Air Pullution Monitoring and Detection System Design Using Fuzzy Method Based on IoT - Firga Deman Samudra; Miftachul Ulum; Koko Joni; Diana Rahmawati (Universitas Muhammadiyah Sidoarjo, 2021)
The large amount of air pollution that occurs in the community is caused by the increase in the number of motorized vehicles and human activities, as well as the limited sense of sight and smell of humans so that they cannot feel the presence of pollutant gases that are harmful to health, so we need a tool that can detect and monitor pollutant gases so they don't exceed the threshold. In this study, a monitoring system and air pollution detection using the fuzzy Sugeno method based on the Internet of Things (IoT) is designed. In this system the MQ-7, MQ-135 and MQ-131 sensors are used to detect CO, CO2 and Ozone gases, while the Sharp GP2Y1010AU0F sensor functions to detect dust. The results of these sensor readings are processed by the Arduino Uno and NodeMCU microcontrollers to be displayed on the P10 panel and sent to the Antares IoT Cloud server which can be accessed in real time. The results of this study have an accuracy rate of approximately 97% for gas sensors, both CO, CO2, and Ozone gas sensors. As for the dust sensor, the accuracy rate is 93.83%.