Air Quality Through IoT and Big Data Analytics

Sree Devi, M.; Rahamathulla, Vempalli

doi:10.1007/978-981-15-0978-0_17

Air Quality Through IoT and Big Data Analytics

M. Sree Devi⁵ &
Vempalli Rahamathulla⁶

Conference paper
First Online: 14 January 2020

870 Accesses
1 Citations

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 37))

Abstract

Air is one of the major important concerns for human life. The survival of human life is completely depending on the air. So, the air is defined as “Lets Live the human life”. The oxygen is much required for life. Fresh air contains more oxygen. More oxygen helps for the better functionality of the body. Nowadays, air is getting polluted due to heavy usage of chemicals, the use of petroleum products and the release of CO₂. So, day by day, the purity of the air is maximum decreasing. Hence, it becomes necessary to monitor air pollution in various segments. The importance of air quality has been recognized in the early 1980s. Different techniques are used to measure air quality. Hence, we propose a new technique of Data science for analyzing the air quality and we have implemented IoT techniques to monitor the air quality.

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Authors and Affiliations

Department of Computer Science, S V University, Tirupati, India
M. Sree Devi
Sree Vidyanikethan Institute of Management, Tirupati, India
Vempalli Rahamathulla

Authors

M. Sree Devi
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Vempalli Rahamathulla
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Correspondence to Vempalli Rahamathulla .

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Editors and Affiliations

Department of Computer Application, SMIT, Sikkim Manipal University, Sikkim, India
Samarjeet Borah
Department of Automatics and Applied Software at the Faculty of Engineering, Aurel Vlaicu University of Arad, Arad, Romania
Valentina Emilia Balas
Faculty of Technical Sciences, Jan Wyzykowski University, Polkowice, Poland
Zdzislaw Polkowski

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Sree Devi, M., Rahamathulla, V. (2020). Air Quality Through IoT and Big Data Analytics. In: Borah, S., Emilia Balas, V., Polkowski, Z. (eds) Advances in Data Science and Management. Lecture Notes on Data Engineering and Communications Technologies, vol 37. Springer, Singapore. https://doi.org/10.1007/978-981-15-0978-0_17

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DOI: https://doi.org/10.1007/978-981-15-0978-0_17
Published: 14 January 2020
Publisher Name: Springer, Singapore
Print ISBN: 978-981-15-0977-3
Online ISBN: 978-981-15-0978-0
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