Water Quality Prediction For Agriculture

G.Siva Prakash , A.Rakesh , A.Gowri supramanian , Dr.R.Arthy

Parameter, Accuracy, Heatmap Generation, Time series analysis,Prediction.

Water is one of the most essential element for the existence of life. The safety and accessibility of drinking-water are major concerns throughout the globe. Health risks may arise from consumption of water contaminated with infectious agents, toxic chemicals etc. In this paper a system is proposed to check the water quality and warn the user before water gets contaminated .There are different parameters that can contaminate the water. These parameters are taken into account and used for predicting when to clean the water. The system uses technologies such as IoT and Machine Learning. It consist of the physical and chemical sensor to measure pH, turbidity ,colour, DO, conductivity etc. to check the parameters .The data obtained from the sensors are recorded in the database and further sent for analysis. The neural network algorithm is used for predicting the result. It is used to obtain non-linear relationship for predicted output. The system sends the alert message to user when any of the parameters are lower than the standard values. This helps the user to know beforehand about the contamination of water in their residential tanks. This technique can not only be limited up to residential tanks but can also be used in water treatment plants and industries.

Published Paper   E-Certificate

"Water Quality Prediction For Agriculture", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.8, Issue 3, page no.c633-c637, March-2023, Available :https://ijnrd.org/papers/IJNRD2303271.pdf

Volume 8 Issue 3, March-2023

Pages : c633-c637

Paper Reg. ID: IJNRD_188593

Published Paper Id: IJNRD2303271

Downloads: 000118857

Research Area: Engineering

Country: Madurai, TamilNadu, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2303271

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2303271

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJNRD (IJ Publication) Janvi Wave

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition