Immersive Bridge Inspection: Quantifying the Benefits of XR for Anomaly Detection

Ali Sabzi Khoshraftar; Berend Jan van der Zwaag; Duc V. Le; Ozlem  Durmaz Incel

doi:10.1145/3714394.3756250

Immersive Bridge Inspection: Quantifying the Benefits of XR for Anomaly Detection

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

6 Downloads (Pure)

Abstract

We present an immersive bridge inspection tool as part of a digital twin for bridges that merges virtual reality (VR) with AI-assisted anomaly detection to evaluate how extended reality (XR) tools can modernize bridge inspections. Two tasks were studied: (i) relocating previously reported anomalies and (ii) detecting new surface anomalies using XR technologies. XR cues and simulated AI prompts were compared with manual inspection for five key performance indicators. Results show that XR + AI cut average detection time by 51%, boosted accuracy by 38%, lowered subjectivity by 11%, and reduced cognitive workload by 23 NASA-TLX points. A post-study survey yielded favorable usability and usefulness ratings, although some volunteers experienced VR-induced discomfort. These findings demonstrate the promise of XR and AI to accelerate, objectify, and lighten the mental load of structural assessments, while highlighting usability challenges that must be addressed for field deployment.

Original language	English
Title of host publication	UbiComp Companion '25
Subtitle of host publication	Companion of the 2025 ACM International Joint Conference on Pervasive and Ubiquitous Computing
Editors	Michael Beigl, Giulio Jacucci, Stephan Sigg, Yu Xiao, Jakob Bardram, Eirini Eleni Tsiropoulou, Chenren Xu
Publisher	Association for Computing Machinery
Pages	1252-1256
Number of pages	6
ISBN (Electronic)	979-8-4007-1477-1
DOIs	https://doi.org/10.1145/3714394.3756250
Publication status	Published - 12 Oct 2025
Event	ACM International Joint Conference on Pervasive and Ubiquitous Computing, UbiComp 2025 - Aalto University, Espoo, Finland Duration: 12 Oct 2024 → 16 Oct 2024 https://www.ubicomp.org/ubicomp-iswc-2025/

Conference

Conference	ACM International Joint Conference on Pervasive and Ubiquitous Computing, UbiComp 2025
Abbreviated title	UbiComp 2025
Country/Territory	Finland
City	Espoo
Period	12/10/24 → 16/10/24
Internet address	https://www.ubicomp.org/ubicomp-iswc-2025/

Access to Document

10.1145/3714394.3756250Licence: CC BY

3714394.3756250Final published version, 2.02 MBLicence: CC BY

Cite this

Khoshraftar, A. S., van der Zwaag, B. J., Le, D. V., & Durmaz Incel, O. (2025). Immersive Bridge Inspection: Quantifying the Benefits of XR for Anomaly Detection. In M. Beigl, G. Jacucci, S. Sigg, Y. Xiao, J. Bardram, E. E. Tsiropoulou, & C. Xu (Eds.), UbiComp Companion '25: Companion of the 2025 ACM International Joint Conference on Pervasive and Ubiquitous Computing (pp. 1252-1256). Association for Computing Machinery. https://doi.org/10.1145/3714394.3756250

Khoshraftar, Ali Sabzi ; van der Zwaag, Berend Jan ; Le, Duc V. et al. / Immersive Bridge Inspection : Quantifying the Benefits of XR for Anomaly Detection. UbiComp Companion '25: Companion of the 2025 ACM International Joint Conference on Pervasive and Ubiquitous Computing. editor / Michael Beigl ; Giulio Jacucci ; Stephan Sigg ; Yu Xiao ; Jakob Bardram ; Eirini Eleni Tsiropoulou ; Chenren Xu. Association for Computing Machinery, 2025. pp. 1252-1256

@inproceedings{ff8938dbe4b54cb5997d5ade446130cb,

title = "Immersive Bridge Inspection: Quantifying the Benefits of XR for Anomaly Detection",

abstract = "We present an immersive bridge inspection tool as part of a digital twin for bridges that merges virtual reality (VR) with AI-assisted anomaly detection to evaluate how extended reality (XR) tools can modernize bridge inspections. Two tasks were studied: (i) relocating previously reported anomalies and (ii) detecting new surface anomalies using XR technologies. XR cues and simulated AI prompts were compared with manual inspection for five key performance indicators. Results show that XR + AI cut average detection time by 51\%, boosted accuracy by 38\%, lowered subjectivity by 11\%, and reduced cognitive workload by 23 NASA-TLX points. A post-study survey yielded favorable usability and usefulness ratings, although some volunteers experienced VR-induced discomfort. These findings demonstrate the promise of XR and AI to accelerate, objectify, and lighten the mental load of structural assessments, while highlighting usability challenges that must be addressed for field deployment.",

author = "Khoshraftar, \{Ali Sabzi\} and \{van der Zwaag\}, \{Berend Jan\} and Le, \{Duc V.\} and \{Durmaz Incel\}, Ozlem",

note = "{\textcopyright} 2025 Copyright held by the owner/author(s).; ACM International Joint Conference on Pervasive and Ubiquitous Computing, UbiComp 2025, UbiComp 2025 ; Conference date: 12-10-2024 Through 16-10-2024",

year = "2025",

month = oct,

day = "12",

doi = "10.1145/3714394.3756250",

language = "English",

pages = "1252--1256",

editor = "Michael Beigl and Giulio Jacucci and Stephan Sigg and Yu Xiao and Jakob Bardram and Tsiropoulou, \{Eirini Eleni\} and Chenren Xu",

booktitle = "UbiComp Companion '25",

publisher = "Association for Computing Machinery",

address = "United States",

url = "https://www.ubicomp.org/ubicomp-iswc-2025/",

}

Khoshraftar, AS, van der Zwaag, BJ , Le, DV & Durmaz Incel, O 2025, Immersive Bridge Inspection: Quantifying the Benefits of XR for Anomaly Detection. in M Beigl, G Jacucci, S Sigg, Y Xiao, J Bardram, EE Tsiropoulou & C Xu (eds), UbiComp Companion '25: Companion of the 2025 ACM International Joint Conference on Pervasive and Ubiquitous Computing. Association for Computing Machinery, pp. 1252-1256, ACM International Joint Conference on Pervasive and Ubiquitous Computing, UbiComp 2025, Espoo, Finland, 12/10/24. https://doi.org/10.1145/3714394.3756250

Immersive Bridge Inspection: Quantifying the Benefits of XR for Anomaly Detection. / Khoshraftar, Ali Sabzi; van der Zwaag, Berend Jan ; Le, Duc V. et al.
UbiComp Companion '25: Companion of the 2025 ACM International Joint Conference on Pervasive and Ubiquitous Computing. ed. / Michael Beigl; Giulio Jacucci; Stephan Sigg; Yu Xiao; Jakob Bardram; Eirini Eleni Tsiropoulou; Chenren Xu. Association for Computing Machinery, 2025. p. 1252-1256.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - Immersive Bridge Inspection

T2 - ACM International Joint Conference on Pervasive and Ubiquitous Computing, UbiComp 2025

AU - Khoshraftar, Ali Sabzi

AU - van der Zwaag, Berend Jan

AU - Le, Duc V.

AU - Durmaz Incel, Ozlem

PY - 2025/10/12

Y1 - 2025/10/12

N2 - We present an immersive bridge inspection tool as part of a digital twin for bridges that merges virtual reality (VR) with AI-assisted anomaly detection to evaluate how extended reality (XR) tools can modernize bridge inspections. Two tasks were studied: (i) relocating previously reported anomalies and (ii) detecting new surface anomalies using XR technologies. XR cues and simulated AI prompts were compared with manual inspection for five key performance indicators. Results show that XR + AI cut average detection time by 51%, boosted accuracy by 38%, lowered subjectivity by 11%, and reduced cognitive workload by 23 NASA-TLX points. A post-study survey yielded favorable usability and usefulness ratings, although some volunteers experienced VR-induced discomfort. These findings demonstrate the promise of XR and AI to accelerate, objectify, and lighten the mental load of structural assessments, while highlighting usability challenges that must be addressed for field deployment.

AB - We present an immersive bridge inspection tool as part of a digital twin for bridges that merges virtual reality (VR) with AI-assisted anomaly detection to evaluate how extended reality (XR) tools can modernize bridge inspections. Two tasks were studied: (i) relocating previously reported anomalies and (ii) detecting new surface anomalies using XR technologies. XR cues and simulated AI prompts were compared with manual inspection for five key performance indicators. Results show that XR + AI cut average detection time by 51%, boosted accuracy by 38%, lowered subjectivity by 11%, and reduced cognitive workload by 23 NASA-TLX points. A post-study survey yielded favorable usability and usefulness ratings, although some volunteers experienced VR-induced discomfort. These findings demonstrate the promise of XR and AI to accelerate, objectify, and lighten the mental load of structural assessments, while highlighting usability challenges that must be addressed for field deployment.

U2 - 10.1145/3714394.3756250

DO - 10.1145/3714394.3756250

M3 - Conference contribution

SP - 1252

EP - 1256

BT - UbiComp Companion '25

A2 - Beigl, Michael

A2 - Jacucci, Giulio

A2 - Sigg, Stephan

A2 - Xiao, Yu

A2 - Bardram, Jakob

A2 - Tsiropoulou, Eirini Eleni

A2 - Xu, Chenren

PB - Association for Computing Machinery

Y2 - 12 October 2024 through 16 October 2024

ER -

Khoshraftar AS, van der Zwaag BJ , Le DV , Durmaz Incel O. Immersive Bridge Inspection: Quantifying the Benefits of XR for Anomaly Detection. In Beigl M, Jacucci G, Sigg S, Xiao Y, Bardram J, Tsiropoulou EE, Xu C, editors, UbiComp Companion '25: Companion of the 2025 ACM International Joint Conference on Pervasive and Ubiquitous Computing. Association for Computing Machinery. 2025. p. 1252-1256 doi: 10.1145/3714394.3756250

Immersive Bridge Inspection: Quantifying the Benefits of XR for Anomaly Detection

Abstract

Conference

Access to Document

Fingerprint

Cite this