Muhammad Saad¹, Maaz Bin Ahmad^1,*, Muhammad Asif², Muhammad Khalid Khan¹, Toqeer Mahmood³, Elsayed Tag Eldin^4,*, Hala Abdel Hameed^5,6

CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 687-709, 2023, DOI:10.32604/cmc.2023.038335

Abstract Pandemics have always been a nightmare for humanity, especially in developing countries. Forced lockdowns are considered one of the effective ways to deal with spreading such pandemics. Still, developing countries cannot afford such solutions because these may severely damage the country’s economy. Therefore, this study presents the proactive technological mechanisms for business organizations to run their standard business processes during pandemic-like situations smoothly. The novelty of this study is to provide a state-of-the-art solution to prevent pandemics using industrial internet of things (IIoT) and blockchain-enabled technologies. Compared to existing studies, the immutable and tamper-proof contact tracing and quarantine management solution… More >

Zhihan Liu¹, Xiang Li¹, Siqi Liu², Wei Li^1,*, Xiangxu Meng¹, Jing Jia³

Computer Systems Science and Engineering, Vol.47, No.1, pp. 937-954, 2023, DOI:10.32604/csse.2023.039417

Abstract The COVID-19 virus is usually spread by small droplets when talking, coughing and sneezing, so maintaining physical distance between people is necessary to slow the spread of the virus. The World Health Organization (WHO) recommends maintaining a social distance of at least six feet. In this paper, we developed a real-time pedestrian social distance risk alert system for COVID-19, which monitors the distance between people in real-time via video streaming and provides risk alerts to the person in charge, thus avoiding the problem of too close social distance between pedestrians in public places. We design a lightweight convolutional neural network… More >

Naeem Ahmed Nawaz¹, Norah Saleh Alghamdi^2,*, Hanen Karamti², Mohammad Ayoub Khan³

CMES-Computer Modeling in Engineering & Sciences, Vol.133, No.2, pp. 327-350, 2022, DOI:10.32604/cmes.2022.020791

Abstract Assemblage at public places for religious or sports events has become an integral part of our lives. These gatherings pose a challenge at places where fast crowd verification with social distancing (SD) is required, especially during a pandemic. Presently, verification of crowds is carried out in the form of a queue that increases waiting time resulting in congestion, stampede, and the spread of diseases. This article proposes a cluster verification model (CVM) using a wireless sensor network (WSN), single cluster approach (SCA), and split cluster approach (SpCA) to solve the aforementioned problem for pandemic cases. We show that SD, cluster… More >

R. Haripriya^*, G. Kousalya

Computer Systems Science and Engineering, Vol.43, No.3, pp. 947-965, 2022, DOI:10.32604/csse.2022.024149

Abstract COVID-19 (Coronavirus disease of 2019) is caused by SARS-CoV2 (Severe Acute Respiratory Syndrome Coronavirus 2) and it was first diagnosed in December 2019 in China. As of 25th Aug 2021, there are 165 million confirmed COVID-19 positive cases and 4.4 million deaths globally. As of today, though there are approved COVID-19 vaccine candidates only 4 billion doses have been administered. Until 100% of the population is safe, no one is safe. Even though these vaccines can provide protection against getting seriously ill and dying from the disease, it does not provide 100% protection from getting infected and passing it on… More >

Hassan Al-Tarawneh¹, Khalid Al-Kaabneh¹, Aysh Alhroob², Hazem Migdady³, Issam Alhadid^4,*

Computer Systems Science and Engineering, Vol.41, No.3, pp. 933-944, 2022, DOI:10.32604/csse.2022.021078

Abstract Social distancing during COVID-19 has become one of the most important measures in reducing the risks of the spread of the virus. Implementing these measures at universities is crucial and directly related to the physical attendance of the populations of students, professors, employees, and other members on campus. This research proposes an automated scheduling approach that can help universities and schools comply with the social distancing regulations by providing assistance in avoiding huge assemblages of people. Furthermore, this paper proposes a novel course timetable-scheduling scheme based on four main constraints. First, a distance of two meters must be maintained between… More >

Yuan Ai Ho¹, Chee Keong Tan^1,*, Yin Hoe Ng²

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 907-924, 2022, DOI:10.32604/cmc.2022.021756

Abstract The world is experiencing the unprecedented time of a pandemic caused by the coronavirus disease (i.e., COVID-19). As a countermeasure, contact tracing and social distancing are essential to prevent the transmission of the virus, which can be achieved using indoor location analytics. Based on the indoor location analytics, the human mobility on a site can be monitored and planned to minimize human’s contact and enforce social distancing to contain the transmission of COVID-19. Given the indoor location data, the clustering can be applied to cluster spatial data, spatio-temporal data and movement behavior features for proximity detection or contact tracing applications.… More >

Muhammad Saad¹, Maaz Bin Ahmad¹, Muhammad Asif^2,*, Khalid Masood², Mohammad A. Al Ghamdi³

CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 3545-3562, 2021, DOI:10.32604/cmc.2021.015720

Abstract Social distancing and self-isolation management are crucial preventive measures that can save millions of lives during challenging pandemics of diseases such as the Spanish flu, swine flu, and coronavirus disease 2019 (COVID-19). This study describes the comprehensive and effective implementation of the Industrial Internet of Things and machine-to-machine technologies for social distancing and smart self-isolation management. These technologies can help prevent outbreaks of any disease that can disperse widely and develop into a pandemic. Initially, a smart wristband is proposed that incorporates Bluetooth beacon technology to facilitate the tracing and tracking of Bluetooth Low Energy beacon packets for smart contact… More >

Mohammad Zuber¹, John Valerian Corda¹, Milad Ahmadi², B. Satish Shenoy¹, Irfan Anjum Badruddin^3,*, Ali E. Anqi³, Kamarul Arifin Ahmad⁴, S. M. Abdul Khader⁵, Leslie Lewis⁶, Mohammad Anas Khan⁷, Sarfaraz Kamangar³

CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.3, pp. 1185-1199, 2020, DOI:10.32604/cmes.2020.015015

Abstract The novel coronavirus responsible for COVID-19 has spread to several countries within a considerably short period. The virus gets deposited in the human nasal cavity and moves to the lungs that might be fatal. As per safety guidelines by the World Health Organization (WHO), social distancing has emerged as one of the major factors to avoid the spread of infection. However, different guidelines are being followed across the countries with regards to what should be the safe distance. Thus, the current work is an attempt to understand the virus deposition pattern in the realistic human nasal cavity and also to… More >

Salma Kammoun Jarraya^1,2,*, Maha Hamdan Alotibi^1,3, Manar Salamah Ali¹

CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1315-1328, 2021, DOI:10.32604/cmc.2020.013522

Abstract With the emergence of the COVID19 virus in late 2019 and the declaration that the virus is a worldwide pandemic, health organizations and governments have begun to implement severe health precautions to reduce the spread of the virus and preserve human lives. The enforcement of social distancing at work environments and public areas is one of these obligatory precautions. Crowd management is one of the effective measures for social distancing. By reducing the social contacts of individuals, the spread of the disease will be immensely reduced. In this paper, a model for crowd counting in public places of high and… More >

Salman A. Cheema¹, Tanveer Kifayat², Abdu R. Rahman², Umair Khan³, A. Zaib⁴, Ilyas Khan^5,*, Kottakkaran Sooppy Nisar⁶

CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1977-1985, 2021, DOI:10.32604/cmc.2020.012096

Abstract The flow of novel coronavirus (COVID-19) has affected almost every aspect of human life around the globe. Being the emerging ground and early sufferer of the virus, Wuhan city-data remains a case of multifold significance. Further, it is of notable importance to explore the impact of unique and unprecedented public health response of Chinese authorities—the extreme lockdown of the city. In this research, we investigate the statistical nature of the viral transmission concerning social distancing, extreme quarantine, and robust lockdown interventions. We observed highly convincing and statistically significant evidences in favor of quarantine and social distancing approaches. These findings might… More >