AI-Enabled Climate-Resilient Smart Agriculture for Sustainable Food Systems
持続可能な食料システムのためのAI対応気候レジリエントなスマート農業 (AI 翻訳)
Samruddhi Pandit, Anuja Mukherjee, Rugved Dani, Abhishek Solanke
🤖 gxceed AI 要約
日本語
本論文は、気候変動に脅かされる農業生産性と食料安全保障に対し、AI技術を活用した5層のスマート農業フレームワークを提案。気候データ、センシング、予測分析、意思決定支援、持続可能性評価を統合し、精密農業やスマート灌漑などの応用事例を紹介。導入障壁と政策課題も議論。
English
This paper proposes a five-layer AI-enabled smart agriculture framework for climate-resilient and sustainable food systems. It integrates climate inputs, sensing, predictive analytics, decision support, and sustainability outcomes. Case studies cover precision farming, smart irrigation, and yield prediction, while addressing implementation barriers like infrastructure and data governance.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
日本では、農業従事者の高齢化や気候変動適応が課題。本フレームワークは、スマート農業技術と気候データ統合の方向性を示し、日本の農業DX・GX政策（みどりの食料システム戦略など）に示唆を与える。
In the global GX context
Globally, climate change threatens food security, and AI offers scalable solutions. This framework aligns with FAO and UNFCCC goals, supporting climate adaptation and mitigation in agriculture. It provides a structured approach for integrating AI into agricultural decision-making, relevant for ISSB and TCFD reporting on supply-chain resilience.
👥 読者別の含意
🔬研究者:Researchers can adopt the five-layer framework as a conceptual model for AI-driven climate resilience studies in agriculture.
🏢実務担当者:Practitioners in agri-tech can use the case studies and framework to design AI-based decision support systems for farms.
🏛政策担当者:Policymakers should consider infrastructure, data governance, and digital inclusion policies highlighted in the chapter.
📄 Abstract（原文）
Climate change is increasingly threatening agricultural productivity, food security, and sustainability of global food systems. Artificial intelligence (AI) and digital agriculture technologies offer new opportunities to enhance climate resilience and optimize resource use. This chapter proposes a five layer AI enabled smart agriculture framework integrating climate inputs, sensing infrastructure, predictive analytics, decision support, and sustainability outcomes. The framework supports climate adaptation, greenhouse gas mitigation, and long term food system resilience. Key AI applications including precision farming, smart irrigation, soil health monitoring, pest forecasting, and yield prediction are examined. Case studies highlight implementation challenges such as infrastructure limitations, data governance, and digital inequality. Policy and governance strategies are discussed to support inclusive adoption. The chapter contributes a structured framework for AI driven climate resilient agriculture supporting sustainable food systems and climate action.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.4018/979-8-3373-9978-2.ch002first seen 2026-06-08 04:36:26
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