Proceedings of the Conference on Technologies for Future Cities (CTFC 2025)

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Smart Infrastructure Monitoring: Parametric and Comparative Analysis of Bridge Deflection Using Vibrating Wire Strain Gauges

Authors
Karishma Gavand1, *, Karthik Nagarajan2, *, Raju Narwade3, *
1Post Graduate Research Scholar, Department of Civil Engineering, Pillai HOC College of Engineering and Technology, Rasayani, University of Mumbai, Mumbai, Maharashtra, India
2Associate Professor, Department of Civil Engineering, Pillai HOC College of Engineering and Technology, Rasayani, University of Mumbai, Mumbai, Maharashtra, India
3Head of Department, Department of Civil Engineering, Pillai HOC College of Engineering and Technology, Rasayani, University of Mumbai, Mumbai, Maharashtra, India
*Corresponding author. Email: karirag3003@gmail.com
*Corresponding author. Email: knagarajan@mes.ac.in
*Corresponding author. Email: rnarwade@mes.ac.in
Corresponding Authors
Karishma Gavand, Karthik Nagarajan, Raju Narwade
Available Online 20 April 2026.
DOI
10.2991/978-94-6239-650-0_10How to use a DOI?
Keywords
Bridge health monitoring; vibrating wire strain gauges; deflection monitoring
Abstract

In order to accurately assess deflection under vehicular loading, this study examines a smart bridge health-monitoring framework that combines vibrating wire strain gauges (VWSGs), finite element simulation, and artificial intelligence-based prediction. The main obstacles to bridge monitoring—scour, temperature fluctuations, fatigue, corrosion, and impact effects—as well as the shortcomings of traditional wired sensing technologies are highlighted in a review of the literature covering the previous 20 years. When combined with wireless sensor networks for real-time monitoring, VWSGs exhibit exceptional robustness, accuracy, and long-term stability. Accelerometer-based VWSG instrumentation was used to gather experimental field measurements from the bridge deck under various vehicle weights and speeds. Analytical baselines for modal and dynamic responses were established through SAP2000 simulations. Dynamic deflection, which peaks close to mid-span and increases with vehicle speed and axle load, is consistently greater than static deflection, according to comparative analysis. The Dynamic Amplification Factor (DAF) exceeded IRC limits, ranging from 1.00 to 2.35. Ultimately, using field and FEM data, a CNN-based prediction model was created that maintained DAF prediction error within ±0.05 and achieved nearly perfect accuracy (R2 ≈ 0.99 vs. field). The findings confirm that bridge diagnostics are greatly improved when VWSGs, FEM simulation, and AI-based prediction are combined. This allows for proactive maintenance and real-time decision-making for smart infrastructure systems.

Copyright
© 2026 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the Conference on Technologies for Future Cities (CTFC 2025)
Series
Atlantis Highlights in Sustainable Development
Publication Date
20 April 2026
ISBN
978-94-6239-650-0
ISSN
3005-155X
DOI
10.2991/978-94-6239-650-0_10How to use a DOI?
Copyright
© 2026 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Karishma Gavand
AU  - Karthik Nagarajan
AU  - Raju Narwade
PY  - 2026
DA  - 2026/04/20
TI  - Smart Infrastructure Monitoring: Parametric and Comparative Analysis of Bridge Deflection Using Vibrating Wire Strain Gauges
BT  - Proceedings of the Conference on Technologies for Future Cities (CTFC 2025)
PB  - Atlantis Press
SP  - 130
EP  - 161
SN  - 3005-155X
UR  - https://doi.org/10.2991/978-94-6239-650-0_10
DO  - 10.2991/978-94-6239-650-0_10
ID  - Gavand2026
ER  -