TY - GEN
T1 - General-purpose deep tracking platform across protocols for the internet of things
AU - An, Zhenlin
AU - Lin, Qiongzheng
AU - Li, Ping
AU - Yang, Lei
N1 - Funding Information:
Zhenlin An and Qiongzheng Lin are the co-primary authors. Lei Yang is the corresponding author. The research is supported by NSFC for Young Scientists of China (NO. 61972331), NSFC General Program (NO. 61902331), NSFC Key Program (NO. 61932017) and UGC/ECS (NO. 25222917). We thank all the anonymous reviewers and the shepherd, Dr. Eric Rozner, for their valuable comments and helpful suggestions.
Publisher Copyright:
© 2020 ACM.
PY - 2020/6/15
Y1 - 2020/6/15
N2 - In recent years, considerable effort has been recently exerted to explore the high-precision RF-tracking systems indoors to satisfy various real-world demands. However, such systems are tailored for a particular type of device (e.g., RFID, WSN or Wi-Fi). With the rapid development of the Internet of Things (IoT), various new wireless protocols (e.g., LoRa, Sigfox, and NB-IoT) have been proposed to accommodate different demands. The coexistence of multiple types of IoT devices forces users to deploy multiple tracking systems in a warehouse or a smart home where various IoT devices are running, which causes huge additional costs in installation and maintenance. To address this issue, this work presents iArk, which is a general-purpose tracking platform for all types of IoT devices working at the ultra high frequency band. Our innovation lies in the design of the "K+1"-model hardware, the protocol free middleware, and the multipath resistant learnware. By the virtue of decoupling from wireless protocols, iArk also allows researchers to concentrate on developing a new tracking algorithm without considering the protocol diversity. To date, the platform can support five mainstream types of IoT devices (i.e., NB-IoT, LoRa, RFID, Sigfox and Zigbee) and is scalable to other types with minimal effort.
AB - In recent years, considerable effort has been recently exerted to explore the high-precision RF-tracking systems indoors to satisfy various real-world demands. However, such systems are tailored for a particular type of device (e.g., RFID, WSN or Wi-Fi). With the rapid development of the Internet of Things (IoT), various new wireless protocols (e.g., LoRa, Sigfox, and NB-IoT) have been proposed to accommodate different demands. The coexistence of multiple types of IoT devices forces users to deploy multiple tracking systems in a warehouse or a smart home where various IoT devices are running, which causes huge additional costs in installation and maintenance. To address this issue, this work presents iArk, which is a general-purpose tracking platform for all types of IoT devices working at the ultra high frequency band. Our innovation lies in the design of the "K+1"-model hardware, the protocol free middleware, and the multipath resistant learnware. By the virtue of decoupling from wireless protocols, iArk also allows researchers to concentrate on developing a new tracking algorithm without considering the protocol diversity. To date, the platform can support five mainstream types of IoT devices (i.e., NB-IoT, LoRa, RFID, Sigfox and Zigbee) and is scalable to other types with minimal effort.
KW - Deep learning
KW - Internet of Things
KW - Localization
UR - http://www.scopus.com/inward/record.url?scp=85088143147&partnerID=8YFLogxK
U2 - 10.1145/3386901.3389029
DO - 10.1145/3386901.3389029
M3 - Conference article published in proceeding or book
AN - SCOPUS:85088143147
T3 - MobiSys 2020 - Proceedings of the 18th International Conference on Mobile Systems, Applications, and Services
SP - 94
EP - 106
BT - MobiSys 2020 - Proceedings of the 18th International Conference on Mobile Systems, Applications, and Services
PB - Association for Computing Machinery, Inc
T2 - 18th ACM International Conference on Mobile Systems, Applications, and Services, MobiSys 2020
Y2 - 15 June 2020 through 19 June 2020
ER -