A DRONE-INTEGRATED SAFETY FRAMEWORK FOR SUSTAINABLE RAIL INFRASTRUCTURE MANAGEMENT AND ACCIDENT PREVENTION

The rail accident statistical data highlights the core reasons related to structural safety are ageing, high-density network, infrastructure defect, environmental hazard and human error. This study proposes a socio-technical architecture pivoting around UAVs within an intelligent transport ecosystem. A three-pillar framework is introduced, consisting of Monitoring, Analysis and Decision-Making, and Response and Mitigation. Data from multiple sources and different sensor types are utilized in machine-actionable safety intervention. Scenario-based assessments demonstrate the framework's impact. The proposed approach offers quantifiable benefits, such as reconnaissance flights adjusting early warning thresholds according to operational context, optimizing field deployment and resource allocation. This guide intends to achieve two primary objectives: firstly, to meaningfully reduce the risk of accidents; and secondly, to support sustainable mobility goals. Additionally, the framework is intended to align with evolving aviation and data governance standards.