Multisensor data fusion for determining hallway blockages in a building during evacuation

Date

2013-01-01

Author

Guven, G,
Ergen, E,
Ozbas, B,
Erberik, Murat Altuğ
Kurç, Özgür
Birgönül, Mustafa Talat

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When a building is under the threat of a disaster/an emergency, it is important to rapidly retrieve up-to-date indoor navigation conditions by identifying the hallways that are blocked. This paper investigates the contribution of data from each sensor that is deployed inside a building in accurately determining the current blockage conditions at hallways. Sensor performances were assessed, both individually and by fusing multisensor data at the building element-level. The final goal is to create and visualize evacuation and navigation paths for the first responders and the occupants during a disaster/an emergency. A prototype was developed to integrate Building Information Model (BIM) with hallway blockage information retrieved from multiple sensors and to provide guidance in a building based on the building's current status using graph theory principles. This paper specifically discusses if less sensors could be used to get similar accuracy results in detecting hallway blockages based on the individual and fused data from multiple sensors. © 2013 American Society of Civil Engineers.

Subject Keywords

Navigation (Geomatic), Probe Instruments, Evacuation, Automation And Robotics, Emergency Management, Disasters And Hazards, Construction Management, Building Information Modeling

URI

https://hdl.handle.net/11511/56278

DOI

https://doi.org/10.1061/9780784413029.090

Conference Name

ASCE International Workshop on Computing in Civil Engineering

Collections

Department of Civil Engineering, Conference / Seminar

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Citation Formats

G. Guven, E. Ergen, B. Ozbas, M. A. Erberik, Ö. Kurç, and M. T. Birgönül, “Multisensor data fusion for determining hallway blockages in a building during evacuation,” presented at the ASCE International Workshop on Computing in Civil Engineering, Los Angeles, California, 2013, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/56278.