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Machine Learning Techniques and Cloud Computing to Estimate River Water Quality—Survey

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Inventive Communication and Computational Technologies

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 145))

Abstract

The quality of the water for drinking purpose is an important aspect to be considered to the well-being of nature and humans. River water is the major source for drinking, agribusiness, and hydroelectric power plants, and as the river flows through different areas, assessment of change in quality has to be done by the water authorities regularly. This paper displays an overview of arrangements of different machine learning techniques to recognize contamination in waterway water. In this survey, a helpful examination of different river water dataset and categorizer utilized for classifying of river water is done successfully.

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Authors and Affiliations

  1. PG & Research Department of Computer Science, Government Arts College (Autonomous), Coimbatore, Tamil Nadu, India

    M. Ranjithkumar & L. Robert

Authors
  1. M. Ranjithkumar
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  2. L. Robert
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Corresponding author

Correspondence to M. Ranjithkumar .

Editor information

Editors and Affiliations

  1. Department of Electronics and Communication Engineering, Gnanamani College of Technology, Namakkal, Tamil Nadu, India

    G. Ranganathan

  2. Department of Electrical Engineering, Dayeh University, Changhua, Taiwan

    Joy Chen

  3. Department of Informatics Engineering, University of Coimbra, Coimbra, Portugal

    Álvaro Rocha

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Ranjithkumar, M., Robert, L. (2021). Machine Learning Techniques and Cloud Computing to Estimate River Water Quality—Survey. In: Ranganathan, G., Chen, J., Rocha, Á. (eds) Inventive Communication and Computational Technologies. Lecture Notes in Networks and Systems, vol 145. Springer, Singapore. https://doi.org/10.1007/978-981-15-7345-3_32

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  • DOI: https://doi.org/10.1007/978-981-15-7345-3_32

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-7344-6

  • Online ISBN: 978-981-15-7345-3

  • eBook Packages: EngineeringEngineering (R0)

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