A user-guided personalization methodology to facilitate new smart home occupancy

被引:0
|
作者
S. M. Murad Ali
Juan Carlos Augusto
David Windridge
Emma Ward
机构
[1] Middlesex University,Department of Computer Science
[2] Middlesex University,Department of Psychology
关键词
Smart home; System adaptation; Transfer learning; System personalisation;
D O I
暂无
中图分类号
学科分类号
摘要
Smart homes are becoming increasingly popular in providing people with the services they desire. Activity recognition is a fundamental task to provide personalised home facilities. Many promising approaches are being used for activity recognition; one of them is data-driven. It has some fascinating features and advantages. However, there are drawbacks such as the lack of ability to providing home automation from the day one due to the limited data available. In this paper, we propose an approach, called READY (useR-guided nEw smart home ADaptation sYstem) for developing a personalised automation system that provides the user with smart home services the moment they move into their new house. The system development process was strongly user-centred, involving users in every step of the system’s design. Later, the user-guided transfer learning approach was introduced that uses an old smart home data set to enhance the existing smart home service with user contributions. Finally, the proposed approach and designed system were tested and validated in the smart lab that showed promising results.
引用
收藏
页码:869 / 891
页数:22
相关论文
共 10 条
  • [1] A user-guided personalization methodology to facilitate new smart home occupancy
    Ali, S. M. Murad
    Augusto, Juan Carlos
    Windridge, David
    Ward, Emma
    [J]. UNIVERSAL ACCESS IN THE INFORMATION SOCIETY, 2023, 22 (03) : 869 - 891
  • [2] Toward Personalization of User Preferences in Partially Observable Smart Home Environments
    Suman S.
    Rivest F.
    Etemad A.
    [J]. IEEE Transactions on Artificial Intelligence, 2023, 4 (03): : 549 - 561
  • [3] User-guided motion planning with reinforcement learning for human-robot collaboration in smart manufacturing
    Yu, Tian
    Chang, Qing
    [J]. EXPERT SYSTEMS WITH APPLICATIONS, 2022, 209
  • [4] New user-guided and ckpt-based checkpointing libraries for parallel MPI applications
    Czarnul, P
    Fraczak, M
    [J]. RECENT ADVANCES IN PARALLEL VIRTUAL MACHINE AND MESSAGE PASSING INTERFACE, PROCEEDINGS, 2005, 3666 : 351 - 358
  • [5] Improving the Adaptation Process for a New Smart Home User
    Ali, S. M. Murad
    Augusto, Juan Carlos
    Windridge, David
    [J]. ARTIFICIAL INTELLIGENCE XXXVI, 2019, 11927 : 421 - 434
  • [6] "Teach Me-Show Me"-End-User Personalization of a Smart Home and Companion Robot
    Saunders, Joe
    Syrdal, Dag Sverre
    Koay, Kheng Lee
    Burke, Nathan
    Dautenhahn, Kerstin
    [J]. IEEE TRANSACTIONS ON HUMAN-MACHINE SYSTEMS, 2016, 46 (01) : 27 - 40
  • [7] Fraship: A Framework to Support End-User Personalization of Smart Home Services with Runtime Knowledge Graph
    Huang, Zhiming
    Chen, Jiawen
    Shen, Liwei
    Chen, Xing
    [J]. COMPANION PROCEEDINGS OF THE WEB CONFERENCE 2022, WWW 2022 COMPANION, 2022, : 987 - 995
  • [8] Design of a New Method for Detection of Occupancy in the Smart Home Using an FBG Sensor
    Vanus, Jan
    Nedoma, Jan
    Fajkus, Marcel
    Martinek, Radek
    [J]. SENSORS, 2020, 20 (02)
  • [9] A Survey of User-Centred Approaches for Smart Home Transfer Learning and New User Home Automation Adaptation
    Ali, S. M. Murad
    Augusto, Juan Carlos
    Windridge, David
    [J]. APPLIED ARTIFICIAL INTELLIGENCE, 2019, 33 (08) : 747 - 774
  • [10] Do We Really Need to Catch Them All? A New User-Guided Social Media Crawling Method
    Erlandsson, Fredrik
    Brodka, Piotr
    Boldt, Martin
    Johnson, Henric
    [J]. ENTROPY, 2017, 19 (12)