Agentic AI for Climate-Resilient Cities: A PRISMA-Guided Review and Digital Twin Framework
Toqeer Ali Syed, Ali Akarma, Muhammad Tayyab Naqash, Danial Hameed, Shahid Kamal (23807824), Antonio Formisano
🤖 gxceed AI 要約
日本語
本論文は、気候変動に強い都市を実現するためのエージェント型AI（AAI）の役割をPRISMAガイドラインに従ってレビュー。自律的意思決定やマルチエージェント協調などの特徴を持つAAIが、スマートモビリティ、エネルギー予測、防災など様々な分野で応用されている一方、統合的なフレームワークが不足していると指摘。そこで、デジタルツインとAAIを融合した新たなアーキテクチャを提案し、持続可能性目標の最適化にPareto手法を導入している。
English
This paper presents a PRISMA-guided review of Agentic AI (AAI) for urban climate resilience, synthesizing 70 studies on smart mobility, energy forecasting, disaster response, etc. It proposes a unified AAI-Digital Twin framework with Pareto optimization to balance competing sustainability goals, highlighting challenges in interoperability, data governance, and scalability.
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
本論文は、日本の都市が気候変動適応策を強化する際に、AIとデジタルツインの活用方法を示唆する。特に、自治体の防災・エネルギー管理システムへの応用が期待されるが、現時点では実装例ではなく概念的な枠組みである点に注意。
In the global GX context
This paper contributes globally by bridging agentic AI and digital twin technologies for climate-resilient urban planning. It offers a structured review and a novel framework that can inform smart city initiatives under climate stress, though it remains conceptual and lacks empirical validation.
👥 読者別の含意
🔬研究者:The paper provides a comprehensive review of agentic AI applications in urban climate resilience and a proposed framework for integrating digital twins, offering a research roadmap for future work.
🏢実務担当者:Urban planners and sustainability teams can use the framework as a conceptual guide for designing AI-driven climate adaptation systems, but should note the need for pilot testing.
🏛政策担当者:Policymakers can reference the identified challenges (interoperability, data governance) when drafting regulations for AI in urban climate resilience.
📄 Abstract（原文）
Rapid urbanization and intensifying climate risks are placing unprecedented pressure on cities to transition toward sustainable and resilient models. Achieving Sustainable Development Goals (SDGs) 11 (Sustainable Cities and Communities) and 13 (Climate Action) requires intelligent systems capable of interpreting complex urban dynamics and enabling proactive, adaptive decision-making. This paper presents a PRISMA-guided rapid review examining the role of Agentic Artificial Intelligence (AAI)–autonomous, goal-directed systems with multi-step reasoning, tool use, and multi-agent coordination–in advancing urban sustainability and climate resilience. Studies were required to exhibit at least two attributes: autonomous decision-making, multi-step planning, tool use or environmental interaction, and multi-agent coordination. From 920 records, 70 peer-reviewed studies were synthesized, covering smart mobility, infrastructure planning, waste management, emergency response, climate monitoring, emissions tracking, renewable energy forecasting, and multi-hazard early warning systems. Results show that despite rapid progress, AAI applications remain fragmented and domain-specific. To address this, a unified Agentic AI–Digital Twin framework is proposed, integrating real-time sensing, urban–climate co-simulation, multi-agent coordination, and adaptive decision intelligence. A Pareto-based optimization approach balances competing sustainability goals. Key challenges in interoperability, data governance, ethics, and scalability are identified, alongside a research roadmap for integrated intelligent urban ecosystems.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.20944/preprints202604.1837.v1first seen 2026-05-21 04:30:26
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