Sherafat, B; Ahn, C R; Akhavian, R; Behzadan, A H; Golparvar-Fard, M; Kim, H; Lee, Y C; Rashidi, A and Azar, E R (2020) Automated methods for activity recognition of construction workers and equipment: State-of-the-art review. Journal of Construction Engineering and Management, 146(6): 0001843, ISSN 0733-9364
Abstract
Equipment and workers are two important resources in the construction industry. Performance monitoring of these resources would help project managers improve the productivity rates of construction jobsites and discover potential performance issues. A typical construction workface monitoring system consists of four major levels: location tracking, activity recognition, activity tracking, and performance monitoring. These levels are employed to evaluate work sequences over time and also assess the workers' and equipment's well-being and abnormal edge cases. Results of an automated performance monitoring system could be used to employ preventive measures to minimize operating/repair costs and downtimes. The authors of this paper have studied the feasibility of implementing a wide range of technologies and computational techniques for automated activity recognition and tracking of construction equipment and workers. This paper provides a comprehensive review of these methods and techniques as well as describes their advantages, practical value, and limitations. Additionally, a multifaceted comparison between these methods is presented, and potential knowledge gaps and future research directions are discussed.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | activity recognition; activity tracking; audio-based method; construction equipment; convolutional neural network; kinematic-based method; location tracking; machine learning; performance monitoring; vision-based method; worker |
| Index terms: | construction industry, construction worker, monitoring, productivity, activity recognition, construction equipment, project manager, repair, machine learning, well-being, state of the art, neural network, performance monitoring |
| Subjects: | modelling and simulation, artificial intelligence, research dissemination and communication, profession, mental health and wellbeing, practitioner, control systems, industry analysis, management, maintenance engineering, monitoring and control systems, construction equipment |
| Topics: | Health and Safety, Business Strategy, Research Practice, Roles and Professions, Governance, Plant and Equipment, Digital Applications, Design Practice, Site Management |
| Descriptive scope: | 3 PCT |
N.B. Descriptive scope is a count of how many of the five facets of empirical research are indicated by the words used in title, abstract and keywords. It is not intended as a judgement on the research; merely a count of the kind of word we would expect to indicate Phenomenon, Concepts, Theoretical framing, Empirical techniques, Analytical techniques. If all five are present, then a code of “5 PCTEA” will indicate this. If you feel the coding for this record is questionable, we welcome discussion around the terms we matched or the way we categorized them. The facet you would expect may not be coded, or a facet may be coded inappropriately. This can also bear on a larger question, of which facets should be treated as defining in construction management research. Please get in touch, and we will look at it. More details here