Sistem Monitoring Kualitas Udara Ruangan Berbasis IoT Dengan Algoritma Fuzzy Logic - Andreas Tandana; Achmad Ridwan; Tan Della Angelica; Caryn Evelyn Tannesia; Rivanco Winson (Universitas Budi Darma, 2026)
Indoor air quality is often not monitored directly, although exposure to pollutant gases, fine particles, unsuitable temperature, and humidity may increase the potential for respiratory health problems. The main problem is that air monitoring devices are commonly expensive, difficult to access, and present technical data that is not easy for users to understand. This study aims to design an Internet of Things (IoT)-based indoor air quality monitoring system that processes sensor data using Fuzzy Logic to produce air quality risk categories rather than disease diagnosis. The system uses an ESP32 DevKit v1, DHT22, MQ-135, and GP2Y1010AU0F sensors, then sends data in real-time through the MQTT protocol to a Mosquitto broker and Python Bridge Server for visualization on a web dashboard. The testing results show that the DHT22 sensor has a maximum error of 0.90% for temperature and 2.17% for humidity, the MQ-135 can distinguish normal to dangerous air conditions, the GP2Y1010AU0F detects PM2.5 up to 89.3 ug/m3, and MQTT communication remains stable with latency below 200 ms. Fuzzy Logic testing produces scores of 15-91 that map clean, moderate, unhealthy, and dangerous air scenarios. The contribution of this study is a low-cost air monitoring prototype that presents real-time air quality information in an understandable form and can support early prevention actions against poor air exposure.