With rapidly changing technology, people have more and more requirements for thermal comforts regarding indoor temperature, humidity, and wind speed, and pay more attention to air quality. Indoor air quality has serious effects on the elderly, children, and those with respiratory allergies. Based on the architecture of the Internet of Things smart home, this study constructed an indoor air quality monitoring system to explore how people can live in an environment with good air quality. Among the numerous air quality indices (AQIs), the carbon dioxide index and AQI of the American Society of Heating, Refrigerating and Air-Conditioning Engineers are selected as the indices suitable for this study. The common points of the two indices are combined, and then, based on the data of the Environmental Protection Administration, indoor and outdoor environmental parameters are analyzed, and controllable environment variables are simulated to analyze their effects on air quality. This study designed effective load control using fuzzy control and developed a fuzzy rule base for simulation of the environment variables. Decision logic was used to replace the threshold control of indoor air quality in the past, and a comfortable air quality monitoring system was designed by combining the Arduino Uno development board and ESP8266 Wi-Fi wireless transmission modules.

随着科技日新月异，人们对室内温度、湿度、风速等热舒适性的要求越来越高，也越来越关注空气质量。室内空气质量对老人、儿童和呼吸道过敏者有严重影响。本研究基于物联网智能家居的架构，构建了室内空气质量监测系统，探索人们如何生活在良好空气质量的环境中。在众多的空气质量指数（AQI）中，美国采暖、制冷和空调工程师学会的二氧化碳指数和AQI被选为适合本研究的指标。结合两个指标的共同点，再以环保总局的数据为基础，分析室内外环境参数，模拟可控环境变量，分析其对空气质量的影响。本研究使用模糊控制设计了有效的负载控制，并开发了用于模拟环境变量的模糊规则库。以往采用决策逻辑代替室内空气质量的阈值控制，结合Arduino Uno开发板和ESP8266 Wi-Fi无线传输模块，设计了一套舒适的空气质量监测系统。