10081565AI-Enabled Rule Extraction System for BIM-based Fire Performance Diagnostic Platform (AI-FireBIM)ClosedCollaborative R&DInnovate UKThe review into the unfortunate Grenfell fire disaster uncovered sharp practices in building regulation regime, which is described as shocking in the 21st century United Kingdom. To tackle the challenges and ensure that everyone does the right thing and those who try to cut corner are held accountable. In line with this, Dame Judith Hackett led team suggested the needs for a new intelligent system of regulation and enforcement for high-rise and complex buildings. _Such system is expected to facilitate a high level of automation to evaluate and diagnose compliance with the array of fire safety legislation such as the_ Approved Document B, HTM 05-02, BS 9999, BS 9991 and BB100, some of which has gone through review processes since the aftermath of Grenfell fire enquiry. To support the move towards automated fire safety compliance diagnostic, our consortium has recently completed Fire-BIM project, which evaluates building design, identify areas of non-conformances, and suggest design changes for meeting fire safety requirements. The collaboration among Innovation Fire Engineering, P+HS Architects, Anglestack Limited, Leeds Beckett University, Farrans Construction PLC, CLM consultancy and University of Hertfordshire has led to the development of FireBIM platform as an automated portal for fire safety compliance diagnostic, which is currently being exploited by a spin out company. However, our FireBIM system is a rule-based design, involving manual extraction of fire safety rules that is coded into MongoDB as a NoSQL database. Thus, this feasibility study provides opportunity for automatically capturing building safety rule using Natural Language Processing (NLP) as a technique in Artificial Intelligence. The feasibility study will be used to determine the optimal approach for executing automated rule capturing and its implementation as a decision support system, covering text pre-processing, sentence segmentation, named entity recognition (in line with building components and elements), rule identification through pattern matching or rule-based parsing, rule extraction and entity capturing, rule classification and categorization, and rule quality assurance through comparison with existing manually extracted rule database. The result of the feasibility study would support in automating rule generation for our FireBIM diagnostics platform, thereby culminating in AI-FireBIM tool. This would evaluate building design for compliance with Approved Document B by (i)Automatically diagnosing proposed/as-built designs for compliance with provisions of targeted regulations/standards. (ii)Identifying areas of non-conformances with regulations and standards. (iii)Suggesting required design changes and fire safety standard requirements for different elements.