A Data-Driven Framework for Infrastructure Resilience Assessment Using the B-R-I-P Model

In recent years, the assessment and mitigation of risks related to building preservation have become increasingly important. This study proposes a Building-Risk-ImportancePreservation (B-R-I-P) evaluation model to address challenges in building preservation. The model considers internal factors such as building stability, damage extent, and historical and economic value, as well as external factors like community budget and potential hazards, providing a quantitative assessment framework for developing effective building protection measures. By analyzing various regions, the study identifies high-risk areas and employs data visualization techniques to illustrate the relative importance of different preservation factors. These findings are essential for guiding policymakers and community leaders in strategy formulation and resource allocation to enhance building resilience and safety.

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Publication Details

Published
2024-12-29
DOI
https://doi.org/10.1109/icirdc65564.2024.00090
Primary Topic
Infrastructure Resilience and Vulnerability Analysis
Type
article
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article

A Data-Driven Framework for Infrastructure Resilience Assessment Using the B-R-I-P Model

Jie Wu, Zhicheng Ji
Infrastructure Resilience and Vulnerability Analysis
article

A Data-Driven Framework for Infrastructure Resilience Assessment Using the B-R-I-P Model

Jie Wu, Zhicheng Ji
article en

Abstract

In recent years, the assessment and mitigation of risks related to building preservation have become increasingly important. This study proposes a Building-Risk-ImportancePreservation (B-R-I-P) evaluation model to address challenges in building preservation. The model considers internal factors such as building stability, damage extent, and historical and economic value, as well as external factors like community budget and potential hazards, providing a quantitative assessment framework for developing effective building protection measures. By analyzing various regions, the study identifies high-risk areas and employs data visualization techniques to illustrate the relative importance of different preservation factors. These findings are essential for guiding policymakers and community leaders in strategy formulation and resource allocation to enhance building resilience and safety.

Jiangnan University (CN)
Openalex Percentile: Top 66%
Infrastructure Resilience and Vulnerability Analysis
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A Data-Driven Framework for Infrastructure Resilience Assessment Using the B-R-I-P Model — Jie Wu, Zhicheng Ji · (2024) | TGRS Research Map | TGRS