TY - GEN
T1 - Similarity Measures in Development of an Indoor Localization System
AU - Huang, Sheng
AU - Shoaib, Syed
AU - Ashfahani, Andri
AU - Pratama, Mahardhika
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/12/18
Y1 - 2018/12/18
N2 - One of the issues faced by manufacturing industry is a lack of automatic localization techniques. In this research, a Radio Frequency Identification (RFID) based localization system is proposed for resource tracking. In this study, we incorporated a RFID tag at each item to be tracked, and a RFID reference tag at each location zone. The encoded IDs are read to identify the names of items and location zones. At the same time, radio signals (received signal strength and phase) are measured as RFID fingerprints. Similarity measures are studied to compare fingerprints between RFID item tags and location reference tags to track the location of the items. The kernel-based learning method was implemented as similarity measure. Different cluster labelling methods were compared and it was found that the proximity method is more efficient. The clustering method is used to overcome the issues faced by traditional RFID based localization methods.
AB - One of the issues faced by manufacturing industry is a lack of automatic localization techniques. In this research, a Radio Frequency Identification (RFID) based localization system is proposed for resource tracking. In this study, we incorporated a RFID tag at each item to be tracked, and a RFID reference tag at each location zone. The encoded IDs are read to identify the names of items and location zones. At the same time, radio signals (received signal strength and phase) are measured as RFID fingerprints. Similarity measures are studied to compare fingerprints between RFID item tags and location reference tags to track the location of the items. The kernel-based learning method was implemented as similarity measure. Different cluster labelling methods were compared and it was found that the proximity method is more efficient. The clustering method is used to overcome the issues faced by traditional RFID based localization methods.
UR - http://www.scopus.com/inward/record.url?scp=85060823530&partnerID=8YFLogxK
U2 - 10.1109/ICARCV.2018.8581143
DO - 10.1109/ICARCV.2018.8581143
M3 - Conference contribution
AN - SCOPUS:85060823530
T3 - 2018 15th International Conference on Control, Automation, Robotics and Vision, ICARCV 2018
SP - 1420
EP - 1425
BT - 2018 15th International Conference on Control, Automation, Robotics and Vision, ICARCV 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 15th International Conference on Control, Automation, Robotics and Vision, ICARCV 2018
Y2 - 18 November 2018 through 21 November 2018
ER -