Visual analysis of situationally aware building evacuations

Guest, Jack; Eaglin, Todd; Subramanian, Kalpathi; Ribarsky, William

doi:10.1117/12.2001535

Cited by 8 publications

(9 citation statements)

References 15 publications

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“…To provide evacuees with safe evacuation routes adaptive to changing hazard conditions, real-time computation and seamless handling of changing safety conditions are crucial. In [19], Guest et al developed computer visual analytic system and real-time visual analytic tools for situationally aware evacuations of large urban structures. They used two different levels of detail in the representation of building graphs that can be used as a part of a visual analytic system for near real-time response.…”

Section: Related Workmentioning

confidence: 99%

A distributed architecture for real-time evacuation guidance in large smart buildings

Lujak

Billhardt

Dunkel

et al. 2017

ComSIS

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In this paper, we consider the route coordination problem in emergency evacuation of large smart buildings. The building evacuation time is crucial in saving lives in emergency situations caused by imminent natural or man-made threats and disasters. Conventional approaches to evacuation route coordination are static and predefined. They rely on evacuation plans present only at a limited number of building locations and possibly a trained evacuation personnel to resolve unexpected contingencies. Smart buildings today are equipped with sensory infrastructure that can be used for an autonomous situation-aware evacuation guidance optimized in real time. A system providing such a guidance can help in avoiding additional evacuation casualties due to the flaws of the conventional evacuation approaches. Such a system should be robust and scalable to dynamically adapt to the number of evacuees and the size and safety conditions of a building. In this respect, we propose a distributed route recommender architecture for situation-aware evacuation guidance in smart buildings and describe its key modules in detail. We give an example of its functioning dynamics on a use case.

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Section: Related Workmentioning

confidence: 99%

A distributed architecture for real-time evacuation guidance in large smart buildings

Lujak

Billhardt

Dunkel

et al. 2017

ComSIS

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“…Mobility for the First Responder is a crucial aspect in their field of work. The absolute necessity of providing mobile system to campus police and first responders was observed during previous evacuation exercises [7]. First Responders are no longer satisfied with officebased work stations, but are demanding interactive mobile analysis techniques to carry out in the field.…”

Section: Real-time Monitoringmentioning

confidence: 99%

An Integrated In-Situ Approach to Impacts from Natural Disasters on Critical Infrastructures

Mittelstädt

Wang

Eaglin

et al. 2015

2015 48th Hawaii International Conference on System Sciences

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Abstract-Natural disasters can have a devastating effect on critical infrastructures, especially in case of cascading effects among multiple infrastructures such as the electric power grid, the communication network, and the road network. While there exist detailed models for individual types of infrastructures such as electric power grids, these do not encompass the various interconnections and interdependencies to other networks. Cascading effects are hard to discover and often the root cause of problems remain unclear. In order to enable real-time situational awareness for operational risk management one needs to be aware of the broader context of events. In this paper, we present a unique visual analytics control room system that integrates the separate visualizations of the different network infrastructures with social media analysis and mobile in-situ analysis to help to monitor the critical infrastructures, detecting cascading effects, performing root cause analyses, and managing the crisis response. Both the social media analysis and the mobile in-situ analysis are important components for an effective understanding of the crisis and an efficient crisis response. Our system provides a mechanism for conjoining the available information of different infrastructures and social media as well as mobile in-situ analysis in order to provide unified views and analytical tools for monitoring, planning, and decision support. A realistic use case scenario based on real critical infrastructures as well as our qualitative study with crisis managers shows the potential of our approach.

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“…Although conventional visualization methods have demonstrated promising performance in emergency evacuation analysis [RWF∗13, GESR13, BKLR14], identifying users’ exploration purposes and tracking features of interest, and delivering users’ exploration results are nontrivial for several reasons. (1) Massive information.…”

Section: Introductionmentioning

confidence: 99%

SEEVis: A Smart Emergency Evacuation Plan Visualization System with Data‐Driven Shot Designs

Liu

Chen

et al. 2020

Computer Graphics Forum

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Despite the significance of tracking human mobility dynamics in a large‐scale earthquake evacuation for an effective first response and disaster relief, the general understanding of evacuation behaviors remains limited. Numerous individual movement trajectories, disaster damages of civil engineering, associated heterogeneous data attributes, as well as complex urban environment all obscure disaster evacuation analysis. Although visualization methods have demonstrated promising performance in emergency evacuation analysis, they cannot effectively identify and deliver the major features like speed or density, as well as the resulting evacuation events like congestion or turn‐back. In this study, we propose a shot design approach to generate customized and narrative animations to track different evacuation features with different exploration purposes of users. Particularly, an intuitive scene feature graph that identifies the most dominating evacuation events is first constructed based on user‐specific regions or their tracking purposes on a certain feature. An optimal camera route, i.e., a storyboard is then calculated based on the previous user‐specific regions or features. For different evacuation events along this route, we employ the corresponding shot design to reveal the underlying feature evolution and its correlation with the environment. Several case studies confirm the efficacy of our system. The feedback from experts and users with different backgrounds suggests that our approach indeed helps them better embrace a comprehensive understanding of the earthquake evacuation.

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Visual analysis of situationally aware building evacuations

Cited by 8 publications

References 15 publications

A distributed architecture for real-time evacuation guidance in large smart buildings

A distributed architecture for real-time evacuation guidance in large smart buildings

An Integrated In-Situ Approach to Impacts from Natural Disasters on Critical Infrastructures

SEEVis: A Smart Emergency Evacuation Plan Visualization System with Data‐Driven Shot Designs

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