ADFIST: Adaptive Dynamic Fuzzy Inference System Tree Driven by Optimized Knowledge Base for Indoor Air Quality Assessment.

ABSTRACT: Air quality levels do not just affect climate change; rather, it leaves a significant impact on public health and wellbeing. Indoor air pollution is the major contributor to increased mortality and morbidity rates. This paper is focused on the assessment of indoor air quality based on several important pollutants (PM₁₀, PM_2.5, CO₂, CO, tVOC, and NO₂). These pollutants are responsible for potential health issues, including respiratory disease, central nervous system dysfunction, cardiovascular disease, and cancer. The pollutant concentrations were measured from a rural site in India using an Internet of Things-based sensor system. An Adaptive Dynamic Fuzzy Inference System Tree was implemented to process the field variables. The knowledge base for

SUBMITTER: Saini J 

PROVIDER: S-EPMC8838659 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature