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In recent times, digital transformations and Industry 4.0 have revolutionized real-time bridge monitoring and its inspection. The use of smart Structural Health Monitoring (SHM) techniques is becoming powerful with the competencies of Building Information Modeling (BIM) tools, Artificial Intelligence (AI), Internet of Things (IoT), and Virtual/Augmented (VR/AR) technologies. However, the lack of interconnectivity between these tools limits their functionality. This research has addressed this problem by developing an integrated framework to assess serviceability and implement a smart SHM for a newly constructed extradosed bridge. Using Finite Element Analysis (FEA), the study proposes an integrated SHM system that utilizes various IoT sensors, including Wired Strain Gauges (WSG), Liquid Levelling Sensors (LLS), MEMS accelerometers, and a Weather Monitoring Station (WMS) to monitor concrete deformations, vertical displacements, structural vibrations, and weather conditions. BIM tool is used to develop the virtual replica of the proposed SHM system which is then used in the 3D Game Engine (GE) to develop an AR application. This application is then successfully deployed and tested in the AR headset (HoloLens) where its capabilities for onsite bridge health monitoring are discovered. This approach overcomes the limitations of HoloLens devices by providing real-time access to SHM data through a web platform, enabling on-site or remote AR-based bridge health monitoring. Conclusively, this paper emphasizes the numerical modeling of bridges for the design of a health monitoring system, that highlights the importance of robust SHM techniques in assessing bridge conditions. Moreover, it introduces a novel approach for smart bridge inspection and onsite visualization of structural defects in an AR environment. |
