In recent years, more and more occupants have suffered from respiratory illness due to poor indoor air quality (IAQ). In order to address this issue, this paper presents a method to achieve efficient assessment and adaptive control of IAQ. Firstly, based on fuzzy inference, a novel fuzzy air quality index (FAQI) model is proposed to effectively assess IAQ. Then, a simple adaptive control mechanism, called SACM, is designed to automatically control the ventilation system (actuator) according to real-time FAQI value. Finally, simulation experiments are per-formed by comparing with regular control (time-based control), which show that our proposed method comprehensively evaluates overall IAQ using various air parameters (CO2, VOC, HCHO, PM2.5, PM10, etc), and reduces average FAQI value.
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Indoor air quality assessment and control using fuzzy inference
Semantic Scholar · Environmental Science · 2022
Abstract
In recent years, more and more occupants have suffered from respiratory illness due to poor indoor air quality (IAQ). In order to address this issue, this paper presents a method to achieve efficient assessment and adaptive control of IAQ. Firstly, based on fuzzy inference, a novel fuzzy air quality index (FAQI) model is proposed to effectively assess IAQ. Then, a simple adaptive control mechanism, called SACM, is designed to automatically control the ventilation system (actuator) according to real-time FAQI value. Finally, simulation experiments are per-formed by comparing with regular control (time-based control), which show that our proposed method comprehensively evaluates overall IAQ using various air parameters (CO2, VOC, HCHO, PM2.5, PM10, etc), and reduces average FAQI value.