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Fog computing-assisted path planning for smart shopping

A Smart City (SC) is a viable solution for green and sustainable living, especially with the current explosion in global population and rural-urban immigration. One of the fields that is not getting much attention in the Smart Economy (SE) is customer satisfaction. The SE is a component of SC that i...

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Autores principales: Aliyu, Farouq, Abdeen, Mohammad A. R., Sheltami, Tarek, Alfraidi, Tareq, Ahmed, Mohamed H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10039442/
https://www.ncbi.nlm.nih.gov/pubmed/37362689
http://dx.doi.org/10.1007/s11042-023-14926-9
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author Aliyu, Farouq
Abdeen, Mohammad A. R.
Sheltami, Tarek
Alfraidi, Tareq
Ahmed, Mohamed H.
author_facet Aliyu, Farouq
Abdeen, Mohammad A. R.
Sheltami, Tarek
Alfraidi, Tareq
Ahmed, Mohamed H.
author_sort Aliyu, Farouq
collection PubMed
description A Smart City (SC) is a viable solution for green and sustainable living, especially with the current explosion in global population and rural-urban immigration. One of the fields that is not getting much attention in the Smart Economy (SE) is customer satisfaction. The SE is a component of SC that is concerned with using Information and Communication Technology (ICT) to improve stages of the traditional economy. In this paper, we propose a fog computing-based shopping recommendation system. Our simulations used Al-Madinah city as a case study. It aims to improve the customer shopping experience. Customers in shopping malls can connect to the system via Wi-Fi. Then the system recommends products to the shoppers according to their preferences. It optimizes shoppers’ schedules using price, the distance between the shops, and the congestion. It also improves customers’ savings by up to 30%. It also increases the shopping speed by up to 6.12% compared to the system proposed in the literature.
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spelling pubmed-100394422023-03-27 Fog computing-assisted path planning for smart shopping Aliyu, Farouq Abdeen, Mohammad A. R. Sheltami, Tarek Alfraidi, Tareq Ahmed, Mohamed H. Multimed Tools Appl Article A Smart City (SC) is a viable solution for green and sustainable living, especially with the current explosion in global population and rural-urban immigration. One of the fields that is not getting much attention in the Smart Economy (SE) is customer satisfaction. The SE is a component of SC that is concerned with using Information and Communication Technology (ICT) to improve stages of the traditional economy. In this paper, we propose a fog computing-based shopping recommendation system. Our simulations used Al-Madinah city as a case study. It aims to improve the customer shopping experience. Customers in shopping malls can connect to the system via Wi-Fi. Then the system recommends products to the shoppers according to their preferences. It optimizes shoppers’ schedules using price, the distance between the shops, and the congestion. It also improves customers’ savings by up to 30%. It also increases the shopping speed by up to 6.12% compared to the system proposed in the literature. Springer US 2023-03-25 /pmc/articles/PMC10039442/ /pubmed/37362689 http://dx.doi.org/10.1007/s11042-023-14926-9 Text en © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Article
Aliyu, Farouq
Abdeen, Mohammad A. R.
Sheltami, Tarek
Alfraidi, Tareq
Ahmed, Mohamed H.
Fog computing-assisted path planning for smart shopping
title Fog computing-assisted path planning for smart shopping
title_full Fog computing-assisted path planning for smart shopping
title_fullStr Fog computing-assisted path planning for smart shopping
title_full_unstemmed Fog computing-assisted path planning for smart shopping
title_short Fog computing-assisted path planning for smart shopping
title_sort fog computing-assisted path planning for smart shopping
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10039442/
https://www.ncbi.nlm.nih.gov/pubmed/37362689
http://dx.doi.org/10.1007/s11042-023-14926-9
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