IOT Enabled Air Quality Monitoring System
1st Prof. Anilkumar Ravjibhai Patel
Department Computer Science Engineering PIET
Vadodara, Gujarat anilkumar.patel2986@paruluniversity.ac.in
2th Dr. Sanjay Agal
CSE-AI PIET
Vadodara, Gujarat sanjayagal@gmail.com
3nd Eedara Venkata Ramana
CSE-AI PIET
Vadodara, Gujarat 210303124395@paruluniversity.ac.in
4rd Dasathwar Srinivas
CSE-AI PIET
Vadodara, Gujarat 210303124365@paruluniversity.ac.in
5th Yanamadala Nuthan Kumar
CSE-AI PIET
Vadodara, Gujarat 210303124111@paruluniversity.ac.in
6th Erani Sarvan Kumar
CSE-AI PIET
Vadodara, Gujarat 210303124401@paruluniversity.ac.in
Abstract—Pollution poses one of the most significant threats to our environment, with various types of pollution impacting the Earth’s well-being. In the context of our project, we primarily address air pollution, which is a major concern. Air pollution is responsible for causing numerous health issues in both humans and animals, including respiratory problems. Polluted air con- tains a mixture of harmful gases such as CO2, CO, SO2, smoke, and benzene. To mitigate the effects of these pollutants, we must take measures like avoiding areas with high levels of polluted air. To implement these measures effectively, we require instruments to measure air quality. As a technical solution, we have chosen to develop an Air Quality Index (AQI) system based on the Internet of Things (IoT). This approach is cost-effective, decentralized, efficient, and portable, providing a significant improvement over the traditional method of using complex laboratory equipment, which is both costly and lacks portability. Our project focuses on implementing an AQI system using IoT technology, aiming to transfer data from sensors to an application or web server via the Internet. This technological advancement allows individuals to check air quality in their surroundings easily, offering valuable information for making decisions about their safety. For instance, while travelling in a car, users can quickly assess the air quality index, and if the particulate matter concentration exceeds 1000 ppm, they can identify the air as harmful. We plan to use an Arduino Uno microcontroller for this purpose, as it offers a suitable platform for programming in C and C++ and is supported by a thriving community and libraries.
