure availability and operational performance. This study investigates how large-scale, low-cost smartphone sensing data, collected by driving personnel during regular service in trams and light-rail vehicles, can support rail infrastructure inspection and maintenance as well as overall operational quality. The results demonstrate that this low-cost smartphone-based sensing approach enables effective monitoring of infrastructure degradation and supports the planning of maintenance interventions. Furthermore, the data can be used to identify safety-critical traffic situations and to assess operational performance.

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