Description

Accelerating urban growth has often outpaced the capacity of planners to guide urbanization processes. Despite efforts to create “intelligent” cities, decision making still remains a largely manual process. One example is in the lack of robust decision support systems (DSS) for risk management and safety in the construction sector. Building on a pilot project, this research has two objectives: (1) advance theories/concepts in systems understanding, by combining Morphological Analysis (MA) and Bayesian Belief Networks (BBNs) to model the underlying problem space and the inherent uncertainties, and (2) demonstrate a methodology for applying MA and BBNs in practice that can help to build useful DSSs for hazard mitigation in the construction sector. The proposed DSS serves as a case exemplar for building a planning tool for scenario analysis and impact assessment, and as an incident response mechanism for safer construction of a smart city.

Share

COinS
 

Combining Morphological Analysis and Bayesian Belief Networks: A DSS for Safer Construction of a Smart City

Accelerating urban growth has often outpaced the capacity of planners to guide urbanization processes. Despite efforts to create “intelligent” cities, decision making still remains a largely manual process. One example is in the lack of robust decision support systems (DSS) for risk management and safety in the construction sector. Building on a pilot project, this research has two objectives: (1) advance theories/concepts in systems understanding, by combining Morphological Analysis (MA) and Bayesian Belief Networks (BBNs) to model the underlying problem space and the inherent uncertainties, and (2) demonstrate a methodology for applying MA and BBNs in practice that can help to build useful DSSs for hazard mitigation in the construction sector. The proposed DSS serves as a case exemplar for building a planning tool for scenario analysis and impact assessment, and as an incident response mechanism for safer construction of a smart city.