Public Funding for P+HS Architects Limited

The design of healthcare facilities presents unique challenges, demanding precision in room layout, adherence to health standards, and efficient use of space. Traditional BIM tools, while useful, fall short in addressing the specific needs of healthcare architecture. Existing tools (Testfit, Sparkel, and Finch3D) offer generative design and rapid iterations but lack the tailored functionality for healthcare settings, particularly in automated room loading and detailed design protocols. The motivation behind this project is to enhance the efficiency and accuracy in healthcare building design, addressing the need for faster design delivery, precision, and reduction of manual, repetitive tasks. The project aims to develop an AI-based BIM tool integrated with Autodesk Revit, specifically designed for healthcare building design. It intends to automate the application of standardised layout requirements, uphold ergonomic and functional requirements across various room sizes and shapes, and significantly reduce human error and manual oversight. The project proposes a groundbreaking approach through three innovative levels: * **Creation of a machine-readable design protocol**: Utilising OWL ontologies, knowledge maps, and SPARQL, the project will develop a machine-readable design protocol. This protocol will integrate complex room loading rules and constraints, ensuring adherence to healthcare-specific design requirements. * **Development of AI models for optimal room loading**: This AI model will leverage 3D spatial BIM analysis and computer vision techniques to automate the process of determining the optimal parameters for room loading, thus streamlining the design process and reducing the potential for errors. * **Development of an intelligent BIM tool**: The tool will function as a design assistant, rule checker, decision support system, and report generator within the Autodesk Revit environment. It will utilise Revit SDK/API, design protocols, and spatial BIM analysis to automate the positioning of components, ensuring clash-free design. The project will result in a dynamic, adaptable design protocol specific to healthcare settings, and an AI-based BIM tool that streamlines healthcare building design, ensuring compliance, efficiency, and optimised spatial utilisation. This proposed BIM tool represents a significant leap in healthcare building design. The project would set new standards in the field by addressing existing gaps in BIM technology and incorporating advanced AI techniques. The project will not only facilitate more efficient and error-free design processes but also allow architects and designers to focus on innovative and creative aspects of healthcare architecture. This project has the potential to revolutionise how healthcare facilities are designed, leading to better outcomes in patient care, staff efficiency, and overall building functionality.

The unfortunate Grenfell fire disaster, where 72 lives were lost, has gone down as one of the UK's worst disaster of modern time. As a way of preventing future occurrence of such tragedy, one of the key recommendations of government's commissioned report (Hackett,2018) suggests the need for intelligent systems of regulation and enforcement to facilitate compliance with arrays of regulations and standards, including Approved Document B, HTM05-02, BS9999, BS9991 and BB100, among others. This is also reinforced by several studies (e.g. Noren et al.,2018; Sun,2020) which suggested integration of fire performance diagnostics with Building Information Modelling (BIM) as optimal approach for mitigating fire disasters. However, development in such areas is hindered, as regulations and standards are written in natural languages, only comprehensible by domain experts, and not usually for machines to process. This implies that compliance with vital safety standards is prone to error, subjectivity, corner-cutting, and additional time in correcting non-conformances identified through manual processes. Advances in the field of machine learning and analytics offers opportunities for automating building safety requirement compliance check, which the proposed project seeks to implement. The project aims to create an intelligent innovative system (FireBIM), as BIM-based solution, consisting of two key elements as follows: Platform 1--Design Diagnostics Platform for Fire Performance Compliance (BIMFire-Diagnostics): This platform evaluates building design for compliance with fire safety standards and regulation, including Approved Document B, HTM 05-02, BS 9999, BS 9991 and BB100, 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)Highlighting uncertified/unwarranted/uninsured areas, requiring detailing for approval. (iv)Suggesting improved and optimal design solutions. Platform 2--Materials and Components Decision Support for Fire Performance (BIMFire-DSS): Based on the requirements of building regulations and standards, up-to-date information from the industry and suppliers' information, this platform will provide decision supports for designers, contractors and building inspectors by: (i)Highlighting fire rating requirements for building elements. (ii)Digitising plethora of valid solutions for attaining compliance. (iii)Suggesting specific materials/detailing/specification for meeting performance standards. (iv)Flagging up materials/components/design solutions when unsafe for purpose. (v)Developing database of tested and certified materials/components. The project employs machine learning to train intelligent model that will identify and predict building regulations infringements/non-conformances in building designs. Text mining will be implemented to translate standards/regulation documents into machine-understandable formats, with automated reasoning and inference mechanism applied to the machine processable information for automated compliance diagnostics.