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Characterization of expertise to build an augmented skill training system for construction industry

Publication Type : Conference Paper

Thematic Areas : Humanitarian-Robotics-HCI

Publisher : Proceedings - IEEE 18th International Conference on Advanced Learning Technologies,

Source : Proceedings - IEEE 18th International Conference on Advanced Learning Technologies, ICALT 2018, 2018.

Url : https://www.scopus.com/inward/record.uri?eid=2-s2.0-85052534038&doi=10.1109%2fICALT.2018.00034&partnerID=40&md5=c98d78db69c0b9ae82711c89ea3437f6

ISBN : 9781538660492

Keywords : construction industry, Experimental methods, Feedback systems, Field experience, Lever positioning, Lever tilting, Motor skills, Real time guidance systems, Rebar

Campus : Amritapuri

School : Department of Social Work

Center : Ammachi labs

Department : Social Work

Year : 2018

Abstract : Rebar Bending is one of the important trade in the construction industry. Major motor skill like force of bend, bend angle accuracy, lever positioning, lever tilting are guiding factor for doing the manual rebar bending process. To be an expert in rebar bending, one should need at least 3 to 4 years of field experience, to learn all motor skill parameters. This paper describes in detail the skill parameters involved during the manual rebar bending process through experimental methods. Comparing the expert data with novice which outline the design of real time guidance system for effective skill transfer and learning. The lever positioning skill learning in manual rebar bending process projected a high accuracy with the help of feedback system.

Cite this Research Publication : D. Sasi, Mohan, H. T., and Rao R. Bhavani, “Characterization of expertise to build an augmented skill training system for construction industry”, in Proceedings - IEEE 18th International Conference on Advanced Learning Technologies, ICALT 2018, 2018.

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