TY - GEN
T1 - MMLOC
T2 - 16th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services, MobiQuitous 2019
AU - Yu, Tuo
AU - Ren, Wenyu
AU - Nahrstedt, Klara
PY - 2019/11/12
Y1 - 2019/11/12
N2 - Indoor localization based on Wi-Fi fingerprints has been an active research topic for years. However, existing approaches do not consider the instability of access points (APs) which may be unreliable in practice, particularly the ones deployed by individual users. This instability impacts the localization accuracy severely, due to the unreliable or even wrong Wi-Fi fingerprints. Ideally, the localization should be done using only the well-deployed APs (e.g., deployed by facility teams). However, in many places the number of these APs is too few to achieve a good localization accuracy. To solve this problem, we leverage emerging smart APs equipped with multi-mode antennas, and build a new indoor localization system called MMLOC to reduce the number of necessary APs. The key idea is controlling the modes of AP antennas to generate more fingerprints with fewer APs. A clustering based localization strategy is designed to enable a mobile terminal to figure out the RSSI (Received Signal Strength Indicator) for different antenna modes without requiring any synchronization. We have implemented a prototype system using smart APs and commercial smartphones. Experimental results demonstrate that MMLOC can reduce the number of necessary APs by 50%, and achieve the same or even better localization accuracy.
AB - Indoor localization based on Wi-Fi fingerprints has been an active research topic for years. However, existing approaches do not consider the instability of access points (APs) which may be unreliable in practice, particularly the ones deployed by individual users. This instability impacts the localization accuracy severely, due to the unreliable or even wrong Wi-Fi fingerprints. Ideally, the localization should be done using only the well-deployed APs (e.g., deployed by facility teams). However, in many places the number of these APs is too few to achieve a good localization accuracy. To solve this problem, we leverage emerging smart APs equipped with multi-mode antennas, and build a new indoor localization system called MMLOC to reduce the number of necessary APs. The key idea is controlling the modes of AP antennas to generate more fingerprints with fewer APs. A clustering based localization strategy is designed to enable a mobile terminal to figure out the RSSI (Received Signal Strength Indicator) for different antenna modes without requiring any synchronization. We have implemented a prototype system using smart APs and commercial smartphones. Experimental results demonstrate that MMLOC can reduce the number of necessary APs by 50%, and achieve the same or even better localization accuracy.
KW - Clustering
KW - Indoor Localization
KW - Smart Access Point
UR - http://www.scopus.com/inward/record.url?scp=85079901564&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85079901564&partnerID=8YFLogxK
U2 - 10.1145/3360774.3360776
DO - 10.1145/3360774.3360776
M3 - Conference contribution
AN - SCOPUS:85079901564
T3 - ACM International Conference Proceeding Series
SP - 473
EP - 482
BT - Proceedings of the 16th EAI International Conference on Mobile and Ubiquitous Systems
PB - Association for Computing Machinery
Y2 - 12 November 2019 through 14 November 2019
ER -