Improving energy consumption of commercial building with IoT and machine learning

Abbas Javed, Hadi Larijani, Andrew Wixted

    Research output: Contribution to journalArticlepeer-review

    30 Citations (Scopus)
    206 Downloads (Pure)

    Abstract

    The critical requirements for devices connected to the Internet of Things are long battery life, long coverage range, and low deployment cost. The authors developed a machine-learning-based smart controller for a commercial buildings HVAC (heating, ventilation, and air conditioning) system using LoRa (a long-range, low-power wireless platform) and compared it with short-range RF communication in an indoor setting. Results show that LoRas coverage range was 60.4 percent more than short-range communication inside the building. The smart controller was capable of identifying when a room was unoccupied and turning off the HVAC, reducing its energy consumption up to 19.8 percent.
    Original languageEnglish
    Pages (from-to)30-38
    Number of pages9
    JournalIT Professional
    Volume20
    Issue number5
    DOIs
    Publication statusPublished - Oct 2018

    Keywords

    • energy consumption
    • commercial building
    • IoT
    • Internet of Things
    • HVAC
    • reducing energy consumption
    • LoRa
    • smart controller
    • Internet of Things
    • machine learning
    • artificial intelligence

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