Dog's life: Wearable activity recognition for dogs

Cassim Ladha, Nils Hammerla, Emma Hughes, Patrick Olivier, Thomas Plötz

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

    52 Citations (Scopus)

    Abstract

    Health and well-being of dogs, either domesticated pets or service animals, are major concerns that are taken seriously for ethical, emotional, and financial reasons. Welfare assessments in dogs rely on objective observations of both frequency and variability of individual behaviour traits, which is often difficult to obtain in a dog's everyday life. In this paper we have identified a set of activities, which are linked to behaviour traits that are relevant for a dog's wellbeing. We developed a collar-worn accelerometry platform that records dog behaviours in naturalistic environments. A statistical classification framework is used for recognising dog activities. In an experimental evaluation we analysed the naturalistic behaviour of 18 dogs and were able to recognise a total of 17 different activities with approximately 70% classification accuracy. The presented system is the first of its kind that allows for robust and detailed analysis of dog activities in naturalistic environments.

    Original languageEnglish
    Title of host publicationUbiComp 2013 - Proceedings of the 2013 ACM International Joint Conference on Pervasive and Ubiquitous Computing
    Pages415-418
    Number of pages4
    DOIs
    Publication statusPublished - 15 Oct 2013
    EventACM International Joint Conference on Pervasive and Ubiquitous Computing 2013 - Zurich, Switzerland
    Duration: 8 Sep 201312 Sep 2013

    Conference

    ConferenceACM International Joint Conference on Pervasive and Ubiquitous Computing 2013
    Abbreviated titleUbiComp 2013
    CountrySwitzerland
    CityZurich
    Period8/09/1312/09/13

    Keywords

    • Activity recognition
    • Animal wellbeing
    • Dog
    • Wearable computing

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