Developing an EEG-Based Building Management System to Enhance Built Environment Accessibility for Disabled Users

Tongrui Zhang^1*, Ali GhaffarianHoseini¹, Amirhosein GhaffarianHoseini^2,3, Nicola Naismith¹, Attiq ur Rehman¹, Ruggiero Lovreglio⁴, Dat Doan Tien¹, Okechukwu Nwadigo¹, John Tookey¹

1. ¹Department of Built Environment Engineering, School of Engineering, Computer and Mathematical Sciences, AUT University, Auckland, New Zealand
2. ²Faculty of Engineering and Architectural Science, Ryerson University, Toronto, Canada
3. ³Faculty of Arts and Social Sciences, University of Malaya (UM), Kuala Lumpur, Malaysia
4. ⁴Department of Civil and Environmental Engineering, The University of Auckland, 20 Symonds Street, Auckland, New Zealand

Published in The Fourth NZAAR International Event Series on Natural and Built Environment, Cities, Sustainability and Advanced Engineering, Kuala Lumpur, Malaysia, 27 January 2018, pages 40 to 42. New Zealand Academy of Applied Research. ISSN 2463-5979 (online), 2463-5960 (print). Indexed in the Web of Science Core Collection, Conference Proceedings Citation Index (Clarivate).

Abstract

Nowadays, research on improving built environment accessibility have a significant effect on occupants’ daily life, especially for disable occupants. The existing smart building facility smart control solutions enhance the built environment accessibility, however, fail to consider the disables. In this regards, electroencephalogram (EEG) technology is raised up to provide specific care for the disables. It involves a Brain-Computer Interface (BCI) which processes the data received from an enhanced or wired brain and sends signals to external devices. This paper proposes an adapted framework to enhance the capabilities of the multidimensional building information model integrated knowledge-based building management system for disabled users. This conceptual framework is established through reviewing the existing applications of smart built environment accessibility concerning EEG, BIM and building automation technology, respectively. This research identifies the significance and feasibility of proposing an EEG-based Building Management System (EBMS).

Keywords: Electroencephalography (EEG); Building Information Modelling (BIM); EEG-based Building Management System (EBMS); Smart Accessibility

Rights

Copyright © New Zealand Academy of Applied Research Ltd 2018. All rights reserved. Reproduced in the GDI Academy archive from the original proceedings without change to the authors’ text.