Smart Air Quality Analysis Using Fuzzy Logic for Health Risk Prevention

Abstract

This study examines an intelligent system for analyzing air quality using fuzzy logic as a decision-making tool to reduce health risks. The system is designed to monitor air quality in real-time and calculate the Air Quality Index (AQI) accurately. By applying the Mamdani method, this system is able to predict the level of air pollution and identify conditions that have the potential to endanger human health. Through processing uncertain and ambiguous data, fuzzy logic helps provide a more precise interpretation of the environmental situation. The analysis results of this system also provide recommendations for actions that need to be taken to prevent the adverse effects of air pollution. Continuous monitoring allows users to obtain direct information regarding the condition of the surrounding air, so that prevention can be carried out more quickly and precisely. This system plays an important role in supporting efforts to protect public health proactively.