CIM-Enabled Quantitative View Assessment In Architectural Design And Space Planning
Authors: Vikrom Laovisutthichai
Journal: 38th International Symposium on Automation and Robotics in Construction Dubai, UAE.
Publication Date: Nov 2021.
Keywords: Architectural Design Generative Design Space Planning View Assessment City Information Model Deep Learning
Abstract
A View Is Among The Critical Criteria In An Architectural Design Process. Presently, It Is Assessed By Conventional Site Observation, Labour-Intensive Data Collection, And Manual Data Analysis Before Designing A Building Mass, Plan, Façade, Openings, And Interior Space. City Information Model (CIM), With Its Capabilities To Store, Visualize, And Analyze A Wealth Of Site-Related Information, Has A Great Potential To Support An Automated View Assessment. However, Its Realization Is Nascent, And It Has Not Integrated With Architectural Space Planning In Either Research Or Practice. This Research, Therefore, Aims To Develop A Model Through Which CIM Can Be Extended To Assist View Assessment In Architectural Space Planning. By Literature Review, Brainstorming, Prototyping, And Case Study, This Research Corroborates That By Harnessing The Power Of CIM, The Conventional View Evaluation Can Be Transformed From Qualitative To Mix-Used. It Helps Practitioners Assess A View And Design A Space In A More Precise And Rapid Manner. This Research Also Provides The Integrated Model For View Evaluation In Architectural Space Planning With Three Stages To Support The Real-World Practice. Future Studies Are Recommended To Develop The Proposed Model And Integrate It With Multiple Criteria To Advance The Generative Design.
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