Crane Signalman Hand-Signal Classification Framework Using Sensor-Based Smart Construction Glove and Machine-Learning Algorithms

Author:

Mansoor Asif1ORCID,Liu Shuai2ORCID,Bouferguene Ahmed3,Al-Hussein Mohamed4ORCID

Affiliation:

1. Ph.D. Candidate, Dept. of Civil and Environmental Engineering, Univ. of Alberta, 116 St. & 85 Ave., Edmonton, Canada T6G2R3. ORCID: .

2. Ph.D. Candidate, Dept. of Civil and Environmental Engineering, Univ. of Alberta, 116 St. & 85 Ave., Edmonton, Canada T6G2R3 (corresponding author). ORCID: .

3. Professor, Campus Saint-Jean, Univ. of Alberta, 8406 Rue Marie-Anne Gaboury, Edmonton, Canada T6G2R3.

4. Professor, Dept. of Civil and Environmental Engineering, Univ. of Alberta, 116 St. & 85 Ave., Edmonton, Canada T6G2R3. ORCID: .

Publisher

American Society of Civil Engineers (ASCE)

Reference55 articles.

1. Agarap A. F. M. 2018. “Deep learning using rectified linear units (ReLU).” Preprint submitted March 22 2018. http://arxiv.org/abs/1803.08375.

2. Wearable Sensing Technology Applications in Construction Safety and Health

3. Smartphone-based construction workers' activity recognition and classification

4. Flex sensor based hand glove for deaf and mute people;Al Mamun A.;Int. J. Comput. Networks Commun. Secur.,2017

5. ASME. 2021. “B30.5-2021: Mobile and locomotive cranes.” Accessed April 22 2024. https://www.asme.org/codes-standards/find-codes-standards/b30-5-mobile-locomotive-cranes.

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