TY - JOUR
T1 - Joint RFID and UWB Technologies in Intelligent Warehousing Management System
AU - Zhao, Kang
AU - Zhu, Minghua
AU - Xiao, Bo
AU - Yang, Xuguang
AU - Gong, Changlei
AU - Wu, Junyi
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2020/12
Y1 - 2020/12
N2 - Joint application of radio-frequency identification (RFID) and ultrawideband (UWB) technologies in the intelligent warehousing management system is proposed. In this system, we regard forklift as infrastructure, and both the UWB mobile terminal (MT) and the RFID reader are mounted on the forklift. The RFID reader is used not only to read the information of goods but also to determine the goods' status of loading and unloading. The UWB MT is used to locate the forklift. The goods or pallets are labeled with RFID tags. Utilizing the integration of these two technologies, the dual goals of goods information and goods location perception are achieved. An $M/N$ - $K$ sliding window method is proposed to determine the loading and unloading of goods in this article. Our experiments reveal that this novel method can quickly, accurately, and efficiently determine the states of the goods on the forklift. For the indoor localization, an algorithm is proposed based on RSS residual weighting (RRW). Experiments show that RRW can mitigate the nonline-of-sight error substantially compared with the conventional Taylor algorithm and recent Convex approximation algorithm. Finally, a real working practice in a warehouse of a company is introduced, and it illustrates the feasibility of the system.
AB - Joint application of radio-frequency identification (RFID) and ultrawideband (UWB) technologies in the intelligent warehousing management system is proposed. In this system, we regard forklift as infrastructure, and both the UWB mobile terminal (MT) and the RFID reader are mounted on the forklift. The RFID reader is used not only to read the information of goods but also to determine the goods' status of loading and unloading. The UWB MT is used to locate the forklift. The goods or pallets are labeled with RFID tags. Utilizing the integration of these two technologies, the dual goals of goods information and goods location perception are achieved. An $M/N$ - $K$ sliding window method is proposed to determine the loading and unloading of goods in this article. Our experiments reveal that this novel method can quickly, accurately, and efficiently determine the states of the goods on the forklift. For the indoor localization, an algorithm is proposed based on RSS residual weighting (RRW). Experiments show that RRW can mitigate the nonline-of-sight error substantially compared with the conventional Taylor algorithm and recent Convex approximation algorithm. Finally, a real working practice in a warehouse of a company is introduced, and it illustrates the feasibility of the system.
KW - Indoor positioning
KW - Internet of Things (IoT)
KW - NonLine of Sight (NLOS)
KW - intelligent warehousing management system (IWMS)
KW - radio-frequency identification (RFID)
KW - received signal strength (RSS)
KW - ultrawideband (UWB)
UR - https://www.scopus.com/pages/publications/85097823054
U2 - 10.1109/JIOT.2020.2998484
DO - 10.1109/JIOT.2020.2998484
M3 - 文章
AN - SCOPUS:85097823054
SN - 2327-4662
VL - 7
SP - 11640
EP - 11655
JO - IEEE Internet of Things Journal
JF - IEEE Internet of Things Journal
IS - 12
M1 - 9103578
ER -