A Prediction System for Farmers to Enhance the Agriculture Yield using Cognitive Data Science

Muthurasu N; M. Narayanan @ Ramanathan; Sahithyan S; Aravind M; Ramanagiri Bharathan A

doi:10.26483/ijarcs.v9i2.5784

PDF

Published: Apr 20, 2018

DOI: https://doi.org/10.26483/ijarcs.v9i2.5784

Keywords:

Agriculture yield, Regression models, Predictive Models, Tensor flow, Big Data, Weather forecasting, Data Analytics, Predictive Analytics, NLP, Chatbot

Muthurasu N

SRM Institute for Science and Technology Vadapalani, Chennai, India

M. Narayanan @ Ramanathan

SRM Institute for Science and Technology Vadapalani, Chennai, India

Sahithyan S

SRM Institute for Science and Technology Vadapalani, Chennai, India

Aravind M

SRM Institute for Science and Technology Vadapalani, Chennai, India

Ramanagiri Bharathan A

SRM Institute for Science and Technology Vadapalani, Chennai, India

Abstract

This paper gives an idea about how to discover additional insights from precision agriculture data through big data approach. Big data analytics in agriculture applications provide a new insight to give advance weather decisions, improve yield productivity and avoid unnecessary cost related to harvesting, use of pesticide and fertilizers. There are number of numerical weather models and algorithms that have been developed and enforced to predict the weather forecasting.

Downloads

Download data is not yet available.

Issue

Vol. 9 No. 2 (2018): March-April 2018

Section

Articles

COPYRIGHT

Submission of a manuscript implies: that the work described has not been published before, that it is not under consideration for publication elsewhere; that if and when the manuscript is accepted for publication, the authors agree to automatic transfer of the copyright to the publisher.

Authors who publish with this journal agree to the following terms:

Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work
The journal allows the author(s) to retain publishing rights without restrictions.
The journal allows the author(s) to hold the copyright without restrictions.

Author Biographies