Autonomic fall detection system

Ahmet Turan Ozdemir, Cihan Tunc, Salim A Hariri

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations

Abstract

Internet of Things (IoT) and cloud computing have produced major breakthroughs in information services and applications. Internet provided the required connections to countless devices or things that have led to a significant improvement in the quality of life. In addition, using wearable devices and smart sensors has facilitated the deployment of pervasive healthcare services that provided better healthcare, and reduced life threatening risks without affecting one's privacy. In this paper, we present an architectural approach for autonomic healthcare management system and show how to use this system for autonomic fall detection, where we leverage wearable technologies, IoT, and cloud computing.

Original languageEnglish (US)
Title of host publicationProceedings - 2017 IEEE 2nd International Workshops on Foundations and Applications of Self* Systems, FAS*W 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages166-170
Number of pages5
ISBN (Electronic)9781509065585
DOIs
StatePublished - Oct 9 2017
Event2nd IEEE International Workshops on Foundations and Applications of Self* Systems, FAS*W 2017 - Tucson, United States
Duration: Sep 18 2017Sep 22 2017

Other

Other2nd IEEE International Workshops on Foundations and Applications of Self* Systems, FAS*W 2017
CountryUnited States
CityTucson
Period9/18/179/22/17

Keywords

  • cloud computing
  • data analytics
  • fall detection
  • fog computing
  • internet of things
  • wearable devices

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Hardware and Architecture
  • Computational Mechanics

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  • Cite this

    Ozdemir, A. T., Tunc, C., & Hariri, S. A. (2017). Autonomic fall detection system. In Proceedings - 2017 IEEE 2nd International Workshops on Foundations and Applications of Self* Systems, FAS*W 2017 (pp. 166-170). [8064118] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/FAS-W.2017.142