Artificial intelligence and internet of things oriented sustainable precision farming: Towards modern agriculture

Author:

Sharma Amit12,Sharma Ashutosh23,Tselykh Alexey1,Bozhenyuk Alexander1,Choudhury Tanupriya4,Alomar Madani Abdu5,Sánchez-Chero Manuel6

Affiliation:

1. Institute of Computer Technologies and Information Security, Southern Federal University , Taganrog , 347922 , Russia

2. Chitkara University Institute of Engineering and Technology, Chitkara University , Punjab , India

3. School of Computer Science, University of Petroleum and Energy Studies , Dehradun , India

4. Symbiosis Institute of Technology, Symbiosis International University , Pune , Maharashtra, 412115 , India

5. Department of Industrial Engineering, Faculty of Engineering – Rabigh, King Abdulaziz University , Jeddah 21589 , Saudi Arabia

6. Universidad Nacional de Frontera, Sullana, Perú, Facultad de Ingeniería de Industrias Alimentarias y Biotecnología , Sullana , Peru

Abstract

Abstract Agriculture encompasses the study, practice, and discipline of plant cultivation. Agriculture has an extensive history dating back thousands of years. Depending on climate and terrain, it began independently in various locations on the planet. In comparison to what could be sustained by foraging and gathering, agriculture has the potential to significantly increase the human population. Throughout the twenty-first century, precision farming (PF) has increased the agricultural output. precision agriculture (PA) is a technology-enabled method of agriculture that assesses, monitors, and evaluates the needs of specific fields and commodities. The primary objective of this farming method, as opposed to conventional farming, is to increase crop yields and profitability through the precise application of inputs. This work describes in depth the development and function of artificial intelligence (AI) and the internet of things (IoT) in contemporary agriculture. Modern day-to-day applications rely extensively on AI and the IoT. Modern agriculture leverages AI and IoT for technological advancement. This improves the accuracy and profitability of modern agriculture. The use of AI and IoT in modern smart precision agricultural applications is highlighted in this work and the method proposed incorporates specific steps in PF and demonstrates superior performance compared to existing classification methods. It achieves a remarkable accuracy of 98.65%, precision of 98.32%, and recall rate of 97.65% while retaining competitive execution time of 0.23 s, when analysing PF using the FAOSTAT benchmark dataset. Additionally, crucial equipment and methods used in PF are described and the vital advantages and real-time tools utilised in PA are covered in detail.

Publisher

Walter de Gruyter GmbH

Subject

General Agricultural and Biological Sciences,General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,General Neuroscience

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