Article Per Year (5 Year)
p-Index From 2019 - 2024
0.23
P-Index
This Author published in this journals
All Journal International Journal of Integrated Science and Technology
Sakshi Shinde
ISSMS IOIT Pune
Computer Science & IT Decision Sciences, Operations Research & Management Education Languange, Linguistic, Communication & Media Social Sciences

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Modernizing Agriculture through ML and Deep Learning Anuja Phapale; Sakshi Shinde
International Journal of Integrated Science and Technology Vol. 1 No. 4 (2023): October 2023
Publisher : MultiTech Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59890/ijist.v1i4.683

Abstract

Farming is an essential part of a country's economy, providing livelihoods for many people. Traditionally, farmers used less precise methods, which reduced productivity and took a lot of time. Precision farming, on the other hand, improves productivity by accurately planning the farming process. It involves predicting weather conditions, analysing soil, recommending crops, and determining the right amount of fertilizers and pesticides to use. Precision farming uses advanced technologies like IoT, data mining, data analytics, and machine learning to gather data, train systems, and make predictions. This technology reduces manual labour and increases productivity. Farmers face various challenges, such as crop failures due to lack of rainfall and poor soil quality. Environmental changes make it important to find smart ways to manage crops and harvests. This research aims to help individuals farm more efficiently and achieve higher productivity at a lower cost. It also helps predict the total cost of cultivation, allowing people to plan their farming activities more effectively. In short, it provides an integrated solution for farming.
Co-Authors Anuja Phapale