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Fog computing-assisted path planning for smart shopping.
Aliyu, Farouq; Abdeen, Mohammad A R; Sheltami, Tarek; Alfraidi, Tareq; Ahmed, Mohamed H.
  • Aliyu F; Academic Belt Road, Dhahran, 31261 Saudi Arabia Computer Engineering Department, King Fahd University of Petroleum and Mineral.
  • Abdeen MAR; Abo Bakr Al Siddiq, Al Jamiah, Madina, 42351 Saudi Arabia Department of Computer Science, Islamic University of Madinah.
  • Sheltami T; Academic Belt Road, Dhahran, 31261 Saudi Arabia Computer Engineering Department, King Fahd University of Petroleum and Mineral.
  • Alfraidi T; Abo Bakr Al Siddiq, Al Jamiah, Madina, 42351 Saudi Arabia Department of Linguistics, Islamic University of Madinah.
  • Ahmed MH; 75 Laurier Ave. East, Ottowa, Ontario K1N 6N5 Canada School of Electrical Engineer and Computer Science, University of Ottawa.
Multimed Tools Appl ; : 1-26, 2023 Mar 25.
Article in English | MEDLINE | ID: covidwho-2249073
ABSTRACT
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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Full text: Available Collection: International databases Database: MEDLINE Language: English Journal: Multimed Tools Appl Year: 2023 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Language: English Journal: Multimed Tools Appl Year: 2023 Document Type: Article