ARTIFICIAL INTELLIGENCE FOR ENVIRONMENTAL SUSTAINABILITY: APPLICATIONS AND IMPACTS
環境持続可能性のための人工知能：応用と影響 (AI 翻訳)
Sevara Umarjonova
🤖 gxceed AI 要約
日本語
本論文は、環境持続可能性の達成におけるAIの応用可能性と影響を探る。資源最適化、汚染制御、気候変動緩和に焦点を当て、再生可能エネルギー、スマート農業、廃棄物管理、環境モニタリングにおけるAI活用事例をレビュー。予測分析によるエネルギー効率向上や精密農業、気候モデリング、政策設計への貢献を評価する一方、実施コストやデータプライバシー、AIインフラ自体の環境負荷といった課題も指摘する。
English
This paper explores the applications and implications of AI for achieving environmental sustainability, focusing on resource optimization, pollution control, and climate change mitigation. It reviews AI applications in renewable energy, smart agriculture, waste management, and environmental monitoring through a qualitative literature review. It highlights AI's potential to improve energy efficiency via predictive analytics, enable precision agriculture, enhance climate modeling and risk assessment, while also identifying challenges such as high implementation costs, data privacy concerns, and environmental impacts of AI infrastructure.
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、2050年カーボンニュートラル達成に向けてAIの活用が期待される分野として、再生可能エネルギーの需給予測やスマート農業、環境モニタリングが挙げられる。本レビューは、これらの分野におけるAI導入の可能性と障壁を俯瞰的に整理しており、政策立案や企業の技術導入判断の参考になる。
In the global GX context
Globally, AI is increasingly seen as a key enabler for climate action and sustainability. This review provides a broad overview of AI applications across multiple environmental domains, which is valuable for understanding the current landscape and challenges. It can inform international discussions on leveraging AI for net-zero transitions and for managing trade-offs such as data privacy and infrastructure footprint.
👥 読者別の含意
🔬研究者:Provides a structured overview of AI for sustainability applications, useful for identifying research gaps and cross-domain synergies.
🏢実務担当者:Highlights concrete AI use cases in energy, agriculture, and waste management that could be piloted for operational efficiency.
🏛政策担当者:Summarizes opportunities and challenges of AI for environmental governance, aiding in policy design and infrastructure planning.
📄 Abstract（原文）
Artificial Intelligence (AI) has been emerging as a powerful tool for solving some of the pressing environmental challenges and for sustainable development․ This paper aims at exploring the potential applications and implications of AI for achieving environmental sustainability specifically focusing on resource optimization‚ pollution control and climate change mitigation․ A key priority is to study and evaluate the application of AI-enabled technologies in effective environmental governance and decision-making․ A qualitative research approach and a research method of analysis are adopted in this research‚ and a thorough literature review was conducted on research papers‚ industry reports‚ and case studies that deal with the applications of AI-enabled solutions in renewable energy systems‚ smart agriculture‚ waste management‚ and environmental monitoring․ Secondary data‚ including academic literature‚ industry publications‚ and government documents‚ are analyzed to provide evidence of the impact and limits of AI․ Additional contributions are areas in which AI can improve the efficiency of energy consumption (predictive analytics)‚ precision agriculture (water and fertilizer optimization)‚ environmental monitoring (pollution monitoring such as air and water quality)‚ better climate modeling‚ and risk assessment and environmental policy design․ It also identifies challenges such as high implementation costs‚ concerns about data privacy‚ and the environmental effects of the AI infrastructure itself․
🔗 Provenance — このレコードを発見したソース
- Zenodo https://zenodo.org/records/21470234first seen 2026-07-22 04:15:05
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gxceed は公開メタデータに基づく研究支援データセットです。要約・翻訳・解説は AI 支援で生成されています。 最終的な解釈・検証は利用者が原典資料に基づいて行うことを前提とします。