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IoT-Cloud Enabled Statistical Analysis and Visualization of Air Pollution Data in India

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Proceedings of Data Analytics and Management

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 91))

Abstract

Air pollution is a significant issue in our environment. Over the last few decades, urbanization and industrialization have accelerated in developing countries, resulting in an outsized problem of air pollution. In this paper, we have studied the air quality data gathered from IoT-enabled devices and stored onto Cloud storage infrastructure, published by the Indian government Web site. For many Indian states, we have considered the various analysis factors and tried to visualize the IoT-enabled air pollution data, and analyzed the impact of pollution on human life in our society. Furthermore, we have analyzed the air pollution on dataset based on certain conditions using the correlation and heatmap.

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Author information

Authors and Affiliations

  1. Department of Computer Science, Jamia Milla Islamia, New Delhi, India

    Manzoor Ansari & Mansaf Alam

Authors
  1. Manzoor Ansari
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  2. Mansaf Alam
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Corresponding author

Correspondence to Manzoor Ansari .

Editor information

Editors and Affiliations

  1. Maharaja Agrasen Institute of Technology, New Delhi, Delhi, India

    Deepak Gupta

  2. Jan Wyzykowski University, Polkowice, Poland

    Zdzislaw Polkowski

  3. Maharaja Agrasen Institute of Technology, New Delhi, Delhi, India

    Ashish Khanna

  4. Rajnagar Mahavidyalaya, Birbhum, West Bengal, India

    Siddhartha Bhattacharyya

  5. Tijuana Institute of Technology, Tijuana, Mexico

    Oscar Castillo

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© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Cite this paper

Ansari, M., Alam, M. (2022). IoT-Cloud Enabled Statistical Analysis and Visualization of Air Pollution Data in India. In: Gupta, D., Polkowski, Z., Khanna, A., Bhattacharyya, S., Castillo, O. (eds) Proceedings of Data Analytics and Management . Lecture Notes on Data Engineering and Communications Technologies, vol 91. Springer, Singapore. https://doi.org/10.1007/978-981-16-6285-0_11

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