Automated Methods for Activity Recognition of Construction Workers and Equipment: State-of-the-Art Review

Author:

Sherafat Behnam1ORCID,Ahn Changbum R.2,Akhavian Reza3,Behzadan Amir H.2,Golparvar-Fard Mani4,Kim Hyunsoo5,Lee Yong-Cheol6,Rashidi Abbas7,Azar Ehsan Rezazadeh8

Affiliation:

1. Ph.D. Student of Construction Engineering, Dept. of Civil and Environmental Engineering, Univ. of Utah, Salt Lake City, UT 84112 (corresponding author). ORCID: .

2. Associate Professor, Dept. of Construction Science, Texas A&M Univ., College Station, TX 77843.

3. Assistant Professor, Dept. of Civil, Construction, and Environmental Engineering, San Diego State Univ., San Diego, CA 92182.

4. Associate Professor, Dept. of Civil and Environmental Engineering, Univ. of Illinois at Urbana-Champaign, Champaign, IL 61801.

5. Assistant Professor, Dept. of Architectural Engineering, Dankook Univ., Yongin, Gyeonggi-do 16890, Republic of Korea.

6. Assistant Professor, Dept. of Construction Management, Louisiana State Univ., Baton Rouge, LA 70803.

7. Assistant Professor, Dept. of Civil and Environmental Engineering, Univ. of Utah, Salt Lake City, UT 84112.

8. Associate Professor, Dept. of Civil Engineering, Lakehead Univ., Thunder Bay, ON, Canada P7B 5E1.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Strategy and Management,Industrial relations,Building and Construction,Civil and Structural Engineering

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