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Bridges have been identified as an essential part of transportation in Taiwan. However, most bridges are experience significant damage from frequent earthquakes, in addition to bridge scour caused by flooding from yearly typhoons and heavy rain. Therefore, implementing a safety assessment and early warning system during bridge maintenance has become an urgent need. Presently, a bridge’s seismic or flood resistance capacity is evaluated by obtaining the required data from the bridge’s design drawings, computation statements, and maintenance inspection data for the estimation of danger thresholds. Extraction of such documents and related information must often be done manually. This study verified the bridge design and maintenance parameters required for safety assessments in terms of seismic resistance evaluation, flood resistance evaluation, and vibration frequency analysis. Relying on the developed data exchange platform, this study innovatively proposes an invisible computer concept to automate the data extraction and analytical process once the required documents and data are uploaded and input in the design and construction phases. During an earthquake, typhoon, or flood in the maintenance phase, the developed system will retrieve the needed data and implement a safety assessment without the requirement of additional user input or interactions. Then the autonomous system will instantaneously send the evaluation results and disaster warnings to the bridge management authorities through mobile facilities for further appropriate actions. The system not only saves time and labor efforts for preemptive measures but also better protects the safety of road users.
Cheng et al. (Thu,) studied this question.