A framework for drone-based remote bridge inspections
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The progressive aging of bridge networks raises the need for more frequent and effective structural inspections. Conventional inspection methods are often costly, labor-intensive, and potentially hazardous, especially in difficult-to-access areas. Unmanned aerial vehicles (UAVs) are emerging as a promising alternative, enabling safer and more efficient data collection while providing high-resolution results. Their use has been extended to post-disaster assessments and large-scale surveys, with further potential offered by swarms equipped with non-destructive testing (NDT) sensors. When integrated with machine learning techniques, UAV-based inspections support agile and low-cost Structural Health Monitoring (SHM) procedures. In addition, the adoption of 5G-and-Beyond communication networks facilitates real-time, remote operations beyond visual line of sight (BVLOS), while immersive technologies such as virtual and augmented reality enhance operator awareness and data interpretation. This paper introduces a framework for remote bridge inspection that combines drones and virtual reality in a unified system, integrating autonomous mission planning, high-speed data transmission, real-time inspection, and decision-support tools. The approach aims to increase inspection frequency, reduce operational risks, and improve the reliability of infrastructure management.