SWARM INTELLIGENCE EMBEDDED DATA MINING FOR PRECISION AGRICULTURE ADVANCEMENTS
Abstract
The present study investigates the potential of Swarm Intelligence (SI) in driving breakthroughs in Precision Agriculture (PA). It focuses on the research of mining techniques to uncover novel insights and developments in the field of PA. Social informatics (SI) is an academic discipline that focuses on the examination of collective behaviour within both herbal and synthetic structures. In order to gather, analyse, and synthesise information, SI utilises self-sufficient mobile devices known as Autonomous Mobile Agents (AMAs). These entities refer to robotic and computational frameworks that engage in mutual interaction, facilitating the examination of collective intelligence. This essay examines the potential impact of utilising the System of International Units (SI) on enhancing the accuracy and precision of commodity production and control in the field of production agriculture (PA). It also highlights the existing advancements that have been achieved in this regard. This analysis examines possible uses of Swarm Intelligence in the Public Administration (PA) industry, as well as the challenges that need to be solved in order to enhance the efficiency and accuracy of PA operations.

Authors
N. Karthik1, Sanjay R. Pawar2, R. Pramodhini3, Arvind Kumar Shukla4
Sri Krishna Arts and Science College, India1,2,3, IFTM University, India4

Keywords
Swarm Intelligence, Embedded Data Mining, Precision Agriculture, Machine Learning, Artificial Intelligence, Crop Yield
Yearly Full Views
JanuaryFebruaryMarchAprilMayJuneJulyAugustSeptemberOctoberNovemberDecember
111051005120730
Published By :
ICTACT
Published In :
ICTACT Journal on Soft Computing
( Volume: 14 , Issue: 2 , Pages: 3218 - 3223 )
Date of Publication :
October 2023
Page Views :
977
Full Text Views :
220

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.