Please use this identifier to cite or link to this item: http://ir.juit.ac.in:8080/jspui/jspui/handle/123456789/9860
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dc.contributor.authorChoudhary, Harshul-
dc.contributor.authorRajput, Ujjwal-
dc.contributor.authorKumar, Alok [Guided by]-
dc.contributor.authorDhiman, Pankaj [Guided by]-
dc.date.accessioned2023-09-04T05:36:52Z-
dc.date.available2023-09-04T05:36:52Z-
dc.date.issued2023-
dc.identifier.urihttp://ir.juit.ac.in:8080/jspui/jspui/handle/123456789/9860-
dc.descriptionEnrolment No. 191362, 191366en_US
dc.description.abstractIn this project, we have developed a GUI that will assist farmers in selecting the most suitable crop for their land. Agriculture is the largest source of livelihood in India and approx. 70 percent of its rural households still depend primarily on agriculture for their livelihood. However, India still has many growing concerns, as the Indian economy has diversified and grown. Looking at the current situation faced by the farmers in India, we have observed that there have been many suicides in India over many years, the main reason behind this is the change in weather conditions and frequent changes in the Indian Government system. Sometimes farmers are not aware of the crop which suits their soil quality, soil nutrients, and soil composition. This project aims to help farmers to check the soil quality to get good crop yield. Any farmer is interested in knowing how much yield he is about to expect. The prediction using various ML models will help the farmers predict the crop yield before cultivating it on the agricultural field. ML is an essential approach for achieving the practical and essential solution to this problem. This system considers various parameters like soil moisture, soil pH value, rainfall, and temperature all at once. Based on all these parameters the system will predict the best crop for the farmer using the ML approach.en_US
dc.language.isoen_USen_US
dc.publisherJaypee University of Information Technology, Solan, H.P.en_US
dc.subjectCrop Recommendation Assistanten_US
dc.subjectWireless sensor networken_US
dc.subjectMachine learningen_US
dc.subjectAgricultureen_US
dc.titleCrop Recommendation System using WSN and ML Algorithmsen_US
dc.typeProject Reporten_US
Appears in Collections:B.Tech. Project Reports

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