IoT-Enabled Chlorine Level Assessment and Prediction in Water Monitoring System Using Machine Learning

IoT-Enabled Chlorine Level Assessment and Prediction in Water Monitoring System Using Machine Learning

The significance of user participation in sustaining drinking water quality and assessing other factors, such as cleanliness, sanitary conditions, preservation, and waste treatment, is essential for preserving groundwater quality. Inadequate water quality spreads disease, causes mortality, and hinde...

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Bibliographic Details
Main Authors: Chandru Vignesh Chinnappan, Alfred Daniel John William, Surya Kalyan Chakravarthy Nidamanuri, S. Jayalakshmi, Ramadevi Bogani, P. Thanapal, Shahada Syed, Boppudi Venkateswarlu, Jafar Ali Ibrahim Syed Masood
Format: Article
Language:English
Published: MDPI AG 2023-03-01
Series:Electronics
Subjects:
IoT
machine learning
residual chlorine
water quality assessment
fuzzy rules
decision tree
Online Access:https://www.mdpi.com/2079-9292/12/6/1458

Internet

https://www.mdpi.com/2079-9292/12/6/1458

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