Multiple user activities recognition in smart home

Ya Hua Lee, Fuchun Lin*, Wei Han Chen

*Corresponding author for this work

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

Abstract

In this paper, we investigate the problem of recognizing multiuser activities using wearable devices in a home environment. Our research objective is to provide situation awareness so that a smart home can respond to the needs of its residents based on the accurate detection of their activities. In this research, we compare applying artificial neural network, decision tree and simple logistic regression for model construction and activity detection. Moreover, we also evaluate different architectural alternatives of our smart home system in order to discover the best system configuration. Our unique contribution lies on the low cost of the proposed system design.

Original languageEnglish
Title of host publicationIoT as a Service - Third International Conference, IoTaaS 2017, Proceedings
EditorsYi-Bing Lin, Ilsun You, Der-Jiunn Deng, Chun-Cheng Lin
PublisherSpringer Verlag
Pages202-209
Number of pages8
ISBN (Print)9783030004095
DOIs
StatePublished - 1 Jan 2018
Event3rd International Conference on IoT as a Service, IoTaaS 2017 - Taichun, Taiwan
Duration: 20 Sep 201722 Sep 2017

Publication series

NameLecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST
Volume246
ISSN (Print)1867-8211

Conference

Conference3rd International Conference on IoT as a Service, IoTaaS 2017
CountryTaiwan
CityTaichun
Period20/09/1722/09/17

Keywords

  • Artificial neural network
  • Decision tree
  • Internet of Things
  • Multiple user activities
  • Simple logistic regression
  • Wearable device

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