Design of Smart Unstaffed Retail Shop Based on IoT and Artificial Intelligence

Unstaffed retail shops have emerged recently and been noticeably changing our shopping styles. In terms of these shops, the design of vending machine is critical to user shopping experience. The conventional design typically uses weighing sensors incapable of sensing what the customer is taking. In...

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Autores principales:	Jianqiang Xu, Zhujiao Hu, Zhuo Zou, Junzhong Zou, Xiaoming Hu, Lizheng Liu, Lirong Zheng
Formato:	article
Lenguaje:	EN
Publicado:	IEEE 2020
Materias:	Unstaffed retail Internet of Things vending machine artificial intelligence SSD Electrical engineering. Electronics. Nuclear engineering TK1-9971
Acceso en línea:	https://doaj.org/article/c26287597fc64320a8fd05fc793c31ef
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spelling	oai:doaj.org-article:c26287597fc64320a8fd05fc793c31ef2021-11-19T00:03:35ZDesign of Smart Unstaffed Retail Shop Based on IoT and Artificial Intelligence2169-353610.1109/ACCESS.2020.3014047https://doaj.org/article/c26287597fc64320a8fd05fc793c31ef2020-01-01T00:00:00Zhttps://ieeexplore.ieee.org/document/9154684/https://doaj.org/toc/2169-3536Unstaffed retail shops have emerged recently and been noticeably changing our shopping styles. In terms of these shops, the design of vending machine is critical to user shopping experience. The conventional design typically uses weighing sensors incapable of sensing what the customer is taking. In the present study, a smart unstaffed retail shop scheme is proposed based on artificial intelligence and the internet of things, as an attempt to enhance the user shopping experience remarkably. To analyze multiple target features of commodities, the SSD (<inline-formula> <tex-math notation="LaTeX">$300\times 300$ </tex-math></inline-formula>) algorithm is employed; the recognition accuracy is further enhanced by adding sub-prediction structure. Using the data set of 18, 000 images in different practical scenarios containing 20 different type of stock keeping units, the comparison experimental results reveal that the proposed SSD (<inline-formula> <tex-math notation="LaTeX">$300\times 300$ </tex-math></inline-formula>) model outperforms than the original SSD (<inline-formula> <tex-math notation="LaTeX">$300\times 300$ </tex-math></inline-formula>) in goods detection, the mean average precision of the developed method reaches 96.1% on the test dataset, revealing that the system can make up for the deficiency of conventional unmanned container. The practical test shows that the system can meet the requirements of new retail, which greatly increases the customer flow and transaction volume.Jianqiang XuZhujiao HuZhuo ZouJunzhong ZouXiaoming HuLizheng LiuLirong ZhengIEEEarticleUnstaffed retailInternet of Thingsvending machineartificial intelligenceSSDElectrical engineering. Electronics. Nuclear engineeringTK1-9971ENIEEE Access, Vol 8, Pp 147728-147737 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	Unstaffed retail Internet of Things vending machine artificial intelligence SSD Electrical engineering. Electronics. Nuclear engineering TK1-9971
spellingShingle	Unstaffed retail Internet of Things vending machine artificial intelligence SSD Electrical engineering. Electronics. Nuclear engineering TK1-9971 Jianqiang Xu Zhujiao Hu Zhuo Zou Junzhong Zou Xiaoming Hu Lizheng Liu Lirong Zheng Design of Smart Unstaffed Retail Shop Based on IoT and Artificial Intelligence
description	Unstaffed retail shops have emerged recently and been noticeably changing our shopping styles. In terms of these shops, the design of vending machine is critical to user shopping experience. The conventional design typically uses weighing sensors incapable of sensing what the customer is taking. In the present study, a smart unstaffed retail shop scheme is proposed based on artificial intelligence and the internet of things, as an attempt to enhance the user shopping experience remarkably. To analyze multiple target features of commodities, the SSD (<inline-formula> <tex-math notation="LaTeX">$300\times 300$ </tex-math></inline-formula>) algorithm is employed; the recognition accuracy is further enhanced by adding sub-prediction structure. Using the data set of 18, 000 images in different practical scenarios containing 20 different type of stock keeping units, the comparison experimental results reveal that the proposed SSD (<inline-formula> <tex-math notation="LaTeX">$300\times 300$ </tex-math></inline-formula>) model outperforms than the original SSD (<inline-formula> <tex-math notation="LaTeX">$300\times 300$ </tex-math></inline-formula>) in goods detection, the mean average precision of the developed method reaches 96.1% on the test dataset, revealing that the system can make up for the deficiency of conventional unmanned container. The practical test shows that the system can meet the requirements of new retail, which greatly increases the customer flow and transaction volume.
format	article
author	Jianqiang Xu Zhujiao Hu Zhuo Zou Junzhong Zou Xiaoming Hu Lizheng Liu Lirong Zheng
author_facet	Jianqiang Xu Zhujiao Hu Zhuo Zou Junzhong Zou Xiaoming Hu Lizheng Liu Lirong Zheng
author_sort	Jianqiang Xu
title	Design of Smart Unstaffed Retail Shop Based on IoT and Artificial Intelligence
title_short	Design of Smart Unstaffed Retail Shop Based on IoT and Artificial Intelligence
title_full	Design of Smart Unstaffed Retail Shop Based on IoT and Artificial Intelligence
title_fullStr	Design of Smart Unstaffed Retail Shop Based on IoT and Artificial Intelligence
title_full_unstemmed	Design of Smart Unstaffed Retail Shop Based on IoT and Artificial Intelligence
title_sort	design of smart unstaffed retail shop based on iot and artificial intelligence
publisher	IEEE
publishDate	2020
url	https://doaj.org/article/c26287597fc64320a8fd05fc793c31ef
work_keys_str_mv	AT jianqiangxu designofsmartunstaffedretailshopbasedoniotandartificialintelligence AT zhujiaohu designofsmartunstaffedretailshopbasedoniotandartificialintelligence AT zhuozou designofsmartunstaffedretailshopbasedoniotandartificialintelligence AT junzhongzou designofsmartunstaffedretailshopbasedoniotandartificialintelligence AT xiaominghu designofsmartunstaffedretailshopbasedoniotandartificialintelligence AT lizhengliu designofsmartunstaffedretailshopbasedoniotandartificialintelligence AT lirongzheng designofsmartunstaffedretailshopbasedoniotandartificialintelligence
_version_	1718420692539539456

Design of Smart Unstaffed Retail Shop Based on IoT and Artificial Intelligence

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