CROP YIELD PREDICTION USING MACHINE LEARNING AND CLOUD COMPUTING


Disha A
Student , Jain university
Abstract
Agriculture is the field which assumes a signif-icant part in improving our nations economy. India is an agrarian country and its economy is generally founded on crop efficiency. Choos-ing of each yield is vital in the farming arrang-ing. The determination of yields will rely on the various boundaries, for example, market value, creation rate and the distinctive government approaches. Numerous progressions are needed in the farming field to improve changes in our Indian economy. We can improve crop yield by utilizing AI procedures which are applied effectively on cultivating area. Stretching out web based business to the culti-vating local area is a significant advance in the computerized change of India. For Mr. Gupta, it addresses the democratization of internet business. Today, ranchers have the choice to purchase online as opposed to going through hours making a trip to and from actual retail locations. "We are digitizing agribusiness in India with AWS—engaging ranchers with in-ternet business availability. Likewise, by ex-hibiting recordings on successful harvest culti-vating, ranchers have had the option to build their yield yields by in excess of 25%," Mr. Gupta says. With the site running on the AWS Cloud, im-provement time is a lot more limited. Mr. Gup-ta remarks, "With AWS, our IT activities productivity has improved by at any rate 80% while creating cost investment funds of in ex-cess of 50%, on the grounds that we can choose, convey, and oversee AWS assets ef-fortlessly. There is no acquirement cycle or need to devote capital spending plans to pro-jects. Our month to month AWS charging is not even close to the expense of power for an on-premises climate of a comparative size.”
Keywords: Indian Agriculture, Machine Learning Techniques, Crop selection method.
Journal Name :
EPRA International Journal of Research & Development (IJRD)

VIEW PDF
Published on : 2021-05-04

Vol : 6
Issue : 5
Month : May
Year : 2021
Copyright © 2024 EPRA JOURNALS. All rights reserved
Developed by Peace Soft