Advancing Agriculture through Artificial Intelligence: A Framework for Sustainable Crop Production and Equitable Food Security

Artificial Intelligence (AI) is revolutionizing agriculture by enabling data-driven, sustainable, and equitable farming practices. This review synthesizes AI applications—machine learning, computer vision, robotics, and IoT integration—to enhance crop productivity, resource efficiency, and climate resilience. We propose a novel Inclusive AI-Agriculture Framework (IAAF) that integrates AI with traditional knowledge and equitable access to address global food security. The review critically evaluates AI’s role in yield prediction, soil management, pest detection, and supply chain optimization, with a focus on India, particularly Punjab and Haryana. Barriers, including high costs, digital literacy gaps, and ethical concerns (e.g., data privacy, rural employment), are analyzed, alongside strategies like policy incentives and public-private partnerships. Global and regional adoption trends are presented, supported by a systematic literature review of 60 studies from 2018–2023. Future directions emphasize localized, climate-smart, and ethically grounded AI solutions. This paper underscores AI’s transformative potential to create resilient, inclusive agricultural systems.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-08-07
DOI
https://doi.org/10.5281/zenodo.16759875
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
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article

Advancing Agriculture through Artificial Intelligence: A Framework for Sustainable Crop Production and Equitable Food Security

Zenodo (CERN European Organization for Nuclear Research)
Smart Agriculture and AI
article

Advancing Agriculture through Artificial Intelligence: A Framework for Sustainable Crop Production and Equitable Food Security

article en

Abstract

Artificial Intelligence (AI) is revolutionizing agriculture by enabling data-driven, sustainable, and equitable farming practices. This review synthesizes AI applications—machine learning, computer vision, robotics, and IoT integration—to enhance crop productivity, resource efficiency, and climate resilience. We propose a novel Inclusive AI-Agriculture Framework (IAAF) that integrates AI with traditional knowledge and equitable access to address global food security. The review critically evaluates AI’s role in yield prediction, soil management, pest detection, and supply chain optimization, with a focus on India, particularly Punjab and Haryana. Barriers, including high costs, digital literacy gaps, and ethical concerns (e.g., data privacy, rural employment), are analyzed, alongside strategies like policy incentives and public-private partnerships. Global and regional adoption trends are presented, supported by a systematic literature review of 60 studies from 2018–2023. Future directions emphasize localized, climate-smart, and ethically grounded AI solutions. This paper underscores AI’s transformative potential to create resilient, inclusive agricultural systems.

Zenodo (CERN European Organization for Nuclear Research)
Zero hunger
Openalex Percentile: Top 68%
Smart Agriculture and AI
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