TMicroscope: Behavior Perception Based on the Slightest RFID Tag Motion
DOI:
https://doi.org/10.5755/j01.eie.22.2.14603Keywords:
RFID, Motion detection, consumer behaviour, support vector machines.Abstract
Behavior perception with fine granularity can offer much more valuable information, e.g. which and why products people are often interested in will not be purchased in shopping. In this paper, we propose a RFID-based method to perceive slight motion of a target product with RFID tag for mining customer’s behaviors. However, the interference from human movements in the reading zone is a challenge to result in false positives. To address this problem, we first compute virtual displacements of the target RFID tag and then adopt Support Vector Machines to recognize absence or presence of human motion near the tag. Next, we divide the surveillance region into mm-level grids to construct similarity matrixes of the tracked tag before and after human motion, which can accurately distinguish absence or presence of tag motion. Indeed, the optimization method based on phase-ambiguity is introduced to reduce computations. The results show that our method can achieve the average scenario classification accuracy of 96.3 % and the average slight tag motion perception accuracy of 100 % with the hypersensitivity of 1 mm.
Downloads
Published
How to Cite
Issue
Section
License
Authors retain copyright and grant the journal the right of the first publication with the paper simultaneously licensed under the Creative Commons Attribution 4.0 (CC BY 4.0) licence.
Authors are allowed to enter into separate, additional contractual arrangements for the non-exclusive distribution of the paper published in the journal with an acknowledgement of the initial publication in the journal.
Copyright terms are indicated in the Republic of Lithuania Law on Copyright and Related Rights, Articles 4-37.