HARNESSING ARTIFICIAL INTELLIGENCE IN AGRICULTURE: IN-DEPTH CASE STUDIES AND STRATEGIC INSIGHTS

Agriculture, which employs over 25% of the global workforce and feeds a growing population, faces increasing challenges due to climate change, resource constraints, and declining productivity. In response, Artificial Intelligence (AI) has emerged as a powerful tool to modernize farming practices, offering data-driven solutions for more efficient and sustainable agriculture. This paper explores the application of AI in agriculture through five real-world case studies from India, Israel, the United States, Japan, and the Netherlands. These studies demonstrate how technologies like machine learning, computer vision, drones, and IoT are being used for pest detection, precision irrigation, yield prediction, crop monitoring, and livestock health management. The paper highlights key outcomes, identifies common challenges, and offers recommendations to enhance AI adoption and impact in global agriculture

Authors

Institutions

Publication Details

Journal
International Journal of Advanced Research in Computer Science
Published
2025-08-20
DOI
https://doi.org/10.26483/ijarcs.v16i4.7300
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

HARNESSING ARTIFICIAL INTELLIGENCE IN AGRICULTURE: IN-DEPTH CASE STUDIES AND STRATEGIC INSIGHTS

Rahul Hooda
International Journal of Advanced Research in Computer Science
Big Data and Business Intelligence
article

HARNESSING ARTIFICIAL INTELLIGENCE IN AGRICULTURE: IN-DEPTH CASE STUDIES AND STRATEGIC INSIGHTS

Rahul Hooda
article en

Abstract

Agriculture, which employs over 25% of the global workforce and feeds a growing population, faces increasing challenges due to climate change, resource constraints, and declining productivity. In response, Artificial Intelligence (AI) has emerged as a powerful tool to modernize farming practices, offering data-driven solutions for more efficient and sustainable agriculture. This paper explores the application of AI in agriculture through five real-world case studies from India, Israel, the United States, Japan, and the Netherlands. These studies demonstrate how technologies like machine learning, computer vision, drones, and IoT are being used for pest detection, precision irrigation, yield prediction, crop monitoring, and livestock health management. The paper highlights key outcomes, identifies common challenges, and offers recommendations to enhance AI adoption and impact in global agriculture

International Journal of Advanced Research in Computer ScienceVol. 16(4)
Alwar Pharmacy College (IN)
Openalex Percentile: Top 63%
Big Data and Business Intelligence
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

HARNESSING ARTIFICIAL INTELLIGENCE IN AGRICULTURE: IN-DEPTH CASE STUDIES AND STRATEGIC INSIGHTS — Rahul Hooda · International Journal of Advanced Research in Computer Science (2025) | TGRS Research Map | TGRS