TY - GEN
T1 - A PDR Method Combining Smartphone and Smartwatch based on Multi-Scenario Map Matching
AU - Wakaizumi, Tomoya
AU - Togawa, Nozomu
N1 - Funding Information:
ACKNOWLEDGMENT This work was supported in part by JST CREST Grant Number JPMJCR19K4, Japan.
Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - As smartphones are widely spread and used, the pedestrian navigation systems are utilized in our daily lives. A pedestrian dead reckoning method, or PDR method in short, is one of the positioning methods in indoor environments, which estimates user's positions by using sensors such as acceleration and angular velocity sensors. Particularly, by combining smartphone and smartwatch sensors, an effective PDR method has been proposed. This method can reduce drift errors even when the user carries his/her smartphone in various carrying modes without external infrastructures. However, the estimation errors tend to become large in the environments with many right and left turns. In this paper, we propose a PDR method combining smartphone and smartwatch sensors based on map information. In the proposed method, we generate walking nodes and walking edges from map information given and introduce multiple scenarios to effectively infer the user's current positions. Through experimental evaluation, we confirmed the effectiveness of the proposed method.
AB - As smartphones are widely spread and used, the pedestrian navigation systems are utilized in our daily lives. A pedestrian dead reckoning method, or PDR method in short, is one of the positioning methods in indoor environments, which estimates user's positions by using sensors such as acceleration and angular velocity sensors. Particularly, by combining smartphone and smartwatch sensors, an effective PDR method has been proposed. This method can reduce drift errors even when the user carries his/her smartphone in various carrying modes without external infrastructures. However, the estimation errors tend to become large in the environments with many right and left turns. In this paper, we propose a PDR method combining smartphone and smartwatch sensors based on map information. In the proposed method, we generate walking nodes and walking edges from map information given and introduce multiple scenarios to effectively infer the user's current positions. Through experimental evaluation, we confirmed the effectiveness of the proposed method.
KW - PDR
KW - carrying mode
KW - indoor positioning
KW - map matching
KW - multi scenario
KW - smartphone
KW - smartwatch
UR - http://www.scopus.com/inward/record.url?scp=85123504234&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85123504234&partnerID=8YFLogxK
U2 - 10.1109/GCCE53005.2021.9621836
DO - 10.1109/GCCE53005.2021.9621836
M3 - Conference contribution
AN - SCOPUS:85123504234
T3 - 2021 IEEE 10th Global Conference on Consumer Electronics, GCCE 2021
SP - 308
EP - 309
BT - 2021 IEEE 10th Global Conference on Consumer Electronics, GCCE 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 10th IEEE Global Conference on Consumer Electronics, GCCE 2021
Y2 - 12 October 2021 through 15 October 2021
ER -