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A Posture Recognition Method Applied to Smart Product Service.

Authors :
Liu, Guanjun
Lin, Liyuan
Zhou, Weibin
Zhang, Rui
Yin, Hongyi
Chen, Jingyu
Guo, Hongfei
Source :
Procedia CIRP; 2019, Vol. 83, p425-428, 4p
Publication Year :
2019

Abstract

Product service system (PSS), an undeveloped business model, provides consumers with full-life cycle services from the perspective of products, functions and services. This paper proposes a posture recognition method based on smart product service system from the aspects of technology and user' need. A Posture-CNN model based on the convolutional neural network (CNN) is established in this paper. According to the theory of PSS, this paper analyses the difficulties that the posture recognition technology is facing in the application of products, and resolves the existing problems such as low accuracy of recognition and unsupported complex environment. A self-made posture data set is tested with the results that the method can greatly reduce network parameters and improve network speed compared with other existing classification methods. To some extent, as a core technology of the PSS control terminal, this technology can perfect users' experiences, better serve consumers and promote the development of the PSS. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
22128271
Volume :
83
Database :
Supplemental Index
Journal :
Procedia CIRP
Publication Type :
Academic Journal
Accession number :
137340313
Full Text :
https://doi.org/10.1016/j.procir.2019.04.145