Internet of Things for Green Building Management: Disruptive Innovations Through Low-Cost Sensor Technology and Artificial Intelligence

Published on Sep 1, 2018in IEEE Signal Processing Magazine7.602
· DOI :10.1109/MSP.2018.2842096
Wayes Tushar16
Estimated H-index: 16
(UQ: University of Queensland),
Nipun Wijerathne4
Estimated H-index: 4
+ 4 AuthorsKristin L. Wood39
Estimated H-index: 39
(NUS: National University of Singapore)
Buildings consume 60% of global electricity. However, current building management systems (BMSs) are highly expensive and difficult to justify for small- to medium-sized buildings. The Internet of Things (IoT), which can collect and monitor a large amount of data on different aspects of a building and feed the data to the BMS's processor, provides a new opportunity to integrate intelligence into the BMS for monitoring and managing a building's energy consumption to reduce costs. Although an extensive literature is available on, separately, IoTbased BMSs and applications of signal processing techniques for some building energy-management tasks, a detailed study of their integration to address the overall BMS is limited. As such, this article will address the current gap by providing an overview of an IoT-based BMS that leverages signal processing and machine-learning techniques. We demonstrate how to extract high-level building occupancy information through simple, low-cost IoT sensors and study how human activities impact a building's energy use-information that can be exploited to design energy conservation measures that reduce the building's energy consumption.
  • References (28)
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