Integration of autonomous robotics, indoor localization technologies, and iot sensing for real-Time cloud-based indoor air quality monitoring and visualization

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Real-Time monitoring of indoor air quality (IAQ) is significant for ensuring occupants' health and comfort. While smart sensing technologies were used for IAQ monitoring, there is still a gap of quantitatively assessing IAQ and visualizing its interactions with the surrounding physical world. Therefore, this study proposes a novel real-Time IAQ monitoring and visualization system. This system specifically integrates an unmanned ground vehicle (UGV), an indoor localization system, and the Internet of Things (IoT). First, an IoT sensing unit was developed to dynamically measure the concentration of different indoor air pollutants. Second, a UGV was configured with the capability of full autonomy for providing mobility to the sensing unit. Third, an indoor localization system was developed using ultra-wideband technology to track the sensing unit. Fourth, a cloud-based web server was created to establish communication for data transmission. Fifth, a 2D visualization interface was generated to visualize the indoor air condition and its interactions with the physical world. The proposed system was validated in a real-world application at the authors' institution to test its applicability and performance. The proposed system achieved promising performance regarding (1) full navigation autonomy to sense the indoor environment, (2) reliably monitoring and quantifying the indoor air condition, (3) accurately localizing the sensing unit, and (4) intuitively visualizing the IAQ with consideration of both temporal and spatial characteristics of indoor air condition. This study contributes to the body of knowledge by enhancing existing practices of IAQ monitoring using a cost-effective and mobile robotic system and indoor localization technology.

Original languageEnglish (US)
Title of host publicationComputing in Civil Engineering 2023
Subtitle of host publicationData, Sensing, and Analytics - Selected Papers from the ASCE International Conference on Computing in Civil Engineering 2023
EditorsYelda Turkan, Joseph Louis, Fernanda Leite, Semiha Ergan
PublisherAmerican Society of Civil Engineers (ASCE)
Pages707-715
Number of pages9
ISBN (Electronic)9780784485224
DOIs
StatePublished - 2024
EventASCE International Conference on Computing in Civil Engineering 2023: Data, Sensing, and Analytics, i3CE 2023 - Corvallis, United States
Duration: Jun 25 2023Jun 28 2023

Publication series

NameComputing in Civil Engineering 2023: Data, Sensing, and Analytics - Selected Papers from the ASCE International Conference on Computing in Civil Engineering 2023

Conference

ConferenceASCE International Conference on Computing in Civil Engineering 2023: Data, Sensing, and Analytics, i3CE 2023
Country/TerritoryUnited States
CityCorvallis
Period6/25/236/28/23

All Science Journal Classification (ASJC) codes

  • General Computer Science
  • Civil and Structural Engineering

Fingerprint

Dive into the research topics of 'Integration of autonomous robotics, indoor localization technologies, and iot sensing for real-Time cloud-based indoor air quality monitoring and visualization'. Together they form a unique fingerprint.

Cite this