Indoor Activity Recognition by Using Recurrent Neural Networks

Yu Zhao, Qingjuan Li, Fadi Farha, Tao Zhu, Liming Chen, Huansheng Ning

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

Because of the development of the ageing population, most countries are facing an increasingly serious pension resources problem. With the development of Internet of Things, the integration of smart home and smart retirement provides a new solution for the new smart home for the elderly, to achieve the elderly to intelligently support the elderly. This paper is based on the development of this background, mainly to solve the problem of indoor activity recognition of the elderly, so as to prepare for the construction of smart medical care. The specific research process is to process the sensor data collected from the smart environment, identify different activities using RNN, LSTM and GRU models with strong ability to process time series data, realize the target of activity recognition.
Original languageEnglish
Title of host publicationInternational Conference on Cyber-Living, Cyber-Syndrome and Cyber-Health
Subtitle of host publicationCyberDI 2019, CyberLife 2019: Cyberspace Data and Intelligence, and Cyber-Living, Syndrome, and Health
Place of PublicationSingapore
Pages205-215
Number of pages10
ISBN (Electronic)978-981-15-1925-3
DOIs
Publication statusPublished - 6 Dec 2019

Publication series

NameCyberspace Data and Intelligence, and Cyber-Living, Syndrome, and Health
Volume1138
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937

Keywords

  • activity recognition
  • Smart environment
  • Recurrent Neural Network

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