Low-Code Digital Twin Framework with Standards-Based IEQ Analytics: Generating Fabric-First Oriented Retrofit Decision-Making for Existing Buildings in Hot Arid Climate
ホットアリッド気候の既存建物向け、標準ベースIEQ分析を備えたローコードデジタルツインフレームワーク：ファブリックファースト指向のレトロフィット意思決定の生成 (AI 翻訳)
Basta G, ElGewely M, Mahmoud A
🤖 gxceed AI 要約
日本語
本研究は、既存建物の脱炭素化を促進するため、デジタルツインと室内環境品質（IEQ）のリアルタイム分析を組み合わせたローコードフレームワークを提案する。ASHRAE基準に基づくIEQ評価により、運用非効率を特定し、具体的なレトロフィット戦略（高性能ガラス、外部日除け、遮音など）を生成する。ホットアリッド気候のオフィススペースでのケーススタディにより有効性を実証した。
English
This paper proposes a low-code digital twin framework integrating real-time IEQ analytics to support retrofitting decisions for existing buildings, aiming to close the performance gap. Using ASHRAE standards, it identifies operational inefficiencies and generates specific retrofit interventions like high-performance glazing and shading. A case study in a hot arid climate office validates the approach.
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
日本の既存建物ストックの省エネ・脱炭素化においても、デジタルツインを用いたリアルタイムIEQ分析とレトロフィット連携は有効な手段となり得る。特にZEB化や省エネ基準強化が進む中、本フレームワークは運用データに基づく実効的な改修計画の立案に寄与する。
In the global GX context
This framework demonstrates a practical pathway for integrating digital twins with building performance monitoring to drive data-informed retrofit decisions, aligning with global efforts to decarbonize existing building stocks. Its standards-based IEQ analysis provides a replicable model for smart building management.
👥 読者別の含意
🔬研究者:Methodology for combining digital twins with real-time IEQ analytics and ASHRAE standards for retrofit planning.
🏢実務担当者:Actionable framework for building managers to leverage low-code digital twin platforms for targeted energy efficiency retrofits.
🏛政策担当者:Potential integration into building energy codes or retrofit subsidy programs to prioritize data-driven interventions.
📄 Abstract（原文）
Decarbonization of existing buildings is obstructed by the performance gap between intended and operational energy consumption. The Operational carbon footprint emitted through achieving stable indoor environmental quality and user comfort highlights a significant contribution to the performance gap that hinders decarbonization. Smart energy management and real time monitoring (digital twins) of existing buildings pose significant attributes towards decarbonization efforts. However, there is limited research transforming real time monitored performance of existing buildings to actionable retrofitting strategies. Most digital twins research focus on data visualization and building management, lacking design optimization and decision making frameworks that respond to the monitored performance. Therefore, this research bridges the digital twin concept with standards-based IEQ analytics for generating retrofit decision making in existing buildings. The framework offers a low code workflow that uses Autodesk Tandem to develop a digital twin integrating indoor environmental quality (IEQ) data, including thermal comfort, humidity, and air quality. In essence, IEQ is selected to be real time monitored, since inefficient management of these parameters often results in excessive HVAC demand, contributing significantly to the performance gap. The framework structure IEQ parameters continuous evaluation against performance benchmarks derived from ASHRAE standards to identify deviations indicative of operational inefficiencies. Unlike conventional retrofit planning based on periodic audits or predictive modelling, the proposed framework links live IEQ tracking and analysis, enabling efficient and effective retrofit interventions. Validating its effectiveness, the proposed workflow is tested through a case study on an office space in hot arid climate to generate retrofitting decisions. The case study tests the research proposition of combining low-code digital twin implementation with standards-based analytical logic to generate actionable retrofit guidance. The results indicates that the integration of digital twin–based IEQ analysis with building characteristics effectively identified the need for targeted envelope improvements, including high-performance glazing, external shading elements, and sound isolation as key factors for eliminating overheating and high noise levels.
🔗 Provenance — このレコードを発見したソース
- Research Square https://doi.org/10.20944/preprints202605.0060.v1first seen 2026-05-14 21:18:16
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