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Virginia Tech

Indoor Human Sensing for Human Building Interaction

Abstract

dc:description.abstract

We inhabit space. This means our deepest mental and emotional understanding of the world is tied intimately to our experiences as we perceive them in a physical context. Just like a book or film may induce a sense of presence, so too may our modern sensor drenched infrastructures and mobile information spaces. With the recent development of personal and ubiquitous computing devices that we always carry with us, and increased connectivity and robustness of wireless connections, there is an increasing tie between people and things around them. This also includes the space people inhabit. However, such enhanced experiences are usually limited to a personal environment with a personal smartphone being the central device. We would like to bring such technology enhanced experiences to large public spaces with many occupants where their movement patterns, and interactions can be shared, recorded, and studied in order to improve the occupants' efficiency and satisfaction. Specifically, we use sensor networks and ubiquitous computing to create smart built environments that are seamlessly aware of and responsive to the occupants. Human sensing system is one of the key enabling technologies for smart built environments. We present our research findings related to the design and deployment of an indoor human sensing system in large public built spaces. We use a case study to illustrate the challenges, opportunities, and lessons for the emerging field of human building interaction. We present several fundamental design trade-offs, applications, and performance measures for the case study.

Degree

thesis:*
Name thesis:degree_name
Master of Science
Level thesis:degree_level
masters
Discipline thesis:degree_discipline
Computer Science and Applications
Department dc:contributor.department
Computer Science
Grantor dc:publisher
Virginia Tech
Year dc:date.issued
2020

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Ma, Nuo
Chair dc:contributor.committeechair
  • Gracanin, Denis
Committee members dc:contributor.committeemember
  • Knapp, R. Benjamin
  • Abbott, A. Lynn

Subjects

dc:subject × 3

Rights

dc:rights
Statement dc:rights
  • In Copyright

Identifiers

dc:identifier.*
Dc Identifier Other
vt_gsexam:26003
OAI identifier oai:identifier
oai:vtechworks.lib.vt.edu:10919/98916

Chain of custody

source
Harvested from
Virginia Tech
Base URL
vtechworks.lib.vt.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Ma, Nuo. Indoor Human Sensing for Human Building Interaction. masters thesis, Virginia Tech, 2020. http://hdl.handle.net/10919/98916