This paper is published in Volume-5, Issue-2, 2019
Area
Computer Engineering
Author
Ashwini K.
Co-authors
J. Janice Vedha, D. Diviya, M. Deva Priya
Org/Univ
Sri Krishna College of Technology, Coimbatore, Tamil Nadu, India
Pub. Date
08 March, 2019
Paper ID
V5I2-1160
Publisher
Keywords
Water quality, Internet of Things (IoT), Machine Learning (ML), K-Nearest Neighbours (KNN), Random forest

Citationsacebook

IEEE
Ashwini K., J. Janice Vedha, D. Diviya, M. Deva Priya. Intelligent model for predicting water quality, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
Ashwini K., J. Janice Vedha, D. Diviya, M. Deva Priya (2019). Intelligent model for predicting water quality. International Journal of Advance Research, Ideas and Innovations in Technology, 5(2) www.IJARIIT.com.

MLA
Ashwini K., J. Janice Vedha, D. Diviya, M. Deva Priya. "Intelligent model for predicting water quality." International Journal of Advance Research, Ideas and Innovations in Technology 5.2 (2019). www.IJARIIT.com.

Abstract

Over the decades, water pollution has been a real threat to the living species. The real-time monitoring of drinking water is nothing less than a challenging task. This paper aims to design and develop a low-cost system for the real-time monitoring of water quality using Internet of Things (IoT) and Machine Learning (ML). The physical and chemical parameters of the water such as temperature, level, moisture, humidity, and visibility are measured using respective sensors. ESP8266, the core controller is employed to process the measured values from the sensors. The data acquired from Sensors are sent to the Django server. Random Forest (RF) and K-Nearest Neighbours (KNN) algorithm are used in the analysis and prediction of water quality.
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