Javed, Abbas

Larijani, Hadi

Wixted, Andrew

English

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

ResearchOnline@GCU

Improving energy consumption of commercial building with IoT and machine learning

Abbas Javed

Hadi Larijani

Andrew Wixted

Crossref

Improving Energy Consumption of a Commercial Building with IoT and Machine Learning

https://researchonline.gcu.ac.uk/files/25489995/IT_ITPro_2016_12_0114_.R1_Larijani.pdf

Improving energy consumption of commercial building with IoT and machine learning

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ResearchOnline@GCU

Crossref