Efficient Monitoring and Adaptive Control of Indoor Air Quality Based on IoT Technology and Fuzzy Inference

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 monitoring and adaptive control of IAQ. Firstly, an indoor air quality monitoring and control system (IAQMCS) is developed using IoT technology. Then, based on fuzzy inference, a novel fuzzy air quality index (FAQI) model is proposed to effectively assess IAQ. Furthermore, a simple adaptive control mechanism, called SACM, is designed to automatically control the IAQMCS according to a real-time FAQI value. Finally, extensive experiments are performed by comparing with regular control (time-based control), which show that our proposed method effectively measures various air parameters (CO2, VOC, HCHO, PM2.5, PM10, etc.) and has good performance in terms of evaluation accuracy, average FAQI value, and overall IAQ.

A Review of Internet of Things-Based Visualisation Platforms for Tracking Household Carbon Footprints

“…An indoor air quality monitoring and control system (IAQMC) was developed by Zhao et al [39]. This groundbreaking system uses IoT technology and fuzzy inference.…”

Retracted: Efficient Monitoring and Adaptive Control of Indoor Air Quality Based on IoT Technology and Fuzzy Inference

“…This article has been retracted by Hindawi following an investigation undertaken by the publisher [1]. This investigation has uncovered evidence of one or more of the following indicators of systematic manipulation of the publication process:…”