Survey of robotics technologies for civil infrastructure inspection

Lee, Alex Junho; Song, Wonho; Yu, Byeongho; Choi, Duckyu; Tirtawardhana, Christian; Myung, Hyun

doi:10.1016/j.iintel.2022.100018

Cited by 17 publications

(4 citation statements)

References 37 publications

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“…It was confirmed that the RES of AI-based robots positively influences PU; these findings are consistent with those of Chen et al [26]. The results also indicate that OPQ has a positive influence on PU, which is consistent with the findings of Lee's [62] study. This shows that the students considered that AI-based robots would produce high-quality results.…”

Section: Discussionsupporting

confidence: 90%

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Understanding the Factors Influencing Higher Education Students’ Intention to Adopt Artificial Intelligence-Based Robots

Algerafi,

Zhou,

Alfadda

et al. 2023

IEEE Access

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Although there has been some progress, the integration of artificial intelligence into higher education remains far from sufficient. The demand for teachers will persist for some time; however, with the introduction of AI-based robots into classrooms, the role of teachers has reduced to a minimum. The purpose of the current study was to evaluate Chinese higher education students' intentions to adopt AI-based robots for educational purposes. Based on the TAM3 model, the current study proposes 14 hypotheses to evaluate students' intention to adopt AI-based robots in education. The students' data were collected and analyzed using PLS-SEM. The study findings revealed that 12 hypotheses were accepted and two were rejected. The results indicate that students are willing to accept AI-based robots in their education. However, the findings revealed an insignificant influence of job relevance and robot anxiety on perceived usefulness and ease of use, respectively. The findings of this study will provide insight into university administrations regarding the significance of AI-based robots in education. Moreover, the findings will help robot developers, policy makers, and university administrators design and implement AI-based robots that fulfill contemporary education needs.

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Section: Discussionsupporting

confidence: 90%

“…Chen et al [26] revealed that AI student assistance chatbots have demonstrated good results in supporting students' learning. The integration of technology can also enhance students' learning outcomes [62]. Huang et al [63] found that AI-enabled recommendations have a substantial impact on students' learning.…”

Section: A Hypotheses Developmentmentioning

confidence: 99%

Understanding the Factors Influencing Higher Education Students’ Intention to Adopt Artificial Intelligence-Based Robots

Algerafi,

Zhou,

Alfadda

et al. 2023

IEEE Access

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show abstract

“…6 Commercially available automated inspection devices include ground, aerial and subsurface image capturing machines. 7 All of which capture images under ambient conditions, or require additional external lighting during dark environments. The opportunity to utilize known illumination techniques to enhance the image collection phase and, therefore, the final analysis, has been overlooked.…”

Section: Introductionmentioning

confidence: 99%

Robotic concrete inspection with illumination-enhancement

McAlorum

Perry

Dow

et al. 2023

Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2023

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Existing automated concrete inspection methods are intractable: capturing images under ambient conditions which can vary substantially. Furthermore, an opportunity may have been overlooked: utilizing illumination techniques to enhance defect contrast during imaging which may improve automatic defect detection accuracy. In this work, we present a robotic-mountable lighting apparatus that implements contrast enhancing illumination techniques in an automated package in order to improve crack detection and classification in concrete. Geometrical lighting techniques; directional and angled, were tested on three cracked concrete slab samples. Results from blind/referenceless image spatial quality evaluation (BRISQUE) show that both directional and varied angled lighting influence the quality in different associated regions in an image. Furthermore, the region-based crack detection algorithm Faster R-CNN attained a higher accuracy when images were enhanced with directional lighting during all samples tested. The direction of highest accuracy was not consistent over samples, and is likely dependant on features such as crack location, width, orientation etc. This emphasises the importance of adaptive lighting: illuminating the surface with the most suitable conditions based on an initial observation of the feature or defect. This system represents the initial step in a fully-automated and optimised concrete inspection system capable of defect capture, classification, localization and segmentation.

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“…In the context of SHM, a DT involves a physics-based or machine learning model that continuously utilizes monitoring data to deduce and categorize the health status of the physical asset. This, in turn, enables the autonomous trigger of specific operational, inspection, and maintenance actions [30]. The use of St-Id for constructing DTs, however, represents a formidable challenge.…”

Section: Introductionmentioning

confidence: 99%

Towards a Comprehensive Damage Identification of Structures though Populations of Competing Models

Hernández-González,

García-Macías

2023

Preprint

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Model-based damage identification for Structural Health Monitoring (SHM) remains an open issue in the literature. Along with the computational challenges related to the modeling of full-scale structures, classical single-model structural identification (St-Id) approaches provide no means to guarantee the physical meaningfulness of the inverse calibration results. In this light, this work introduces a novel concept of multi-class digital twins (DTs) formed by a population of competing models, each representing a different failure mechanism. The forward models in the DT are replaced by computationally efficient meta-models, and continuously calibrated using monitoring data. If an anomaly in the structural performance is detected, a model selection approach based on the Bayesian information criterion (BIC) is used to identify the most plausibly activated failure mechanism. The potential of the proposed approach is illustrated through two case studies, including a numerical planar truss and a real-world historical construction: the Muhammad Tower in the Alhambra fortress.

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Survey of robotics technologies for civil infrastructure inspection

Cited by 17 publications

References 37 publications

Understanding the Factors Influencing Higher Education Students’ Intention to Adopt Artificial Intelligence-Based Robots

Understanding the Factors Influencing Higher Education Students’ Intention to Adopt Artificial Intelligence-Based Robots

Robotic concrete inspection with illumination-enhancement

Towards a Comprehensive Damage Identification of Structures though Populations of Competing Models

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