TY - GEN
T1 - Study of localization method for switching between low electricity consumption and high precision for a watching system
AU - Kobayashi, Hideyuki
AU - Takahashi, Akiko
AU - Chiba, Shinji
AU - Fujiki, Nahomi M.
AU - Hayakawa, Yoshihiro
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/3/26
Y1 - 2018/3/26
N2 - The Internet of things is often used on researches analyzing and estimating human behavior and tracking their exact locations through mobile terminals. In particular, localization through the use of IoT is highly effective for watching over seniors, searching a missing child or detecting risky incidents. In this paper, we propose a hybrid system of localization that can be used as an accurate monitoring device for regular use and as a localization device with low power consumption and a long span operation for emergency use. The low power consumption is realized by switching to the system operated on Bluetooth Low Energy. As a result of experiments with actual machines, our proposed system could localize the area of a terminal located within 5 m distance with 100% accuracy. Moreover, its correct position can be identified with 84.2% accuracy by using the finger print method.
AB - The Internet of things is often used on researches analyzing and estimating human behavior and tracking their exact locations through mobile terminals. In particular, localization through the use of IoT is highly effective for watching over seniors, searching a missing child or detecting risky incidents. In this paper, we propose a hybrid system of localization that can be used as an accurate monitoring device for regular use and as a localization device with low power consumption and a long span operation for emergency use. The low power consumption is realized by switching to the system operated on Bluetooth Low Energy. As a result of experiments with actual machines, our proposed system could localize the area of a terminal located within 5 m distance with 100% accuracy. Moreover, its correct position can be identified with 84.2% accuracy by using the finger print method.
UR - http://www.scopus.com/inward/record.url?scp=85048838867&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85048838867&partnerID=8YFLogxK
U2 - 10.1109/ICCE.2018.8326279
DO - 10.1109/ICCE.2018.8326279
M3 - Conference contribution
AN - SCOPUS:85048838867
T3 - 2018 IEEE International Conference on Consumer Electronics, ICCE 2018
SP - 1
EP - 6
BT - 2018 IEEE International Conference on Consumer Electronics, ICCE 2018
A2 - Mohanty, Saraju P.
A2 - Corcoran, Peter
A2 - Li, Hai
A2 - Sengupta, Anirban
A2 - Lee, Jong-Hyouk
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 IEEE International Conference on Consumer Electronics, ICCE 2018
Y2 - 12 January 2018 through 14 January 2018
ER -