ICTACT Journal on Soft Computing

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Swarm Intelligence Embedded Data Mining for Precision Agriculture Advancements


Affiliations
1 Department of Information Technology and Cognitive Systems, Sri Krishna Arts and Science College, India
2 Department of Mechanical Engineering, Bharati Vidyapeeth College of Engineering, India
3 Department of Electronics and Communication, Nitte Meenakshi Institute of Technology, India
4 Department of Computer Applications, IFTM University, India
     

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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.

Keywords

Swarm Intelligence, Embedded Data Mining, Precision Agriculture, Machine Learning, Artificial Intelligence, Crop Yield.
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Abstract Views: 145

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  • Swarm Intelligence Embedded Data Mining for Precision Agriculture Advancements

Abstract Views: 145  |  PDF Views: 1

Authors

N. Karthik
Department of Information Technology and Cognitive Systems, Sri Krishna Arts and Science College, India
Sanjay R. Pawar
Department of Mechanical Engineering, Bharati Vidyapeeth College of Engineering, India
R. Pramodhini
Department of Electronics and Communication, Nitte Meenakshi Institute of Technology, India
Arvind Kumar Shukla
Department of Computer Applications, IFTM University, India

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.

Keywords


Swarm Intelligence, Embedded Data Mining, Precision Agriculture, Machine Learning, Artificial Intelligence, Crop Yield.

References