Predictive building emergency training and guidance system

The disclosed technology provides for generating simulation training models that can be used to prepare people (i.e., building occupants, first responders) to safely and calmly respond to emergencies, such as fires in high-rise buildings. Using the training models, people can better cope with decisi...

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Bibliographische Detailangaben
Hauptverfasser:	Derickson, Russell G, Hilliard, Susan R
Format:	Patent
Sprache:	eng
Schlagworte:	ADVERTISING APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND,DEAF OR MUTE CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING CRYPTOGRAPHY DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES DIAGNOSIS DIAGRAMS DISPLAY EDUCATION EDUCATIONAL OR DEMONSTRATION APPLIANCES ELECTRIC DIGITAL DATA PROCESSING GLOBES HUMAN NECESSITIES HYGIENE IDENTIFICATION MEDICAL OR VETERINARY SCIENCE PHYSICS PLANETARIA SEALS SURGERY SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR
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Beschreibung
Zusammenfassung:	The disclosed technology provides for generating simulation training models that can be used to prepare people (i.e., building occupants, first responders) to safely and calmly respond to emergencies, such as fires in high-rise buildings. Using the training models, people can better cope with decision-making during emergencies. The disclosed technology also uses signaling devices, wearables, and other devices and sensors distributed throughout a building to provide egress or stay-in-place guidance to people located in the building during an emergency. Audio and/or visual information can be outputted to people to guide them along a safe pathway that is selected to provide safe egress for the person, including anticipating and protecting the person from changing emergency conditions within the building and in response to how the person responded to the simulation training models.