Estimation of Human Occupancy in Enclosed Spaces Using CO₂ Sensor Data and Statistical Modeling for HVAC Control Applications
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27350%2F25%3A10259333" target="_blank" >RIV/61989100:27350/25:10259333 - isvavai.cz</a>
Result on the web
<a href="https://www.e3s-conferences.org/articles/e3sconf/abs/2025/67/e3sconf_aee2025_01008/e3sconf_aee2025_01008.html" target="_blank" >https://www.e3s-conferences.org/articles/e3sconf/abs/2025/67/e3sconf_aee2025_01008/e3sconf_aee2025_01008.html</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1051/e3sconf/202566701008" target="_blank" >10.1051/e3sconf/202566701008</a>
Alternative languages
Result language
angličtina
Original language name
Estimation of Human Occupancy in Enclosed Spaces Using CO₂ Sensor Data and Statistical Modeling for HVAC Control Applications
Original language description
This study investigates the estimation of human occupancy in enclosed indoor spaces using CO₂ concentration data obtained from a low-cost sensor. An experimental campaign was conducted in a naturally ventilated university classroom, where CO₂ levels and the number of occupants were recorded under controlled conditions. Statistical analysis, including linear regression and correlation methods, confirmed a strong positive relationship between occupancy and CO₂ accumulation. The selected NDIR sensor (MH-Z16), integrated with an ESP32-based microcontroller, demonstrated sufficient sensitivity and stability for real-time data acquisition. The results validate the use of CO₂ concentration as a reliable indirect indicator of human presence, particularly under standardized conditions with minimal external disturbances. The proposed approach offers a cost-effective and scalable solution for demand-controlled ventilation (DCV) in smart building applications, contributing to energy-efficient HVAC control and proactive indoor air quality and workplace safety management.
Czech name
—
Czech description
—
Classification
Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
20201 - Electrical and electronic engineering
Result continuities
Project
<a href="/en/project/TM04000003" target="_blank" >TM04000003: Development of autonomous driving smart air cleaner and safety control services platform for improving indoor air quality(IAQ) in industrial and public sites</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
E3S Web of Conferences. Volume 667
ISBN
—
ISSN
2267-1242
e-ISSN
2267-1242
Number of pages
14
Pages from-to
1-14
Publisher name
EDP Sciences
Place of publication
Les Ulis
Event location
Ostrava
Event date
Nov 26, 2025
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
—