Paper Title
Water Quality Prediction For Agriculture
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Keywords
Parameter, Accuracy, Heatmap Generation, Time series analysis,Prediction.
Abstract
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.
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How To Cite (APA)
G.Siva Prakash, A.Rakesh, A.Gowri supramanian, & Dr.R.Arthy (March-2023). Water Quality Prediction For Agriculture. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 8(3), c633-c637. https://ijnrd.org/papers/IJNRD2303271.pdf
Issue
Volume 8 Issue 3, March-2023
Pages : c633-c637
Other Publication Details
Paper Reg. ID: IJNRD_188593
Published Paper Id: IJNRD2303271
Downloads: 000122253
Research Area: Engineering
Author Type: Indian Author
Country: Madurai, TamilNadu, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2303271.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2303271
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