Title :
A Cloud-Storage RFID Location Tracking System
Author :
Yeong-Lin Lai ; Cheng, James
Author_Institution :
Dept. of Mechatron. Eng., Nat. Changhua Univ. of Educ., Changhua, Taiwan
Abstract :
This paper presents a cloud-storage location tracking system designed and implemented with radio frequency identification (RFID) technology, wireless sensor network (WSN) technology, and a location tracking algorithm (LTA), based on cloud computing technology. This system used the signal attenuation model (SAM) in a nonopen space, received signal strength indicator (RSSI), link quality indicator (LQI), and cloud localization algorithm (CLA) for object tracking. The cloud-storage RFID location tracking system using a network node communication technique provided real-time localization and tracking for object recognition and collected the object information from sensors. The software as a service (SaaS) model was used for cloud computing to enhance user convenience. The personal homepage program (PHP) and cascading style sheets (CSS) language technologies were used for the user interface of the system. The SAM and reference tag information were used to reduce localization errors in the nonopen space. The cloud-storage RFID location tracking system achieved significant improvements in both high localization accuracy and low hardware costs.
Keywords :
cloud computing; radiofrequency identification; storage management; wireless sensor networks; CLA; LQI; LTA; RSSI; SAM; SaaS model; WSN technology; cascading style sheets language technologies; cloud computing technology; cloud localization algorithm; cloud-storage RFID location tracking system; link quality indicator; nonopen space; object tracking; personal homepage program; radiofrequency identification technology; received signal strength indicator; signal attenuation model; software as a service model; wireless sensor network technology; Attenuation; Cloud computing; Computational modeling; Hardware; Radiofrequency identification; Servers; Wireless sensor networks; Cloud computing; cloud storage; location tracking; radio frequency identification (RFID); wireless sensor network (WSN);
Journal_Title :
Magnetics, IEEE Transactions on
DOI :
10.1109/TMAG.2014.2303810