An Intelligent IoT Fuzzy Based Approach for Automated Indoor Air Quality Monitoring

Indoor air quality has a critical impact on human and animal health and well-being. Because of the confinement during the Covid-19 health crisis, millions of people were forced to stay at home. Therefore, living environments should incorporate an automated monitoring system to detect unfavorable air quality scenarios. Also, Internet of things (IoT) due to their ability to carry air low-cost sensing units have become a cheap alternative to monitor pollution values in a given area. However, enough still needs to be learned as these types of studies are expected to increase in the future years. In this paper, we have developed an intelligent IoT-fuzzy-based device based on low-cost sensors for indoor air quality monitoring (IoT-fuzzy-based AQM). It used a type-1 fuzzy inference system to improve the measurement accuracy of the low-cost sensors and to estimate the air quality index. Experiment tests are made in an indoor environment (home), where the obtained results have proved the effectiveness of the realized system.