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One of the most critical components of the US transportation system is railroads, accommodating transportation for 48% of the nation’s total modal tonnage. Despite such vital importance, more than half of the railroad bridges, an essential component of railroad infrastructure in maintaining the flow of the network, were built before 1920; as a result, bridges comprise one of the most fragile components of the railroad system. Current structural inspection practice does not ensure sufficient information for both short- and long-term condition assessment while keeping the operation cost low enough for mandatory annual inspection. In this paper, we document the development process of an autonomous, affordable system for monitoring railroad bridges using the wireless smart sensor (WSS) so that a complete end-to-end monitoring solution can provide relevant information directly from the bridges to the end-users. The system’s main contribution is to capture the train-crossing event efficiently and eliminate the need for a human-in-the-loop for remote data retrieval and post-processing. In the proposed system, an adaptive strategy combining an event-based and schedule-based framework is implemented. The wireless system addresses the challenges of remote data retrieval by integrating 4G-LTE functionality into the sensor network and completes the data pipeline with a cloud-based data management and visualization solution. This system is realized on hardware, software, and framework levels. To demonstrate the efficacy of this system, a full-scale monitoring campaign is reported. By overcoming the challenges of monitoring railroad bridges wirelessly and autonomously, this system is expected to be an essential tool for bridge engineers and decision-makers.

Autonomous end-to-end wireless monitoring system for railroad bridges