@article{DANG2013421,
title = {A framework for pedestrian comfort navigation using multi-modal environmental sensors},
author = {Congwei Dang and Masayuki Iwai and Yoshito Tobe and Kazunori Umeda and Kaoru Sezaki},
url = {http://www.sciencedirect.com/science/article/pii/S1574119213000242},
doi = {https://doi.org/10.1016/j.pmcj.2013.01.002},
issn = {1574-1192},
year = {2013},
date = {2013-01-01},
journal = {Pervasive and Mobile Computing},
volume = {9},
number = {3},
pages = {421 - 436},
abstract = {Environments significantly influence the sensation of pedestrians, while sensing and navigation technologies can help people improve their trip comfort. In this paper, we present an integrated framework, named NaviComf, which constructs pedestrian navigation systems to improve comfort in time varying environments taking into account the heterogeneous environmental factors. With NaviComf we aim to systematically provide solutions to the four key issues: (1) how to organize the huge amount of sensor data, (2) how to forecast future environmental information, (3) how to incorporate the heterogeneous environmental factors, and (4) how to select optimal paths in time varying environments. We have gathered sensor data of air temperature, relative humidity, and pedestrian congestion in real environments. We have also implemented a prototype system on the basis of the framework using the sensor data. Results of simulations and evaluations show that NaviComf can efficiently provide more comfortable paths as compared with the traditional navigation method.},
note = {Special Issue: Selected Papers from the 2012 IEEE International Conference on Pervasive Computing and Communications (PerCom 2012)},
keywords = {Environmental sensing, Multi-factor cost model, Pedestrian navigation, Time-dependent network},
pubstate = {published},
tppubtype = {article}
}