Smart Environmental Monitoring System

Smart Environmental Monitoring System

Karthik Sudhakaran Menon, Brinzel Rodrigues, Akash Prakash Barot, Prasad Avinash Gharat
Copyright: © 2019 |Pages: 12
DOI: 10.4018/IJGC.2019010103
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Abstract

In today's world, air pollution has become a common phenomenon everywhere, especially in the urban areas, air pollution is a real-life problem. In urban areas, the increased number of hydrocarbons and diesel vehicles and the presence of industrial areas at the outskirts of the major cities are the main causes of air pollution. The problem is seriously intense within the metropolitan cities. The governments around the world are taking measure in their capability. The main aim of this project is to develop a system which may monitor and measure pollutants in the air in real time, tell the quality of air and log real-time data onto a remote server (Cloud Service). If the value of the parameters exceeds the given threshold value, then an alert message is sent with the GPS coordinates to the registered number of the authority or person so necessary actions can be taken. The Arduino board connects with Thingspeak cloud service platform using ESP8266 Wi-Fi module. The device uses multiple sensors for monitoring the parameters of the air pollution like MQ-135, MQ-7, DHT-22, sound sensor, LCD.
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Literature Survey

Mobile Air Quality Monitoring Network (MAQUMON), it consists of a number of car-mounted sensor nodes measuring different pollutants in the air. The data points are labeled with location co-ordinates and time utilizing an on-board GPS. Periodically, the values are uploaded to a server, processed and then published on the Microsoft SensorMap portal. Given an ample variety of nodes and various quality patterns, a detailed picture of the air quality in a large area will be obtained at a low cost. Sensor nodes equipped with vehicles were easy to install and portable, but the system was not able to send back the data immediately to the system (Kaur, 2015).

Apollo System, APOLLO provides air quality information by collecting independent sensing information from various air components and forwarding the collected data to the host system. The sensors were extensively evaluated each in performance and power management aspects. The sensors can detect CO, CO2, NO2, particulate matter (PM), and volatile organic compounds (VOCs). The system was able to monitor multiple air pollutants simultaneously. The actual implementation of the system was not done in reality (Yang, 2015).

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