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Shelf control in retail stores via ultra-low and low power microcontrollers

Authors :
M. Erkin Yücel
Cem Ünsalan
Yucel M. E., ÜNSALAN C.
Source :
Journal of Real-Time Image Processing. 19:751-762
Publication Year :
2022
Publisher :
Springer Science and Business Media LLC, 2022.

Abstract

Smart retail stores started to take place in our lives. Several computer vision and sensor-based systems are working together to achieve such a complex and automated operation. Besides, the retail sector has several open and challenging problems which can be solved by embedded computer vision systems. One important problem to be tackled is shelf control or stock out detection. Here, shelves in a store should be controlled regularly such that no item is missing in the shelf. In this study, we propose an embedded computer vision system to solve this problem. To do so, we frame the shelf control operation as change detection. Due to the constraints posed by the retail sector, we formed the system by an ultra-low or low power microcontroller with an embedded camera attached to it. We provided all the implementation details of the system both from software and hardware perspectives. We also tested the proposed shelf control system from different perspectives. Hence, the reader can form such a system for retail sector or for a broad class of change detection problems in which stand-alone embedded system usage is mandatory.

Details

ISSN :
18618219 and 18618200
Volume :
19
Database :
OpenAIRE
Journal :
Journal of Real-Time Image Processing
Accession number :
edsair.doi.dedup.....6e56d1d6c85c0adde9c3985a69ea0d05
Full Text :
https://doi.org/10.1007/s11554-022-01222-2