Design and Implementation of an IoT-Based Roadside Air Quality Monitoring System Using ESP32 Multi-Sensor and Mamdani Fuzzy Logic Integrated with Blynk

Abstract

Increased volume of road transportation can worsen air quality and negatively impact the health of road users. The project aims to develop and implement a highway air quality monitoring system that leverages the Internet of Things (IoT), with multi-sensor integration and Mamdani's fuzzy logic for air quality evaluation. The system consists of an ESP32 microcontroller integrated with a BME280 sensor to measure temperature, humidity, and pressure, an MQ-135 sensor to detect gaseous pollutants, and a GP2Y1010AU0F dust sensor to assess particle concentration. Sensor data is sent in real-time to Blynk's IoT platform over Wi-Fi and displayed as numerical values, graphs, and time-series graphs. Gas and dust measurements are further processed through Mamdani's fuzzy logic system to generate a Fuzzy Air Quality (Fuzzy AQ) score, which ranges from 0 to 100 and is categorized into three levels: low, medium, and high. The experimental results showed that the system could consistently monitor air quality parameters and present up-to-date air quality status through the Blynk app, with fuzzy outputs that correspond to sensor fluctuations and open up opportunities for expansion to other roadside monitoring locations in the future.