Vayu – An IoT Powered Indoor Air Quality Monitoring System

Air pollution is a growing global concern, impacting public health, ecosystems, and overall quality of life. Effective monitoring and forecasting are crucial for mitigating its effects and enabling proactive interventions. To address this challenge, we developed Vayu, an advanced IoT and Machine Learning-based Air Quality Monitoring System (AQMS) designed to provide real-time insights and predictive analysis. The system integrates and Arduino UNO, ESP8266 Wi-Fi Module, DHT11, MQ2 and MQ135 sensors to continuously measure key air pollutants. This data is transmitted to ThingSpeak for storage and visualization through a dedicated dashboard, which also provides Pushover notifications for timely alerts. To enhance forecasting accuracy, Machine Learning models such as ARIMA, LSTM and others analyses historical trends to predict future air quality levels. By combining real-time monitoring with intelligent forecasting, Vayu empowers individuals, policymakers and organizations with the real time data needed to take informed actions, ultimately contributing to a cleaner and healthier environment.

Authors

Publication Details

Journal
Journal of Information Systems Engineering & Management
Published
2025-04-11
DOI
https://doi.org/10.52783/jisem.v10i34s.5910
Primary Topic
Air Quality Monitoring and Forecasting
Type
article
Field-Weighted Citation Impact
0.00
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article

Vayu – An IoT Powered Indoor Air Quality Monitoring System

M. Sunitha
Journal of Information Systems Engineering & Management
Air Quality Monitoring and Forecasting
article

Vayu – An IoT Powered Indoor Air Quality Monitoring System

M. Sunitha
article en

Abstract

Air pollution is a growing global concern, impacting public health, ecosystems, and overall quality of life. Effective monitoring and forecasting are crucial for mitigating its effects and enabling proactive interventions. To address this challenge, we developed Vayu, an advanced IoT and Machine Learning-based Air Quality Monitoring System (AQMS) designed to provide real-time insights and predictive analysis. The system integrates and Arduino UNO, ESP8266 Wi-Fi Module, DHT11, MQ2 and MQ135 sensors to continuously measure key air pollutants. This data is transmitted to ThingSpeak for storage and visualization through a dedicated dashboard, which also provides Pushover notifications for timely alerts. To enhance forecasting accuracy, Machine Learning models such as ARIMA, LSTM and others analyses historical trends to predict future air quality levels. By combining real-time monitoring with intelligent forecasting, Vayu empowers individuals, policymakers and organizations with the real time data needed to take informed actions, ultimately contributing to a cleaner and healthier environment.

Journal of Information Systems Engineering & ManagementVol. 10(34s)
Openalex Percentile: Top 93%
Air Quality Monitoring and Forecasting
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Vayu – An IoT Powered Indoor Air Quality Monitoring System — M. Sunitha · Journal of Information Systems Engineering & Management (2025) | TGRS Research Map | TGRS