TY - JOUR
T1 - Collaborative Mobile-Cloud Computing for Civil Infrastructure Condition Inspection
AU - Chen, Zhiqiang
AU - Chen, Jianfei
AU - Shen, Feichen
AU - Lee, Yugyung
N1 - Publisher Copyright:
© 2014 American Society of Civil Engineers.
PY - 2015/9/1
Y1 - 2015/9/1
N2 - Optical imaging techniques have been commonly used in civil engineering practice for aiding the archival of damage scenes and more recently, for image-based damage analysis. However, an evident limitation in the current practice is the lacking of real-time imaging, computing, and analytics capability for team-based visual inspection in a complex built environment. This paper explores a new computing paradigm called collaborative mobile-cloud computing (CMCC) and proposes a CMCC framework for conducting intelligent civil infrastructure condition inspection. Through software design, this framework synthesizes advanced mobile and cloud computing technologies with three innovative features: (1) context-enabled image collection, (2) interactive imaging and processing, and (3) real-time on-demand image analysis and condition analytics. Through field experiments and computational performance evaluation, this paper demonstrates the feasibility of the proposed CMCC framework, which includes verification of real-time imaging, analytics, and particularly, the mobile-cloud computational solution to two representative damage analysis problems regarding complex imagery scenes.
AB - Optical imaging techniques have been commonly used in civil engineering practice for aiding the archival of damage scenes and more recently, for image-based damage analysis. However, an evident limitation in the current practice is the lacking of real-time imaging, computing, and analytics capability for team-based visual inspection in a complex built environment. This paper explores a new computing paradigm called collaborative mobile-cloud computing (CMCC) and proposes a CMCC framework for conducting intelligent civil infrastructure condition inspection. Through software design, this framework synthesizes advanced mobile and cloud computing technologies with three innovative features: (1) context-enabled image collection, (2) interactive imaging and processing, and (3) real-time on-demand image analysis and condition analytics. Through field experiments and computational performance evaluation, this paper demonstrates the feasibility of the proposed CMCC framework, which includes verification of real-time imaging, analytics, and particularly, the mobile-cloud computational solution to two representative damage analysis problems regarding complex imagery scenes.
KW - Computer applications
KW - Damage
KW - Imaging techniques
KW - Information technology
KW - Inspection
KW - Interactive systems
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U2 - 10.1061/(ASCE)CP.1943-5487.0000377
DO - 10.1061/(ASCE)CP.1943-5487.0000377
M3 - Article
AN - SCOPUS:84939438848
SN - 0887-3801
VL - 29
JO - Journal of Computing in Civil Engineering
JF - Journal of Computing in Civil Engineering
IS - 5
M1 - 4014066
ER -