Data sources for a model to predict air temperatures inside a residential home

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    Abstract

    This paper introduces the data sources for a model to predict air temperatures inside a residential home. Sources included local and remote environmental sensors. Data from the sensors is being used to create models of temperature change. The sensor data is expected to lead to new and novel system designs that will combine the new models with traditional heating control to create a new optimal start-stop heating application for residential homes.
    Original languageEnglish
    Pages (from-to)313-319
    JournalJournal of Computing in Systems and Engineering
    Volume15
    Publication statusPublished - 2014

    Keywords

    • thermal comfort
    • Smart Home
    • prediction
    • domestic
    • sensor fusion
    • smart environment
    • AI

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