Automated construction of variable density navigable networks in a 3D indoor environment for emergency response

Abstract

Widespread human-induced or natural threats on buildings and their users have made preparedness and rapid response crucial issues for saving human lives. The ability to identify the paths of egress during an emergency is critical for rescue and emergency services. Quality models supporting real, or near-real, time decision making and allowing the implementation of automated methods are very important. In this paper, we propose a novel automated construction of the Variable Density Network (VDN) for determining egress paths in dangerous environments. VND is used for deriving a navigable network in an indoor building environment, including a full 3D topological model. The accuracy of the proposed paths prediction tool was compared with key methods for navigable network generation, using the actual floor plan of Doha World Trade Centre. Findings revealed that in comparison to prevailing approaches, a key benefit from this approach is an increased prediction accuracy of egress route planning.