Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/372857
Title: Development of model for crop leaf fault detection using internet of things
Researcher: Shukla, A
Guide(s): Miri, R
Keywords: Computer Science
Computer Science Software Engineering
Engineering and Technology
University: Dr. C.V. Raman University
Completed Date: 2021
Abstract: Agriculture sector plays a major role in the Indian economy; there are a large number of farmers in India who are putting in the hard work, and those farmers are the pillars for the Indian economy. However, there are numerous problems that Indian farmers must deal with, including rainfall, crop failure and leaf disease. These issues are wreaking havoc on their cultivating practices.These problems have had a negative impact on their ability to cultivate. In India, there are different kinds of farmers who are still not embracing innovation and are growing their crops in the conventional way. newlineBeyond farming, backwoods are subjected to contamination difficulties, which create a cascade of problems across the forest, and as a result, the animals that consume those plants get affected with a range of diseases.In these conditions, it is possible that early disease identification might have been helpful. Because of their medicinal qualities, leaves from a wide range of plants and flavours are helpful to mankind as a whole. Developing Countries, where a significant part of the population is dependent on agriculture for work, offer benefits and food security to the rest of the world. Furthermore, disease-related incidents can have a significant financial effect, resulting in a decrease in remuneration for crop creators, among other things.
Pagination: 
URI: http://hdl.handle.net/10603/372857
Appears in Departments:Department of Computer Science & Engineering

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11. chapter-2.pdf141.63 kBAdobe PDFView/Open
12. chapter-3.pdf1.11 MBAdobe PDFView/Open
13. chapter-4.pdf1.45 MBAdobe PDFView/Open
14. chapter-5.pdf9.03 kBAdobe PDFView/Open
1. title.pdf15.06 kBAdobe PDFView/Open
2. certificate.pdf89.43 kBAdobe PDFView/Open
5. references.pdf36.23 kBAdobe PDFView/Open
6. table of content.pdf129.33 kBAdobe PDFView/Open
80_recommendation.pdf20.5 kBAdobe PDFView/Open
8. list of table.pdf179.19 kBAdobe PDFView/Open
9. list of figure.pdf183.98 kBAdobe PDFView/Open
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