Citation

Jafriz, Iskandar Zulkarnain and Mansor, Sarina (2022) Smart Retail Monitoring System using Intel OpenVINO Toolkit. International Journal of Technology, 13 (6). p. 1241. ISSN 2086-9614

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Abstract

In the era of Covid-19 infection, enforcing social distance is essential for confined areas such as shopping retails and classrooms. Human workforce is used to ensure the safety measure rules are adhered. However, a better technique to enforce social distancing regulations is to use an automated system that counts and detects people and measures the social distance. This work proposes an innovative retail monitoring system based on the Intel Distribution of Open VINO toolkit. The system uses deep learning techniques and trained models to automatically count the number of individuals, the number of persons entering and exiting premises, and the distance between each person to ensure social distancing. Five experiments were conducted to evaluate the efficiency and accuracy of the system.

Item Type:	Article
Uncontrolled Keywords:	Intel OpenVINO, Machine learning, Monitoring system, Smart retail, Social distancing
Subjects:	Q Science > Q Science (General) > Q300-390 Cybernetics
Divisions:	Faculty of Engineering (FOE)
Depositing User:	Ms Nurul Iqtiani Ahmad
Date Deposited:	13 Jan 2023 01:42
Last Modified:	13 Jan 2023 01:42
URII:	http://shdl.mmu.edu.my/id/eprint/11087

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