Estimation of Human Occupancy in Enclosed Spaces Using CO₂ Sensor Data and Statistical Modeling for HVAC Control Applications

¹ VSB-Technical University of Ostrava, 17. listopadu 15/2172, Ostrava, Czech Republic
² Advanced Institute of Convergence Technology, Suwon-si, 16229, South Korea
³ Department of Industrial Engineering, Sungkyunkwan University, 2066 Seobu-ro, Jangan-gu, Suwon, 16419, South Korea

^* Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.

Abstract

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.