Abstract

Air quality control systems are essential for addressing pollution issues in Indonesia, a country facing significant air quality challenges due to rapid urbanization and industrialization. Over a 30-day testing period, the system successfully transmitted 98.7% of 43,200 data packets to a MySQL server via HTTP protocols with an average transmission delay of 2.3 seconds. The Tsukamoto fuzzy inference engine achieved 94.2% accuracy when validated against standard air quality measurements, processing environmental parameters with a response time of 150 ms. This research proposes the design and development of an Internet of Things (IoT)-based air quality monitoring system using Tsukamoto Fuzzy Logic to provide real-time air quality assessments. The system employs DHT11 sensors to measure temperature and humidity, and MQ135 sensors to detect gas and smoke levels, with data processing conducted on an ESP32 microcontroller. The processed data is transmitted via HTTP protocols to a MySQL server for storage and further analysis. This prototype includes a web-based dashboard that visualizes air quality data through graphs and logs, enabling users to monitor environmental conditions effectively. The integration of Tsukamoto Fuzzy Logic ensures accurate categorization of air quality into good or poor conditions. The system provides actionable insights for government interventions and promotes public awareness to mitigate the adverse health effects of air pollution. This work contributes to smart city initiatives by offering a scalable, real-time solution for air quality control, enhancing urban livability and sustainability.

Concepts :

Access to Document

SDGs

Citations by Year