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INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016 open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15 |
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| Paper Title: | Digital Farming Using Data Analysis |
| Authors Name: | Mr. Avinash S Kangane , Mr.Rohan S Kapse , Mr.Samarthanand D Kamble , Mr. Sachin S Ghugare , Prof. M.T.Jagtap. Prof. S.G.Chordiya |
| Unique Id: | IJSDR2204021 |
| Published In: | Volume 7 Issue 4, April-2022 |
| Abstract: | Digital farming can be defined as the use of technology by farmers to integrate financial and field level records for complete farm activity management. Digital farming is applying precision location methods and decision quality agronomic information to illuminate, predict, and affect the continuum of cultivation issues across the farm. The main focus of our project is inclined towards the minimal utilization of time and maximum output. The moto is to introduce farmers to show how traditional things can be done in digitalized ways within fraction of seconds, about 88livelihood. Most of this population comprises small holders, and poverty is widespread. The Agriculture Perspective Plan (APP) formulated in 1995 considers agricultural growth as the key to poverty reduction. The APP stressed the need to diversify agricultural production on the basis of geographical location and commercialization of agro-products. The Ninth Five-Year Plan (1996-2001) also saw the start of the 20-year APP and drew upon its strategies. The 1990s also saw changes in government policy, with reforms moving the economy towards a more market-oriented system. The second major change that has affected the agricultural system over the past decade is the move towards decentralization, with the Self-Governance Act 1999, providing for greater devolution of power to the local government. An increased emphasis on participation and on partnerships between the public sector and other service providers has been embodied in the formulation of recent projects in the agriculture sector. As a result of the impetus given by the APP and these policy changes, growth in the agriculture sector has accelerated during the 1990s, although it is still short of the APP target of 2growth per capita. |
| Keywords: | React Js , Python , Detection , Machine Learning system |
| Cite Article: | "Digital Farming Using Data Analysis", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.7, Issue 4, page no.119 - 122, April-2022, Available :http://www.ijsdr.org/papers/IJSDR2204021.pdf |
| Downloads: | 000337064 |
| Publication Details: | Published Paper ID: IJSDR2204021 Registration ID:200234 Published In: Volume 7 Issue 4, April-2022 DOI (Digital Object Identifier): Page No: 119 - 122 Publisher: IJSDR | www.ijsdr.org ISSN Number: 2455-2631 |
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