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Spatio-temporal location modeling in a 3D indoor environment: the case of AEDs as emergency medical devices

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Abstract:

This research innovatively extends optimal emergency facility location models to the interior space of multistory buildings with an integrated spatial-temporal framework. We present the case of deployed emergency medical devices known as automated external defibrillators (AEDs), which serve to treat sudden cardiac arrest on-site within the first few critical minutes of the event. AEDs have become a critical element of basic life support services in many public buildings. The proposed framework is based on the concept of discrete time windows to capture the time-dependence of potential demand and stochastically model the detection time component of impedance as a function of space–time distribution of demand. Different optimization objectives minimizing sudden cardiac arrest outcome consequences (e.g., brain damage or death) as a function of suffering time are formulated and solved. The first model is the multiple-time-window maximal covering location problem model which optimizes the placement of AEDs by maximizing the covered demand over all time periods. The second is the multiple-time-window p-Median model which places AEDs to maximize the expected value of prevented death or permanent brain impairment in case of defibrillation treatment over multiple time windows. Both models are implemented through tight coupling of commercial geographic information system software and a linear programming solver. The models are novel in two primary respects, namely location modeling in 3D microscale spaces and the integration of spatial and temporal considerations. Innovative visualization techniques for AED indoor location and coverage are also presented.

Keywords: 3D visualization; location-allocation modeling; microscale spaces; socio-technical systems; spatio-temporal

Document Type: Research Article

DOI: http://dx.doi.org/10.1080/13658816.2011.597753

Affiliations: Department of Geography and Earth Sciences,University of North Carolina, Charlotte,NC,28223, USA

Publication date: March 1, 2012

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