The Internet of Things (IoT) plays an important role in various healthcare applications. Radio Frequency IDentification (RFID) is widely used as a leading identification technology in a variety of IoT-health applications. In 2020, the number of cases of novel Corona Virus Disease 2019 ( n COVID-19) was increased rapidly throughout the world. Herein, IoT-Health enables the more convenient ways to access remotely and efficiently the medical services for the patients, also provides health monitoring by the doctors, physicians, and nurses over the Internet. However, security and privacy are considered key concerns in RFID-based IoT-health systems due to wireless communication over the channel. There could be huge risks of leakage of the patient's sensitive information, medical data, privacy of the patients, and so forth. To overcome these shortcomings, we have put forward a secure and reliable RFID authentication protocol using Digital Schnorr Cryptosystem for IoT-Health in COVID-19 patients care named S R 2 AP-DSC. Compared with the similar existing protocols, the security analysis followed by the performance evaluation of our proposed protocol demonstrates the minimal computation overheads and also provides resistance to various well-known security attacks. The AVISPA and Scyther simulation results confirm that the proposed protocol is safe under active and passive attacks. The overall analysis shows that the S R 2 AP-DSC is relatively superior to the other similar existing protocols.
In 2019, a novel type of coronavirus emerged in China called SARS-COV-2, known COVID-19, threatens global health and possesses negative impact on people's quality of life, leading to an urgent need for its diagnosis and remedy. On the other hand, the presence of hazardous infectious waste led to the increase of the risk of transmitting the virus by individuals and by hospitals during the COVID-19 pandemic. Hence, in this review, we survey previous researches on nanomaterials that can be effective for guiding strategies to deal with the current COVID-19 pandemic and also decrease the hazardous infectious waste in the environment. We highlight the contribution of nanomaterials that possess potential to therapy, prevention, detect targeted virus proteins and also can be useful for large population screening, for the development of environmental sensors and filters. Besides, we investigate the possibilities of employing the nanomaterials in antiviral research and treatment development, examining the role of nanomaterials in antiviral- drug design, including the importance of nanomaterials in drug delivery and vaccination, and for the production of medical equipment. Nanomaterials-based technologies not only contribute to the ongoing SARS- CoV-2 research efforts but can also provide platforms and tools for the understanding, protection, detection and treatment of future viral diseases.
The COVID-19 pandemic forced many governments across the world to implement some form of lockdown to minimalize the spread of the virus. On 18th March 2020, the Malaysian government put into action an enforced movement control order (MCO) to reduce the numbers of infections. This study aims to investigate the concentrations of air pollutants during the MCO in the Klang Valley. The concentrations of air pollutants were recorded by the continuous air quality monitoring system (CAQMS) operated by the Department of Environment. The results showed that there were significant reductions (p
Fourth industrial revolution (4IR) technologies have been proved as successful platforms to communicate and visualise construction projects within team meetings. These techniques possibly can enhance compliance with Covid-19 rules on sites. How far concerning Nigerian construction contractors in the use of 4IR technologies are yet to receive in-depth studies. Therefore, this paper offers a collective insight into the issues affecting construction firms from Covid-19 regarding lockdown rules and the role of 4IR technologies. Given the unexplored nature of the problem, a virtual face-to-face type of qualitative research method was employed. Twelve semi-structured interviews from selected construction firms and consultant experts were engaged and collated data analysed via a thematic approach. Findings group the 4IR technologies into smart construction site, simulation and modelling, and digitisation and virtualisation in Nigeria's context, and majority of the 4IR technologies can be useful to enhance Covid-19 compliance. Reluctant to adopt, high implementation cost, inadequate knowledge management, resistance to change, among others emerged as the factors hindering 4IR technologies usage. Findings will strengthen and provide a rich insight into the impact of Covid-19 on construction sites and contribute towards informing key stakeholders to create an enabling environment for the implementation of 4IR technologies on site.
The COVID-19 disease has once again reiterated the impact of pandemics beyond a biomedical event with potential rapid, dramatic, sweeping disruptions to the management, and conduct of everyday life. Not only the rate and pattern of contagion that threaten our sense of healthy living but also the safety measures put in place for containing the spread of the virus may require social distancing. Three different measures to counteract this pandemic situation have emerged, namely: (i) vaccination, (ii) herd immunity development, and (iii) lockdown. As the first measure is not ready at this stage and the second measure is largely considered unreasonable on the account of the gigantic number of fatalities, a vast majority of countries have practiced the third option despite having a potentially immense adverse economic impact. To mitigate such an impact, this paper proposes a data-driven dynamic clustering framework for moderating the adverse economic impact of COVID-19 flare-up. Through an intelligent fusion of healthcare and simulated mobility data, we model lockdown as a clustering problem and design a dynamic clustering algorithm for localized lockdown by taking into account the pandemic, economic and mobility aspects. We then validate the proposed algorithms by conducting extensive simulations using the Malaysian context as a case study. The findings signify the promises of dynamic clustering for lockdown coverage reduction, reduced economic loss, and military unit deployment reduction, as well as assess potential impact of uncooperative civilians on the contamination rate. The outcome of this work is anticipated to pave a way for significantly reducing the severe economic impact of the COVID-19 spreading. Moreover, the idea can be exploited for potentially the next waves of corona virus-related diseases and other upcoming viral life-threatening calamities.