The traditional approach to the building emergency management is based on a deterministic prevision of the main scenarios, regardless of contextual, changing and unexpected events that may happen and seriously affect the effectiveness of emergency measures. The current approach results affected by several weaknesses due to a poor and inefficient data acquisition regarding the evolving scenario and to the bottlenecks in the decision flow, deriving from a too rigid hierarchical workflow. The contribution of this dissertation lies on the development of a new methodology in the emergency management based on the principles of real-time effectiveness, resilience and unconventional problem solving. A shift from a deterministic to a contingent approach is proposed, leveraging the system’s flexibility and adaptability to changing scenarios, founded on the application of the Holonic Theory to the emergency management. This theory promotes a higher autonomy and cooperation among the actors of the lowest level of the hierarchy, as a response to a too rigid hierarchical workflow, often affected by bottlenecks in the decision flow that may result fatal in critical scenarios like the emergency ones. The research has conducted to the definition of a system architecture as support to the standard rescue operations, which improves the usual approach supplying more updated and significant information from different sources and investigating unusual solutions for rescue purposes in case of unforeseen events. It relies on the means of BIM (Building Information Modelling), as comprehensive building information provider, Bayesian Networks to make the decision flow more flexible and able to cope with uncertainties and Virtual Reality engines to collect data from heterogeneous sources and test the overall system. The bottlenecks in the process flow result considerably reduced, providing the system with a faster capability to face unexpected events, endowing it with the required resilience and adaptability.
Il tradizionale approccio alla gestione delle emergenze negli edifici si basa sulla previsione deterministica dei principali scenari che potrebbero verificarsi, non tenendo conto degli eventi casuali e inaspettati che potrebbero presentarsi influendo negativamente sulle operazioni da eseguire in caso di emergenza. L’approccio attuale presenta diversi punti di debolezza dovuti ad un’acquisizione di dati sullo stato di emergenza scarsa e poco efficiente e a diversi “colli di bottiglia” nel processo decisionale, che appare irrigidito dal suo carattere eccessivamente gerarchico. Il contributo scientifico di questa tesi, consiste nello sviluppo di una metodologia nella gestione delle emergenze che presenta innovative caratteristiche di efficienza in tempo reale, resilienza e capacità di risoluzione di problemi in modi non convenzionali. Si propone un cambio di rotta da un approccio deterministico ad uno volto ad affrontare la contingenza delle situazioni che potrebbero verificarsi, elevando la flessibilità e adattabilità del sistema, attraverso l’applicazione della teoria “olonica”, la quale promuove maggiore autonomia e cooperazione tra i livelli più bassi della gerarchia in risposta a un workflow troppo rigido. La ricerca ha condotto alla definizione di un’architettura di sistema a supporto delle operazioni standard previste da normativa, rendendole più efficienti attraverso l’utilizzo di dati aggiornati ed eterogenei, proponendo soluzioni alternative in caso di imprevisti, rapidamente calcolate. La metodologia è stata implementata in un caso studio, dettagliandone l’architettura di sistema fondata sull’utilizzo di modelli BIM come “contenitori” di informazioni aggiornate, coerenti e complete sull’edificio, di Reti Bayesiane per selezionare le azioni alternative più promettenti analizzando rapidamente le serie di dati al momento disponibili e una piattaforma di Realtà Virtuale come collettore di dati provenienti da fonti eterogenee e ambiente di simulazione con elementi di Intelligenza Artificiale.
Management of Unexpected Events in Emergency Scenarios / Tolve, LUCIA CRISTINA. - (2019 Mar 27).
Management of Unexpected Events in Emergency Scenarios
TOLVE, LUCIA CRISTINA
2019-03-27
Abstract
The traditional approach to the building emergency management is based on a deterministic prevision of the main scenarios, regardless of contextual, changing and unexpected events that may happen and seriously affect the effectiveness of emergency measures. The current approach results affected by several weaknesses due to a poor and inefficient data acquisition regarding the evolving scenario and to the bottlenecks in the decision flow, deriving from a too rigid hierarchical workflow. The contribution of this dissertation lies on the development of a new methodology in the emergency management based on the principles of real-time effectiveness, resilience and unconventional problem solving. A shift from a deterministic to a contingent approach is proposed, leveraging the system’s flexibility and adaptability to changing scenarios, founded on the application of the Holonic Theory to the emergency management. This theory promotes a higher autonomy and cooperation among the actors of the lowest level of the hierarchy, as a response to a too rigid hierarchical workflow, often affected by bottlenecks in the decision flow that may result fatal in critical scenarios like the emergency ones. The research has conducted to the definition of a system architecture as support to the standard rescue operations, which improves the usual approach supplying more updated and significant information from different sources and investigating unusual solutions for rescue purposes in case of unforeseen events. It relies on the means of BIM (Building Information Modelling), as comprehensive building information provider, Bayesian Networks to make the decision flow more flexible and able to cope with uncertainties and Virtual Reality engines to collect data from heterogeneous sources and test the overall system. The bottlenecks in the process flow result considerably reduced, providing the system with a faster capability to face unexpected events, endowing it with the required resilience and adaptability.File | Dimensione | Formato | |
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