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Smart-parking management algorithms in smart city
Recently, various advanced technologies have been employed to build smart cities. Smart cities aim at improving the quality of life through the delivery of better services. One of the current services that are essential for any smart city, is the availability of enough parking spaces to ensure smoot...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9020765/ https://www.ncbi.nlm.nih.gov/pubmed/35444220 http://dx.doi.org/10.1038/s41598-022-10076-4 |
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author | Jemmali, Mahdi Melhim, Loai Kayed B. Alharbi, Mafawez T. Bajahzar, Abdullah Omri, Mohamed Nazih |
author_facet | Jemmali, Mahdi Melhim, Loai Kayed B. Alharbi, Mafawez T. Bajahzar, Abdullah Omri, Mohamed Nazih |
author_sort | Jemmali, Mahdi |
collection | PubMed |
description | Recently, various advanced technologies have been employed to build smart cities. Smart cities aim at improving the quality of life through the delivery of better services. One of the current services that are essential for any smart city, is the availability of enough parking spaces to ensure smooth and easy traffic flow. This research proposes a new framework for solving the problem of parking lot allocation, which emphasizes the equitable allocation of people based on the overall count of people in each parking space. The allocation process is performed while considering the available parking lots in each parking space. To accomplish the desired goal, this research will develop a set of seven algorithms to reduce the gap in the number of people between parking spaces. Many experiments carried out on 2430 different cases to cover several aspects such as the execution time and the gap calculations, were used to explore the performance of the developed algorithm. Analyzing the obtained results indicates a good performance behavior of the developed algorithms. Also, it shows that the developed algorithms can solve the studied problem in terms of gap and time calculations. The MR algorithm gained excellent performance results compared to one of the best algorithms in the literature. The MR algorithm has a percentage of 96.1 %, an average gap of 0.02, and a good execution time of 0.007 s. |
format | Online Article Text |
id | pubmed-9020765 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-90207652022-04-21 Smart-parking management algorithms in smart city Jemmali, Mahdi Melhim, Loai Kayed B. Alharbi, Mafawez T. Bajahzar, Abdullah Omri, Mohamed Nazih Sci Rep Article Recently, various advanced technologies have been employed to build smart cities. Smart cities aim at improving the quality of life through the delivery of better services. One of the current services that are essential for any smart city, is the availability of enough parking spaces to ensure smooth and easy traffic flow. This research proposes a new framework for solving the problem of parking lot allocation, which emphasizes the equitable allocation of people based on the overall count of people in each parking space. The allocation process is performed while considering the available parking lots in each parking space. To accomplish the desired goal, this research will develop a set of seven algorithms to reduce the gap in the number of people between parking spaces. Many experiments carried out on 2430 different cases to cover several aspects such as the execution time and the gap calculations, were used to explore the performance of the developed algorithm. Analyzing the obtained results indicates a good performance behavior of the developed algorithms. Also, it shows that the developed algorithms can solve the studied problem in terms of gap and time calculations. The MR algorithm gained excellent performance results compared to one of the best algorithms in the literature. The MR algorithm has a percentage of 96.1 %, an average gap of 0.02, and a good execution time of 0.007 s. Nature Publishing Group UK 2022-04-20 /pmc/articles/PMC9020765/ /pubmed/35444220 http://dx.doi.org/10.1038/s41598-022-10076-4 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Jemmali, Mahdi Melhim, Loai Kayed B. Alharbi, Mafawez T. Bajahzar, Abdullah Omri, Mohamed Nazih Smart-parking management algorithms in smart city |
title | Smart-parking management algorithms in smart city |
title_full | Smart-parking management algorithms in smart city |
title_fullStr | Smart-parking management algorithms in smart city |
title_full_unstemmed | Smart-parking management algorithms in smart city |
title_short | Smart-parking management algorithms in smart city |
title_sort | smart-parking management algorithms in smart city |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9020765/ https://www.ncbi.nlm.nih.gov/pubmed/35444220 http://dx.doi.org/10.1038/s41598-022-10076-4 |
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