Activity Recognition Based on Streaming Sensor Data for Assisted Living in Smart Homes

被引：10
|
作者：
Chen, Beichen [1 ]
Fan, Zhong [1 ]
Cao, Fengming [1 ]
机构：
[1] Toshiba Res Europe Ltd, Telecommun Res Lab, 32 Queen Sq, Bristol BS1 4ND, Avon, England
来源：
2015 INTERNATIONAL CONFERENCE ON INTELLIGENT ENVIRONMENTS IE 2015 | 2015年
关键词：
activity recognition; machine learning; assisted living;
D O I：
10.1109/IE.2015.25
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper proposes an activity recognition method for streaming sensor data in smart homes. Experiments on real datasets have been carried out to show the effectiveness of the proposed approach. It has great potential for applications in e-health and assisted living.
引用
收藏
页码：124 / 127
页数：4
相关论文
共 50 条
  • [41] Recognition of Fuzzy Contexts from Temporal Data under Uncertainty Case Study: Activity Recognition in Smart Homes
    Amirjavid, Farzad
    Bouzouane, Abdenour
    Bouchard, Bruno
    Bouchard, Kevin
    2012 IEEE 13TH INTERNATIONAL CONFERENCE ON INFORMATION REUSE AND INTEGRATION (IRI), 2012, : 231 - 238
  • [42] Probabilistic ontology based activity recognition in smart homes using Markov Logic Network
    Gayathri, K. S.
    Easwarakumar, K. S.
    Elias, Susan
    KNOWLEDGE-BASED SYSTEMS, 2017, 121 : 173 - 184
  • [43] A Genetic Algorithm-based Classifier Ensemble Optimization for Activity Recognition in Smart Homes
    Fatima, Iram
    Fahim, Muhammad
    Lee, Young-Koo
    Lee, Sungyoung
    KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS, 2013, 7 (11): : 2853 - 2873
  • [44] A Low-cost Activity Recognition System for Smart Homes
    Malkani, Yasir Arfat
    Memon, Waseem Ahmed
    Das Dhomeja, Lachhman
    2018 5TH IEEE INTERNATIONAL CONFERENCE ON ENGINEERING TECHNOLOGIES AND APPLIED SCIENCES (IEEE ICETAS), 2018,
  • [45] EEM: evolutionary ensembles model for activity recognition in Smart Homes
    Muhammad Fahim
    Iram Fatima
    Sungyoung Lee
    Young-Koo Lee
    Applied Intelligence, 2013, 38 : 88 - 98
  • [46] Integration of discriminative and generative models for activity recognition in smart homes
    Fahad, Labiba Gillani
    Rajarajan, Muttukrishnan
    APPLIED SOFT COMPUTING, 2015, 37 : 992 - 1001
  • [47] A Novel and Distributed Approach for Activity Recognition Inside Smart Homes
    Plantevin, Valere
    Bouzouane, Abdenour
    Bouchard, Bruno
    Gaboury, Sebastien
    2018 IEEE SMARTWORLD, UBIQUITOUS INTELLIGENCE & COMPUTING, ADVANCED & TRUSTED COMPUTING, SCALABLE COMPUTING & COMMUNICATIONS, CLOUD & BIG DATA COMPUTING, INTERNET OF PEOPLE AND SMART CITY INNOVATION (SMARTWORLD/SCALCOM/UIC/ATC/CBDCOM/IOP/SCI), 2018, : 726 - 733
  • [48] EEM: evolutionary ensembles model for activity recognition in Smart Homes
    Fahim, Muhammad
    Fatima, Iram
    Lee, Sungyoung
    Lee, Young-Koo
    APPLIED INTELLIGENCE, 2013, 38 (01) : 88 - 98
  • [49] Exploiting Passive RFID Technology for Activity Recognition in Smart Homes
    Fortin-Simard, Dany
    Bilodeau, Jean-Sebastien
    Bouchard, Kevin
    Gaboury, Sebastien
    Bouchard, Bruno
    Bouzouane, Abdenour
    IEEE INTELLIGENT SYSTEMS, 2015, 30 (04) : 7 - 15
  • [50] On the Design of Smart Homes: A Framework for Activity Recognition in Home Environment
    Cicirelli, Franco
    Fortino, Giancarlo
    Giordano, Andrea
    Guerrieri, Antonio
    Spezzano, Giandomenico
    Vinci, Andrea
    JOURNAL OF MEDICAL SYSTEMS, 2016, 40 (09)
12345