Study on Collision Detection Techniques for the Informed Design of Natural Views in Healthcare Environments. (July 2022)

• Record Type: Journal Article
• Authors: Ban, Qichao; Lyu, Min; Gao, Weijun; Chen, Yulin; Yao, Jiawei
• Is Part Of: HERD. Volume 15:Number 3(2022)
• Page Start: 229
• Page End: 245
• Publication Date: 2022-07
• Subjects: natural view -- healthcare environment -- Building Information Modeling -- collision detection technique -- social sustainability; Health facilities -- Design and construction -- Periodicals; Medical care -- Periodicals; Health facilities -- Design and construction; Medical care; Periodicals; 725.5
• DOI: 10.1177/19375867221084220
• Languages: English
• ISSNs: 1937-5867

Abstract

Background: Natural views are an important design strategy for the application of ecological resources in built environments. Numerous clinical studies have indicated that views of nature—for example, plants—can effectively promote patient recovery by relieving their postoperative pains and negative emotions during hospitalization. Aims: This study demonstrates an intelligent method that develops algorithms of using collision detection techniques in Building Information Modeling to evaluate outdoor plant visibility for patients. Methods: These algorithms are digitized into a Revit plug-in program, which can be viewed as a design-aided tool for architects with the purpose of informing healthcare environment design in the decision-making process. Results: Its acceptability and effectiveness are evaluated based on the consultations in beta tests. Conclusions: It is believed that this method can improve the work efficiency of evaluating natural views in wards and help architects implement an informed design of built environments for better health performance. All findings in this study can contribute to the development of computational intelligence and social sustainability in the near future.