An IoT Based Real-Time Air Quality Monitoring System for Electric Bike Warehouse

Abstract

    The air quality is one of the important factors in the natural green world which influences not only human and animal daily life but also affects different industries such as agriculture, production and so on. So, it is necessary to monitor the air quality in real-time to have a comfortable life by developing a suitable green environment. In this study a low-cost and scalable air monitoring system is developed for an electric-bike warehouse in real-time based on the Internet of Things (IoT). In this proposed system, DHT22 sensor, MQ-135 sensor and SHARP GP2Y1014 dust sensor were used to detect four parameters: temperature, humidity, Sulfur dioxide (SO2), and dust intensity. The sensor data are read by Arduino Uno microcontroller and sent the monitored data to ThingSpeak cloud through ESP8266 WiFi module. If any monitored data is out of range, the buzzer alarm system will be activated. Besides, the common-cathode LED (light-emitting diode) is used to indicate the current air quality level, green, light blue, blue and red color represent normal, low, medium and high air pollution levels. The monitored data would be visualized by accessing the ThingSpeak web and mobile application. Apart from that, using machine learning technology to construct a suitable warehouse air quality machine model and make predictions of parameters such that some immediate actions could be taken to alleviate the influence from air pollution.