A Hybrid Accuracy- and Energy-Aware Human Activity Recognition Model in IoT Environment-Reference-Cited by-同舟云学术

A Hybrid Accuracy- and Energy-Aware Human Activity Recognition Model in IoT Environment

Author:

Jha Devki Nandan¹^ORCID,Chen Zhenghua²^ORCID,Liu Shudong²^ORCID,Wu Min²^ORCID,Zhang Jiahan³,Morgan Graham³^ORCID,Ranjan Rajiv³,Li Xiaoli²^ORCID

Affiliation:

1. Oxford e-Research Centre, University of Oxford, Oxford, U.K.

2. Institute of Infocomm Research, and Centre for Frontier AI Research, A*STAR, Singapore

3. Newcastle University, Newcastle upon Tyne, U.K.

Funder

U.K. Research and Innovation council

Internet of Energy

National Research Foundation Singapore

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computational Theory and Mathematics,Control and Optimization,Hardware and Architecture,Renewable Energy, Sustainability and the Environment,Software

Link

Reference50 articles.

2. Deep, convolutional, and recurrent models for human activity recognition using wearables;hammerla;Proc 25th Int Joint Conf Artif Intell,2016

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