Social dimension is a fundamental part of sustainable spatial planning, design and management. Envisioning its requirements and consequences is of the utmost importance when implementing solutions. Decision Support Systems aim towards improving decision-making processes in the development of infrastructures and services. They assist decision makers in assessing to what extent the designed places meet the requirements expressed by intended users. However, there is an intrinsic limit in the forecasting of emerging phenomena in spatial complex systems. This is because the use of built environment could differ from its function since it changes as a response to the context and it reflects emergent and dynamic human spatial and social behaviour. This paper proposes a Multi-Agent Simulation approach to support Decision-Making for the spatial design and management of complex systems in risk conditions. A virtual simulation shows a hospital ward in the case of health risk due to Hospital Acquired Infection, with an emphasis on the spatial spread of the risk. It is applied to find out correlations between human characteristics, behaviours and activities influenced by spatial design and distribution. The scenario-building mechanism is designed to improve decision-making by offering a consideration of the simulation outcomes. The visualization of how a building environment is used is suitable in verifying hypotheses and to support operational choices. The proposed framework aims at assessing and forecasting the building’s capacity to support user activities and to ensure users safety.

Decision support systems based on multi-agent simulation for spatial design and management of a built environment: The case study of hospitals / Esposito, Dario; Schaumann, Davide; Camarda, Domenico; Kalay, Yehuda E.. - STAMPA. - 12251:(2020), pp. 340-351. [10.1007/978-3-030-58808-3_25]

Decision support systems based on multi-agent simulation for spatial design and management of a built environment: The case study of hospitals

Dario Esposito
;
Domenico Camarda;
2020-01-01

Abstract

Social dimension is a fundamental part of sustainable spatial planning, design and management. Envisioning its requirements and consequences is of the utmost importance when implementing solutions. Decision Support Systems aim towards improving decision-making processes in the development of infrastructures and services. They assist decision makers in assessing to what extent the designed places meet the requirements expressed by intended users. However, there is an intrinsic limit in the forecasting of emerging phenomena in spatial complex systems. This is because the use of built environment could differ from its function since it changes as a response to the context and it reflects emergent and dynamic human spatial and social behaviour. This paper proposes a Multi-Agent Simulation approach to support Decision-Making for the spatial design and management of complex systems in risk conditions. A virtual simulation shows a hospital ward in the case of health risk due to Hospital Acquired Infection, with an emphasis on the spatial spread of the risk. It is applied to find out correlations between human characteristics, behaviours and activities influenced by spatial design and distribution. The scenario-building mechanism is designed to improve decision-making by offering a consideration of the simulation outcomes. The visualization of how a building environment is used is suitable in verifying hypotheses and to support operational choices. The proposed framework aims at assessing and forecasting the building’s capacity to support user activities and to ensure users safety.
2020
Computational Science and Its Applications - ICCSA 2020 : 20th International Conference, Cagliari, Italy, July 1-4, 2020. Proceedings, Part III
978-3-030-58807-6
Springer
Decision support systems based on multi-agent simulation for spatial design and management of a built environment: The case study of hospitals / Esposito, Dario; Schaumann, Davide; Camarda, Domenico; Kalay, Yehuda E.. - STAMPA. - 12251:(2020), pp. 340-351. [10.1007/978-3-030-58808-3_25]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11589/206955
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