Applications of ICTs and Action Recognition for Construction Workers

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Applications of ICTs and Action Recognition for Construction Workers

Journal Title: Trends in Civil Engineering and its Architecture - Year 2018, Vol 1, Issue 3

Abstract

Human action recognition has gained considerable attention because of its wide variety of potential applications (e.g., entertainment, rehabilitation, robotics, and security) in the computer vision sector. During the last decades, rapid advances have been made, investigating various approaches such as scene interpretation, holistic body-based recognition, body part- based recognition, and action hierarchy-based recognition [1]. Recognizing the activities of workers enables measurement and control of safety, productivity, and quality at construction sites, and automated activity recognition can enhance the efficiency of the measurement system [2]. Novel information and communication technologies (ICTs) have undergone unprecedented advancements in the recent decades and are transforming lives as well as academic research. This paper reviews the recent research developments and applications regarding action recognition in the construction industry. Because action recognition is employed in several research fields where different terminologies are used, in this paper, the term "action" is used in a broader sense and may refer to "activity," "behavior or state," and "posture," which are all essential for the management of construction jobsites. First, the action of a construction worker may refer to a typical activity performed by a worker, such as formwork assembly or concrete pouring. Moreover, it may refer to more detailed operative steps or sub activities of an activity such as hammering nails and turning a wrench. In the context of productivity, activities may include not only production activity but also supportive activities such as moving or sorting tiles and idling activities such as chatting or smoking. Second, the action of a construction worker may refer to behavior such as the adoption of a stance (e.g., squatting or bending to lift a load), a physical state (e.g., unsteady movement or sudden stamping), or a mind state (e.g., vigilance or inattention) that a worker intentionally or unintentionally exhibits. For example, in the context of monitoring worker safety at a jobsite, the action may concern whether a worker is taking a normal stance or making a hazardous action such as a sudden stamp. Finally, the action of a worker may refer to posture (e.g., a large angle of bending when carrying heavy loads)when research is concerned with ergonomics and worker health. Recognizing the actions of workers is important for many aspects of construction management such as monitoring personal hazardous behaviors to prevent work-related injuries or musculoskeletal disorders(WMSDs), monitoring work activities to reduce non-value-added activity for improving productivity, and facilitation of visual communication (e.g., hand signals between an equipment operator and on-ground support crew). Conventionally, the task of action recognitions visually performed by human inspectors or supervisors; moreover, it is a time-consuming and error-prone process because of the subjective nature of human visualization and human memory limitations. ICTs have gained considerable attention in recent years owing to their availability, affordability, diversity, and applicability. The ability to detect human actions is particularly crucial and has received great attention from both practitioners and researchers in several other fields such as ambient intelligence, surveillance, elderly care, human-machine interaction, smart manufacturing, sports training, and postural correction and rehabilitation, and entertainment games [3]. Compared with some environments such as the manufacturing industry where fabrication is mostly based on static stations and assembly processes, the dynamic nature of construction activities, workface, and site environments make the application of ICTs for action recognition more challenging due to problems such as occlusions, different viewpoints, multiple workers working simultaneously, and a large range of movement. This paper reviews the recent development of human-action- recognition technologies and their applications in the construction industry. Some other technologies (e.g., ultra-wideband, radiofrequency identification, and global positioning systems) that monitor construction activities or workers without involving action recognition are beyond the scope of this review. For example, the research by Cheng et al. [4], which used commercial ultra-wideband technology to monitor resource allocations and productivity at a harsh construction site, is not covered by the scope of this review because the researchers derived information about on-going activities solely based on the locations and movements of each type of resource without actually monitoring individual actions.

Authors and Affiliations

Ren-Jye Dzeng, HsienHui Hsueh, Keisuke Watanabe

Keywords

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EP ID EP605063
DOI 10.32474/TCEIA.2018.01.000113
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