| Issue |
E3S Web Conf.
Volume 672, 2025
The 17th ROOMVENT Conference (ROOMVENT 2024)
|
|
|---|---|---|
| Article Number | 02004 | |
| Number of page(s) | 6 | |
| Section | Modelling & Measuring: Control & Data Usage | |
| DOI | https://doi.org/10.1051/e3sconf/202567202004 | |
| Published online | 05 December 2025 | |
Smart Indoor Air Quality (IAQ) measurement to enhance occupancy comfort in campus buildings
University Technology Sydney, School of Built Environment, Sydney, Australia
* Corresponding author: arezoo.shirazi@uts.edu.au
Rising Environmental Air Pollution (EAP) and its impact on Indoor Air Quality (IAQ) in urban areas is a growing concern in modern built environment with several interconnected impacts on human health. Therefore, monitoring and managing the overall IAQ of buildings on an ongoing basis is of great importance for public health, environmental sustainability, and the well-being of occupants. In this study, Internet of Things (IoT) sensors are employed to delve into the connections, both in terms of time and space, between diverse concentrations of PM2.5 indoors and outdoors within a university building located in Sydney, Australia. This investigation spanned a period of 5 months. The study’s timeframe encompassed the influences of both Hazard Reduction Burning (HRB) activities and localized instances of high traffic volume under various climatic conditions. The utilization of IoT sensors for real-time PM2.5 measurement provides a precise assessment of indoor air quality. By categorizing indoor areas based on PM2.5 concentrations, this data-driven approach not only enhances occupant protection but also empowers facility managers to strategize the utilization of spaces in ways that prioritize occupant health and comfort while accounting for the dynamic nature of PM2.5 exposure. The myriad of factors influencing indoor PM2.5 levels underscores the necessity of this comprehensive approach to effectively manage and improve indoor air quality. Additionally, hourly examination of PM2.5 concentration reveals the fluctuations in PM2.5 levels over different periods, encompassing daytime, night-time, peak traffic hours, and intervals when heating, ventilation, and air conditioning (HVAC) systems are active. This granular analysis offers insights into how PM2.5 is distributed across various timeframes. The findings from the hourly analysis underscore the necessity of assessing HVAC efficiency and the effectiveness of filtering layers, particularly during instances of severe air pollution like HRB events. This proactive evaluation ensures that HVAC systems remain capable of adequately filtering out PM2.5 particles during heightened pollution episodes. Furthermore, considering alternative options like using portable air filters can be a wise step to enhance indoor air quality during periods of elevated pollution.
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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