IoT-Based Air Quality Monitoring System Using Rule-Based Method in Pertamina Green Village

Abstract

This research aims to design and implement an Internet of Things (Iot)-based air quality monitoring system with rule-based method in Pertamina Green Village. This system is designed to monitor and detect various air quality parameters such as Ozone (O3), Carbon Monoxide (CO), dust particles (PM10), temperature, humidity, and rainy weather detection using various sensors connected through the IoT platform. The sensors used in this system include MQ131 sensor to detect O3, MQ7 sensor for CO, DHT22 sensor for temperature and humidity, ZH03B dust sensor to detect (PM10), and rain sensor. Data from these sensors are sent in real-time to the Blynkcloud platform and telegram application for direct notification to the user. System testing shows that the sensors used are able to detect air quality parameters well. Quality of Service (QOS) test results indicate that the system has Troughput, Packet Loss, and Delay (Latency) which fall into the excellent category, although Jitter is in the medium category. The test results carried out on the five sensors are the average percentage of DHT22 sensor error values of 0.1% for temperature, and -0.4% for humidity, MQ7 sensor of 0.90%, MQ131 of 0.15%, ZH03B of -0.03%, for rain sensors in normal conditions. QOS system tests prove that the use of hotspot internet networks is superior with an average value of 3.25 compared to Wifi which is only 2.9.