@INPROCEEDINGS{agnihotri2018evacuating,
author={A. {Agnihotri} and S. {Fathi-Kazerooni} and Y. {Kaymak} and R. {Rojas-Cessa}},
booktitle={2018 IEEE 39th Sarnoff Symposium},
title={Evacuating Routes in Indoor-Fire Scenarios with Selection of Safe Exits on Known and Unknown Buildings Using Machine Learning},
year={2018},
volume={},
number={},
pages={1-6},
keywords={buildings (structures);emergency management;emergency services;fires;floors;learning (artificial intelligence);probability;potentially safe exit;evacuation time;scheme pre-calculates;occupant;exit pre-selection;evacuation success ratio;evacuation routing scheme;route calculation;machine learning;floor plan similarities;successful evacuation;floor similarity accuracy estimation increases;analyzed floor plans;indoor-fire scenarios;safe exits;indoor evacuation routes;single-floor building;evacuation starts;Windows;Routing;Servers;Estimation;Communication networks;Robot sensing systems;fire;emergency network;evacuation;emergency scenario;sensor network},
doi={10.1109/SARNOF.2018.8720478},
ISSN={},
month={Sep.},}