Internet of Things-Based LoRa Air Quality Monitoring System in the University of Jember

In current environmental conditions, air quality is often underestimated even though it is crucial for the survival of living organisms. Good air quality that contains sufficient oxygen for breathing and photosynthesis, as well as stable carbon dioxide levels, is essential for humans, animals, and plants. Pollution factors such as motor vehicle exhaust, factory emissions, and waste burning can reduce air quality and thus have an indirect impact on the health of living beings. This research focuses on air pollution caused by carbon monoxide and carbon dioxide, using the Mamdani fuzzy method to determine uncertainty and vagueness values. An IoT system with two LoRa devices is used to monitor air quality, with data from sensors represented via MATLAB using fuzzy logic for more accurate results. LoRa device integration with Arduino and ESP32 can be used for accurate sensor reading and communication, ensuring proper data transmission between nodes and gateways for real-time monitoring and comparison of gas parameters at different locations. The reading results from the sensors and the monitoring results on the Blynk platform show identical values with 0% error from monitoring. For the percentage of ISPU values from simulation results in MATLAB compared to manual calculations, there is a difference of 1.12% when compared with the reading values from the sensors.