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

By Wayes Tushar, Nipun Wijerathne, Wen-Tai Li, Chau Yuen, H. Vincent Poor, Tapan Kumar Saha, Kristin L. Wood. 2018

109 citations recorded by the source corpus.

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.

Subfields: Building and Construction, Electrical and Electronic Engineering, Environmental Engineering

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In Electrical and Electronic Engineering

  1. Chau Yuen
  2. H. Vincent Poor
  3. Wayes Tushar
  4. Tapan Kumar Saha
  5. Billy Pik Lik Lau
  6. U-Xuan Tan
  7. Yuren Zhou
  8. Meng Zhang

Citations in the corpus