Jemmali Mahdi
Department of Computer Science and Information, College of Science at Zulfi, Majmaah University, AL-Majmaah, 11952 Saudi Arabia.
MARS Laboratory, University of Sousse, Sousse, Tunisia.
Complex Intell Systems. 2022;8(1):597-609. doi: 10.1007/s40747-021-00524-5. Epub 2021 Oct 6.
Achieving community immunity against the coronavirus disease 2019 (COVID-19) depends on vaccinating the largest number of people within a specific period while taking all precautionary measures. To address this problem, this paper presents a smart parking system that will help the health crisis management committee to vaccinate the largest number of people with the minimum period of time while ensuring that all precautionary measures are followed, through a set of algorithms. These algorithms seek to ensure a uniform distribution of persons in parking. This paper proposes a novel complex system for smart parking and nine algorithms to address the NP-hard problem. The experimental results demonstrate the performance of the proposed algorithms in terms of gap and time. Applying these algorithms to smart cities to ensure precautionary measures against COVID-19 can help fight against this pandemic.
实现针对2019冠状病毒病(COVID-19)的群体免疫取决于在采取所有预防措施的同时,在特定时期内为尽可能多的人接种疫苗。为了解决这个问题,本文提出了一种智能停车系统,该系统将通过一组算法帮助健康危机管理委员会在最短的时间内为尽可能多的人接种疫苗,同时确保所有预防措施都得到遵守。这些算法旨在确保人员在停车场的均匀分布。本文提出了一种新颖的智能停车复杂系统和九种算法来解决NP难问题。实验结果展示了所提算法在差距和时间方面的性能。将这些算法应用于智慧城市以确保针对COVID-19的预防措施有助于抗击这一疫情。