FallCare+: An IoT surveillance system for fall detection

Charles C.H. Hsu, Michael Y.C. Wang, Hsien C.H. Shen, Ranma H.C. Chiang, Charles H.P. Wen

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

11 Scopus citations

Abstract

Recently, the rapid prevalence of mobile devices leads to diversified applications of intelligent IoT systems (including connected devices and cloud computing) for services. Better performance and efficiency can be achieved from well planning and utilizing computing resources. In this paper, we try to explain the system development of communication and computing for fall detection. Feature extraction is the first task along with live video streaming, and the machine learning techniques are involved to determine the fall event. During integrating various IoT components, our system has four developing stages, and is incrementally improved for better performance. We aim at providing experience as a reference for other homecare or medical services in the future.

Original languageEnglish
Title of host publicationProceedings of the 2017 IEEE International Conference on Applied System Innovation
Subtitle of host publicationApplied System Innovation for Modern Technology, ICASI 2017
EditorsTeen-Hang Meen, Artde Donald Kin-Tak Lam, Stephen D. Prior
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages921-922
Number of pages2
ISBN (Electronic)9781509048977
DOIs
StatePublished - 21 Jul 2017
Event2017 IEEE International Conference on Applied System Innovation, ICASI 2017 - Sapporo, Japan
Duration: 13 May 201717 May 2017

Publication series

NameProceedings of the 2017 IEEE International Conference on Applied System Innovation: Applied System Innovation for Modern Technology, ICASI 2017

Conference

Conference2017 IEEE International Conference on Applied System Innovation, ICASI 2017
CountryJapan
CitySapporo
Period13/05/1717/05/17

Keywords

  • Fall detection
  • Home care
  • IoT

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