Improving energy consumption of commercial building with IoT and machine learning

Abbas Javed, Hadi Larijani, Andrew Wixted

    Research output: Contribution to journalArticle

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    Abstract

    The critical requirements for devices connected to the Internet of Things (IoT) are long battery life, long coverage range, and low deployment cost. In this work, we developed a machine learning based smart controller for the HVAC of commercial building using LoRa and compared it with short range RF communication in an indoor setting. The comparison was made in terms of battery life, coverage range and memory size. The effect of changing the transmission power of LoRa on battery consumption of the sensor node was also evaluated. Results show that coverage range of LoRa was 60.4% more than short range communication inside a building. The smart controller was capable of identifying when the room was unoccupied and turning off the HVAC which reduced the energy consumption up to 19.8%.
    Original languageEnglish
    Pages (from-to)30-38
    Number of pages9
    JournalIT Professional
    Volume20
    Issue number5
    DOIs
    Publication statusPublished - 25 Oct 2018

    Fingerprint

    Learning systems
    Energy utilization
    Controllers
    Communication
    Power transmission
    Sensor nodes
    Data storage equipment
    Costs
    HVAC
    Internet of things

    Keywords

    • energy consumption
    • commercial building
    • IoT
    • Internet of Things
    • HVAC

    Cite this

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    title = "Improving energy consumption of commercial building with IoT and machine learning",
    abstract = "The critical requirements for devices connected to the Internet of Things (IoT) are long battery life, long coverage range, and low deployment cost. In this work, we developed a machine learning based smart controller for the HVAC of commercial building using LoRa and compared it with short range RF communication in an indoor setting. The comparison was made in terms of battery life, coverage range and memory size. The effect of changing the transmission power of LoRa on battery consumption of the sensor node was also evaluated. Results show that coverage range of LoRa was 60.4{\%} more than short range communication inside a building. The smart controller was capable of identifying when the room was unoccupied and turning off the HVAC which reduced the energy consumption up to 19.8{\%}.",
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    Improving energy consumption of commercial building with IoT and machine learning. / Javed, Abbas; Larijani, Hadi; Wixted, Andrew.

    In: IT Professional, Vol. 20, No. 5, 25.10.2018, p. 30-38.

    Research output: Contribution to journalArticle

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    AU - Javed, Abbas

    AU - Larijani, Hadi

    AU - Wixted, Andrew

    N1 - Acceptance in SAN Not yet online at 7-12-17 Duplicate record deleted. AAM uploaded between acceptance and earliest publication. Most appropriate exception applied. ET 26/11/19

    PY - 2018/10/25

    Y1 - 2018/10/25

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    AB - The critical requirements for devices connected to the Internet of Things (IoT) are long battery life, long coverage range, and low deployment cost. In this work, we developed a machine learning based smart controller for the HVAC of commercial building using LoRa and compared it with short range RF communication in an indoor setting. The comparison was made in terms of battery life, coverage range and memory size. The effect of changing the transmission power of LoRa on battery consumption of the sensor node was also evaluated. Results show that coverage range of LoRa was 60.4% more than short range communication inside a building. The smart controller was capable of identifying when the room was unoccupied and turning off the HVAC which reduced the energy consumption up to 19.8%.

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