Revolutionizing Precision Agriculture Using Artificial Intelligence and Machine Learning

Author:

Murugan Jayalakshmi1,Kaliyanandi Maharajan1,Sobia M. Carmel2

Affiliation:

1. Department of Computer Science and Engineering, School of Computing, Kalasalingam Academy of Research and Education, Krishnankoil, Tamilnadu, India

2. Department of Electrical and Electronics Engineering, PSR Engineering College, Sivakasi, Tamilnadu, India

Abstract

Plant disease mechanization in the agricultural discipline is a major source of concern for every country, since the world's population continues to grow at an alarming rate, increasing the need for food. However, due to a scarcity of necessary infrastructure in various parts of the world, it is difficult to identify them quickly in some areas. In the context of the expanded use of technology, it is now feasible to assess the efficiency and accuracy of methods for identifying illnesses in plants and animals. It has recently been discovered that information technology-based tools, technologies, and applications are effective and realistic measures for the improvement of the whole agricultural field, spanning from scientific research to farmer assistance. The integration of expert systems as a strong tool for stakeholders in agricultural production has enormous promise, and it is now being explored. The suggested effort begins with the collection of disease symptoms and environmental factors by agriculture specialists and plant pathologists, who will then analyze the information gathered. The corrective solution is then recommended to the end user by an expert system, which is accessed through a mobile application. Computer application consisting of an expertise base, inference engine, and a user interface is envisaged as the machine of the future. Integrated inside the gadget is a structured expertise base that contains information on the signs and treatments of various ailments. In order to identify and diagnose plant disorders, the machine must first locate and diagnose the condition. It is accomplished by the analysis of the symptoms of illness on the crop's surface. On the basis of the yield and the surrounding environment, this symptom is utilized to identify the illness and give an entirely unique diagnostic solution. The computer will test the plants and their disordered lives inside the database and provide a set of diagnostic levels in accordance with the condition that the plants are suffering from, according to the database. Farmers may easily identify and manipulate plant diseases with the help of the suggested technology, which is supported by a sophisticated expert system.

Publisher

BENTHAM SCIENCE PUBLISHERS

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3