Leveraging the Deployment of AI Technologies in Urban Green Infrastructure for Carbon Neutrality in Smart Buildings
スマートビルにおけるカーボンニュートラルのための都市緑地インフラへのAI技術の活用 (AI 翻訳)
Solomon Oisasoje Ayo-Odifiri, Andrew Ebekozien, Clinton Aigbavboa, Mohamed Hafez
🤖 gxceed AI 要約
日本語
本研究は、スマートビルにおけるカーボンニュートラル達成のために、AI技術を活用した都市緑地インフラ（UGI）の統合を探求する。ナイジェリアの3都市の30名のステークホルダーへのインタビューを通じ、AIがメンテナンス予測やエネルギー最適化に有効であること、また課題としてスキル不足や資金制約があることを明らかにした。技術受容モデル等の枠組みを用いて、AIを活用したグリーンデザインと炭素管理の実現可能性を示した。
English
This study explores the integration of AI technologies to enhance urban green infrastructure (UGI) for carbon neutrality in smart buildings. Through interviews with 30 stakeholders in three Nigerian cities, it finds that AI effectively predicts maintenance and optimizes energy, while challenges include skills gaps and financial constraints. Using frameworks like TAM, TOE, and Triple Helix, it offers insights for leveraging AI in green design and carbon management.
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
日本は2050年カーボンニュートラルを掲げ、スマートビルやグリーンインフラへのAI活用が注目される。本稿はナイジェリアの事例だが、AIとUGIの統合による省エネ・炭素削減の可能性は、日本の都市開発やSSBJに基づく開示にも示唆を与える。
In the global GX context
This paper adds a developing-country perspective to the global discourse on AI-enabled green infrastructure for carbon neutrality. While the qualitative evidence is context-specific, the identified barriers (skills, finance, regulation) and proposed initiatives (incentives, PPP) resonate with international efforts to scale AI for urban sustainability.
👥 読者別の含意
🔬研究者:Provides qualitative insights on AI-UGI integration and theoretical frameworks (TAM, TOE, THM) for future quantitative studies.
🏢実務担当者:Highlights AI applications for predictive maintenance and energy optimization in smart buildings, along with key implementation challenges.
🏛政策担当者:Recommends incentives, public-private collaborations, and inter-professional training to foster AI-enabled green design and carbon management.
📄 Abstract（原文）
Despite conventional approaches to incorporating green spaces into urban areas, carbon emissions persist, posing risks to the realisation of Sustainable Development Goals (SDGs) 11 and 13, which are linked to sustainable cities and climate action. This study explores the integration of Artificial Intelligence (AI) technologies to enhance urban green infrastructure (UGI) for carbon neutrality in smart buildings. A phenomenological qualitative research approach was adopted in this study. The purposively and snowball-sampled data from 30 stakeholders comprising architects, planners, engineers, and information and communication experts from Lagos, Abuja, and Kano via a Google Form questionnaire and virtual interview attained saturation at the 28th participant. The data extracted were manually analysed and thematically presented. The results revealed that AI predicts maintenance and optimises energy in smart buildings, and monitors UGI. While deficient skills, financial constraints, and poor regulations were identified as challenges, incentives, public-private collaborations, and inter-professional training were advocated as initiatives. To actualise AI-enabled green design and carbon management in smart buildings, the researchers adopted the Technology Acceptance Model (TAM), the Technology-Organisation-Environment (TOE) framework, and the Triple Helix Model (THM). The study offers insights for built environment experts and policymakers on how to leverage AI to harness UGI potential in smart buildings, mitigate the carbon footprint, and foster sustainable cities.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.20944/preprints202607.0091.v1first seen 2026-07-04 04:49:24
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