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Collaborative Mobile-Cloud Computing for Civil Infrastructure Condition Inspection

机译:用于民用基础设施状况检查的协同移动云计算

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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. (C) 2014 American Society of Civil Engineers.
机译:光学成像技术已广泛用于土木工程实践中,以帮助对损坏场景进行存档,最近还用于基于图像的损坏分析。但是,当前实践中的明显局限性是,在复杂的构建环境中,缺乏基于团队的视觉检查的实时成像,计算和分析功能。本文探索了一种称为协作移动云计算(CMCC)的新计算范例,并提出了用于进行智能民用基础设施状况检查的CMCC框架。通过软件设计,该框架综合了具有三个创新功能的高级移动和云计算技术:(1)支持上下文的图像收集,(2)交互式成像和处理以及(3)实时按需图像分析和条件分析。通过现场实验和计算性能评估,本文证明了所提出的CMCC框架的可行性,该框架包括实时成像,分析的验证,尤其是针对复杂图像场景中两个代表性损伤分析问题的移动云计算解决方案。 (C)2014年美国土木工程师学会。

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