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International Journal of Creative and Open Research in Engineering and Management

A Peer-Reviewed, Open-Access International Journal Supporting Multidisciplinary Research, Digital Publishing Standards, DOI Registration, and Academic Indexing.
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ISSN: 3108-1754 (Online)
Crossref DOI: Available
ISO Certification: 9001:2015
Publication Fee: 599/- INR
Compliance: UGC Journal Norms
License: CC BY 4.0
Peer Review: Double Blind
Volume 02, Issue 05

Published on: May 2026

AIR QUALITY VISUALIZER AND 72-HOUR AQI FORECASTING SYSTEM USING SATELLITE DATA AND MACHINE LEARNING

Santhosh S Anbuchelvan M Tamil Selvan S

A. Kayalvizhi

Department of Artificial Intelligence and Data Science  Sri Ramakrishna Engineering College

Coimbatore,India Coimbatore, India
DOI:https://doi.org/10.55041/ijcope.v2i5.721

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Abstract

Ground-level air quality sensors remain largely absent from rural and semi-urban pockets of India, leaving residents with no reliable way to gauge daily pollution exposure. To address this blind spot, we designed and built a satellite-driven web platform that computes, maps, and predicts the Air Quality Index (AQI) for any named location nationwide without depending on physical monitoring infrastructure. Atmospheric concentration data retrieved from orbital instruments are standardized and processed according to the breakpoint interpolation method prescribed by India’s Central Pollution Control Board (CPCB), yielding AQI values that conform to the national reporting standard. A Long Short-Term Memory (LSTM) neural network trained on historical pollution records then extends the assessment window to 24, 48, and 72 hours, enabling proactive rather than reactive responses to deteriorating air quality. Whenever forecasted levels threaten to enter hazardous territory, the platform automatically compiles and displays health guidance calibrated to the projected severity. Trials conducted across multiple districts in Tamil Nadu showed strong agreement between satellite-derived index values and anticipated pollution behaviour, supporting wider deployment as a cost-free alternative to fixed sensor infrastructure.

Index Terms—Air Quality Index, Satellite Data, AQI Forecasting, LSTM, Environmental Monitoring, Health Advisory System.

How to Cite this Paper

S, S., M, A. & S, T. S. (2026). Air Quality Visualizer and 72-Hour AQI Forecasting System Using Satellite Data and Machine Learning. International Journal of Creative and Open Research in Engineering and Management, <i>02</i>(05). https://doi.org/10.55041/ijcope.v2i5.721

S, Santhosh, et al.. "Air Quality Visualizer and 72-Hour AQI Forecasting System Using Satellite Data and Machine Learning." International Journal of Creative and Open Research in Engineering and Management, vol. 02, no. 05, 2026, pp. . doi:https://doi.org/10.55041/ijcope.v2i5.721.

S, Santhosh,Anbuchelvan M, and Tamil S. "Air Quality Visualizer and 72-Hour AQI Forecasting System Using Satellite Data and Machine Learning." International Journal of Creative and Open Research in Engineering and Management 02, no. 05 (2026). https://doi.org/https://doi.org/10.55041/ijcope.v2i5.721.

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Ethical Compliance & Review Process

  • •All submissions are screened under plagiarism detection.
  • •Review follows editorial policy.
  • •Authors retain copyright.
  • •Peer Review Type: Double-Blind Peer Review
  • •Published on: May 23 2026
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