Abstract
Urban planning practice and architectural design increasingly adopt agent-based models and simulations to support decision-making for spatial design. Nonetheless, although essential, a reliable representation of human spatial behaviour in a socially rich context is still challenging. The study presents a framework built on a Dynamic Network Visualization of space use patterns based on a Post Occupancy Evaluation in the case study of a hospital ward, which is intended to develop an agent-based spatial analysis. A functional and organizational redesign of the ward plan is proposed following the analysis of social and spatial behaviour of agents. The outlined methodology aims to prepare the development of a multi-agent software simulation to validate the proposed redesign from a human-centred perspective. Findings indicate the relevance of the proposed approach starting from organizational contexts with complex workflows where cooperation between agents is widely exist, such as in healthcare environments. The framework is structured as a methodology to support the practice of architectural design and urban planning for the realization of more efficient and sustainable cities.
Author Contributions: Conceptualization, methodology, formalization, review and editing D.E.; investigation and visualization D.E. and I.A.; writing – introduction, background, and conclusions D.E.; writing - case study and results D.E. and I.A. All authors have read and agreed to the published version of the manuscript.
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Acknowledgments
We wish to thank Professor Angela Pezzolla, Professor Dino Borri and Professor Domenico Camarda for their valuable methodological assistance. We are grateful to the nurses, doctors and hospital managers of the Policlinico hospital of Bari (Italy) for their availability.
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Esposito, D., Abbattista, I. (2020). Dynamic Network Visualization of Space Use Patterns to Support Agent-based Modelling for Spatial Design. In: Luo, Y. (eds) Cooperative Design, Visualization, and Engineering. CDVE 2020. Lecture Notes in Computer Science(), vol 12341. Springer, Cham. https://doi.org/10.1007/978-3-030-60816-3_29
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