Real-time Air Quality Monitoring in Smart Cities using IoT-enabled Advanced Optical Sensors

Air quality control has drawn a lot of attention from both theoretical research and practical application due to the air pollution problem's increasing severity. As urbanization accelerates, the need for effective air quality monitoring in smart cities becomes increasingly critical. Traditional methods of air quality monitoring often involve stationary monitoring stations, providing limited coverage and outdated data. This study proposes an Internet of Things (IoT) centred framework equipped with inexpensive devices to monitor pollutants vital to human health, in line with World Health Organization recommendations, in response to the pressing issue of air pollution and its increased importance. The hardware development entails building a device that can track significant contamination percentages. Ammonia, carbon monoxide, nitrogen dioxide, PM2.5 and PM10 particulate matter, ozone, and nitrogen dioxide. The gadget is driven by the ESP-WROOM-32 microcontroller, which has Bluetooth and Wi-Fi capabilities for easy data connection to a cloud server. It uses PMSA003, MICS-6814, and MQ-131 sensors. The gadget activates indicators when a pollutant concentration exceeds the allowable limit, enhancing its software to enable immediate response and intervention. This work leverages the robust cloud architecture of Amazon Web Server (AWS) to integrate it into the system and improve accessibility and data control. This combination no longer just ensures data preservation but also enables real-time tracking and analysis, which adds to a comprehensive and preventive strategy for reducing air pollution and preserving public health. With an RMSE score of 3.7656, the Real-Time Alerts with AWS Integration model—which was built in Python—has the lowest value.

@article{Aserkar2024,
  title     = {Real-time Air Quality Monitoring in Smart Cities using IoT-enabled Advanced Optical Sensors},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {15},
  number    = {4},
  year      = {2024},
  publisher = {The Science and Information Organization},
  author    = {Anushree A. Aserkar and Sanjiv Rao Godla and Yousef A.Baker El-Ebiary and Krishnamoorthy and Janjhyam Venkata Naga Ramesh},
  doi       = {10.14569/IJACSA.2024.0150487},
  url       = {https://doi.org/10.14569/IJACSA.2024.0150487}
}