Dirichlet Process Gaussian Mixture Model for Activity Discovery in Smart Homes with Ambient Sensors

Thuong Nguyen, Duc Viet Le Viet Duc, Quing Zhang, Mohan Karunanithi

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

    Abstract

    Most of the existing approaches to activity recognition in smart homes rely on supervised learning with well annotated sensor data. However obtaining such labeled data is not only challenging but sometimes also an unobtainable task, especially for senior citizens who may suffer various mental health disorders. Other unsupervised learning approaches to activity discovery are based on fixed complexity models that require the number of activities to be specified in advance. Such models may not be suitable for smart home setting as the activity space may change over time. In this paper, we propose to use a Bayesian nonparametric clustering method to discover the activities from ambient sensors deployed in smart homes. Our model can automatically infer the number of activities from observed data, thus can be widely applicable in smart home environment. We test our method on two smart home datasets, including a public dataset and a dataset collected in our project. The experiment results demonstrate the efficiency of our method in activity discovery in smart home environment.
    Original languageEnglish
    Title of host publicationEAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services (Mobiquitous)
    PublisherEuropean Alliance for Innovation
    Publication statusPublished - 7 Nov 2017
    Event14th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services - Melbourne, Australia
    Duration: 7 Nov 201710 Nov 2017
    Conference number: 14
    http://eai.eu/event/mobiquitous/2017

    Conference

    Conference14th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services
    Abbreviated titleMobiQuitous 2017
    CountryAustralia
    CityMelbourne
    Period7/11/1710/11/17
    Internet address

    Keywords

    • activity discovery
    • smart home
    • ambient sensing
    • unsupervised learning
    • Bayesian nonparametric
    • Dirichlet process

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