Please use this identifier to cite or link to this item: http://ir.juit.ac.in:8080/jspui/jspui/handle/123456789/10240
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dc.contributor.authorRohit Raj-
dc.contributor.authorRajiv Kumar [Guided by]-
dc.date.accessioned2023-10-07T10:28:15Z-
dc.date.available2023-10-07T10:28:15Z-
dc.date.issued2023-
dc.identifier.urihttp://ir.juit.ac.in:8080/jspui/jspui/handle/123456789/10240-
dc.descriptionEnrollment No. 191010en_US
dc.description.abstractA water quality monitoring system can aid in preserving the environment, ensuring the security of nearby water sources, and fostering economic growth in rural areas. As a result, this will help to develop a system here that employs Internet of Things and Machine Learning to monitor the quality of water. This paper discusses the characteristics of water to let us know whether it is fit for human consumption or not. The sensors dipped in water samples acquired from wells, lakes, rivers, ponds, or other places are used to inform the development of an effective model made up of TDS, pH and turbidity sensors. The data will be delivered from the sensors as soon as they are received to the IDE, where it will then be sent to the cloud server. The model effectively accounts for test tables, where 1 indicates the water is fit for drinking and 0 indicates the water is not. The values were classified differently using Machine Learning models like SVM, RF and XG Boost method.en_US
dc.language.isoen_USen_US
dc.publisherJaypee University of Information Technology, Solan, H.P.en_US
dc.subjectwater quality monitoringen_US
dc.subjectInternet of thingsen_US
dc.subjectLogistic regressionen_US
dc.subjectArtificial neural networken_US
dc.titleWater Quality Monitoring Systemen_US
dc.typeProject Reporten_US
Appears in Collections:B.Tech. Project Reports

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