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Air pollution has become a major environmental concern affecting human health and climate worldwide. To address this issue, this paper proposes an Air Pollution Monitoring and Prediction System based on the Internet of Things (IoT). The system employs smart sensors to measure key air quality parameters such as CO₂, CO, NO₂, SO₂, and particulate matter (PM2.5 and PM10) in real time. The collected data is transmitted to a cloud platform via wireless communication modules for storage, visualization, and analysis. Machine learning algorithms are then applied to predict future pollution levels based on historical and environmental data trends. The system provides real-time alerts and air quality index (AQI) updates through web and mobile interfaces, enabling authorities and citizens to take timely actions. By integrating IoT with predictive analytics, the proposed framework offers a scalable, low-cost, and efficient solution for continuous environmental monitoring and sustainable urban management.
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Copyright © 2020, This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC-BY-NY-SA). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Corresponding Author: Bosubabu Sambana, bosukalam@gmail.com
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
Conflict of interest: The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Publisher’s note: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
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