Automated fire risk assessment and mitigation in building blueprints using computer vision and deep generative models

Chen, Dayou; Chen, Long; Zhang, Yu; Lin, Shan; Ye, Mao; Sølvsten, Simon

doi:10.1016/j.aei.2024.102614

Advanced Engineering Informatics

2024

DOI: 10.1016/j.aei.2024.102614

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Automated fire risk assessment and mitigation in building blueprints using computer vision and deep generative models

Dayou Chen,

Long Chen,

Yu Zhang

et al.

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2024

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Cited by 5 publications

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The 30th international conference on intelligent computing in engineering (EG-ICE): Sustainable, smart and resilient buildings, infrastructures and cities

Lu,

Broyd,

2024

Advanced Engineering Informatics

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The 30th international conference on intelligent computing in engineering (EG-ICE): Sustainable, smart and resilient buildings, infrastructures and cities

Lu,

Broyd,

2024

Advanced Engineering Informatics

View full text Add to dashboard Cite

Automated construction site layout design system for prefabricated buildings using transformer based conditional GAN

Yang,

Chen,

2024

Advanced Engineering Informatics

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Adaptive information retrieval for enhanced building safety management leveraging BIM

Jiang,

Zhang,

Shi

et al. 2024

ECAM

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PurposeThis paper introduces a novel method to improve building safety management by leveraging building information modeling (BIM) and adaptive information retrieval techniques. The integration aims to overcome the limitations of traditional safety management methods in connecting construction processes with risk management efficiently.Design/methodology/approachThe proposed method involves developing industry foundation classes (IFC) ontologies and integrating them with a safety document ontology to form a comprehensive BIM-based safety context framework. Custom reasoning rules and an inference engine are constructed to enable automatic context-aware safety information retrieval. The methodology is demonstrated through an adaptive information retrieval system using job hazard analysis (JHA) documents.FindingsThe implementation of the BIM-based adaptive information retrieval system shows significant improvements in identifying and managing construction risks. By mapping job-specific risks to corresponding safety measures, the system enhances risk detection and management tailored to particular construction tasks. The results indicate a marked improvement in the precision and accuracy of safety assessments and recommendations, aligning them closely with planned construction activities and conditions.Originality/valueThis paper offers an innovative approach to construction safety management through the development of a BIM-facilitated context-aware information retrieval system. This approach provides a more intelligent and automated framework for identifying and managing risks in construction projects. By focusing on specific job steps and related risks, the system enhances the effectiveness and accuracy of safety measures, contributing to better overall building safety management.

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Automated fire risk assessment and mitigation in building blueprints using computer vision and deep generative models

Cited by 5 publications

References 54 publications

The 30th international conference on intelligent computing in engineering (EG-ICE): Sustainable, smart and resilient buildings, infrastructures and cities

The 30th international conference on intelligent computing in engineering (EG-ICE): Sustainable, smart and resilient buildings, infrastructures and cities

Automated construction site layout design system for prefabricated buildings using transformer based conditional GAN

Adaptive information retrieval for enhanced building safety management leveraging BIM

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