Reminder Care System: An Activity-Aware Cross-Device Recommendation System

  • May S. Altulyan
  • , Chaoran Huang
  • , Lina Yao
  • , Xianzhi Wang
  • , Salil Kanhere
  • , Yunajiang Cao

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

10 Scopus citations

Abstract

Alzheimer’s disease (AD) affects large numbers of elderly people worldwide and represents a significant social and economic burden on society, particularly in relation to the need for long term care facilities. These costs can be reduced by enabling people with AD to live independently at home for a longer time. The use of recommendation systems for the Internet of Things (IoT) in the context of smart homes can contribute to this goal. In this paper, we present the Reminder Care System (RCS), a research prototype of a recommendation system for the IoT for elderly people with cognitive disabilities. RCS exploits daily activities that are captured and learned from IoT devices to provide personalised recommendations. The experimental results indicate that RCS can inform the development of real-world IoT applications.

Original languageEnglish
Title of host publicationAdvanced Data Mining and Applications - 15th International Conference, ADMA 2019, Proceedings
EditorsJianxin Li, Sen Wang, Shaowen Qin, Xue Li, Shuliang Wang
PublisherSpringer
Pages207-220
Number of pages14
ISBN (Print)9783030352301
DOIs
StatePublished - 2019
Externally publishedYes
Event15th International Conference on Advanced Data Mining and Applications, ADMA 2019 - Dalian, China
Duration: 21 Nov 201923 Nov 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11888 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference15th International Conference on Advanced Data Mining and Applications, ADMA 2019
Country/TerritoryChina
CityDalian
Period21/11/1923/11/19

Keywords

  • Activity recognition
  • Internet of Things
  • Recommender systems
  • Smart home

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