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Ghosh S, Dave V, Sharma P, Patel A, Kuila A. Protective face mask: an effective weapon against SARS-CoV-2 with controlled environmental pollution. Environ Sci Pollut Res Int 2023:10.1007/s11356-023-30460-5. [PMID: 37968481 DOI: 10.1007/s11356-023-30460-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/04/2023] [Accepted: 10/10/2023] [Indexed: 11/17/2023]
Abstract
Masks are face coverings that give protection from infectious agents, airborne pathogens, bacteria, viruses, surgical fog, dust, and other chemical hazards by acting as a barrier between the wearer and the environment. In the COVID-19 pandemic, this major personal protective equipment's became essential part of our daily life. The aim of this review is to analyze and discuss the different types of masks with their pros and cons, manufacturing procedures, evaluation criteria, and application with some of the sterilization process for reuse and smart mask. The review used a thorough examination of the literature to analyze the preventive effects of surgical, N95, smart mask, and potential environmental damage from those masks. Several studies and evidence were also examined to understand the efficiency of different mask on different environment. N95 respirators are capable of filtering out non-oil-based 95% air-born particles, and surgical masks act as a protective barrier between the wearer and the environment. The application of spoon bond and melt blown techniques in the fabrication process of those masks improves their protective nature and makes them lightweight and comfortable. But the high demand and low supply forced users to reuse and extend their use after sterilizations, even though those masks are recommended to be used once. Universal masking in the SARS-COV-2 pandemic increased the chance of environmental pollution, so the application of smart masks became essential because of their high protection power and self-sterilizing and reusing capabilities.
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Affiliation(s)
- Shovan Ghosh
- Department of Pharmacy, School of Health Science, Central University of South Bihar, Bihar, India
| | - Vivek Dave
- Department of Pharmacy, School of Health Science, Central University of South Bihar, Bihar, India.
| | - Prashansa Sharma
- Department of Home Science, Mahila Maha Vidyalaya, Banaras Hindu University, Varanasi, India
| | - Akash Patel
- Department of Pharmacy, School of Health Science, Central University of South Bihar, Bihar, India
| | - Arindam Kuila
- Department of Bioscience and Biotechnology, Banasthali Vidyapith, Sikar, Rajasthan, 304022, India
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Mekid S, Chenaoua K. IoT-enabled smart mask for monitoring body parameters and location through cloud. Internet Things (Amst) 2023; 22:100794. [PMID: 37266184 PMCID: PMC10121153 DOI: 10.1016/j.iot.2023.100794] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/03/2023]
Abstract
In the last interim guidance, the WHO advised the use of masks in communities, during home care, and in healthcare settings in areas with reported cases of COVID-19. This advice was intended for individuals in the community, public health and infection prevention and control (IPC) professionals, healthcare managers, healthcare workers (HCWs), and community health workers. As the two primary routes of transmission of the COVID-19 virus are respiratory droplets and contact, face masks have become potential safety tools in public places. Subsequent contact with the face, eyes, nose, and mouth following contamination is detrimental. However, during this pandemic, physicians and nurses have suffered the consequences of wearing face masks for several hours. Therefore. a full-face mark, which ensures filtered breathing during the day, is critical. The proposed smart mask model protects the respiration of mask wearers and monitors their body temperature, sneezing attacks, and social distancing. Moreover, it registers their geographical location after ensuring ID registration. The proposed mask can be used both indoors and outdoors. Moreover, data can be processed locally for alarms related to temperature and social distancing. The remaining data are sent to a cloud for post-processing to record the histories of mask wearers in all parameters, including their geographical dynamic location, to track the possible spread of contamination. The prototype and measurement results demonstrate the practicality and potential utility of mass numbers.
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Affiliation(s)
- S Mekid
- Department of Mechanical Engineering, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia
- Interdisciplinary Research Center for Intelligent Manufacturing and Robotics, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia
| | - K Chenaoua
- Department of Computer Engineering, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia
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Goar V, Sharma A, Yadav NS, Chowdhury S, Hu YC. IoT-Based Smart Mask Protection against the Waves of COVID-19. J Ambient Intell Humaniz Comput 2022; 14:1-12. [PMID: 36117515 PMCID: PMC9466323 DOI: 10.1007/s12652-022-04395-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/19/2021] [Accepted: 08/30/2022] [Indexed: 06/15/2023]
Abstract
In the year 2020, the word "pandemic" has become quite popular. A pandemic is a disease that spreads over a wide geographical region. The massive outbreak of coronavirus popularly known as COVID-19 has halted normal life worldwide. On 11th March 2020, the World Health Organization (WHO) quoted the COVID-19 outbreak as a "Pandemic". The outbreak pattern differs widely across the globe based on the findings discovered so far; however, fever is a common and easily detectable symptom of COVID-19 and the new COVID strain. After the virus outbreak, thermal scanning is done using infrared thermometers in most public places to detect infected persons. It is time-consuming to track the body temperature of each person. Besides, close contact with infected persons can spread the virus from the infected persons to the individual performing the screening or vice-versa. In this research, we propose a device architecture capable of automatically detecting the coronavirus or new COVID strain from thermal images; the proposed architecture comprises a smart mask equipped with a thermal imaging system, which reduces human interactions. The thermal camera technology is integrated with the smart mask powered by the Internet of Things (IoT) to proactively monitor the screening procedure and obtain data based on real-time findings. Besides, the proposed system is fitted with facial recognition technology; therefore, it can also display personal information. It will automatically measure the temperature of each person who came into close contact with the infected humans or humans in public spaces, such as markets or offices. The new design is very useful in healthcare and could offer a solution to preventing the growth of the coronavirus. The presented work hasa key focus on the integration of advanced algorithms for the predictive analytics of parameters required for in-depth evaluations. The proposed work and the results are pretty effectual and performance cognizant for predictive analytics. The manuscript and associated research work integrate the IoT and Internet of Everything (IoE) based analytics with sensor technologies with real-time data so that the overall predictions will be more accurate and integrated with the health sector. Supplementary Information The online version contains supplementary material available at 10.1007/s12652-022-04395-7.
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Affiliation(s)
- Vishal Goar
- Govt. Engineering College Bikaner, Bikaner, Rajasthan India
| | - Aditi Sharma
- Department of Computer Science and Engineering, Parul Institute of Technology, Parul University, Vadodara, Gujarat India
| | | | - Subrata Chowdhury
- Department of Computer Science & Applications, SVCET Engineering College, Chittoor, Andra Pradesh India
| | - Yu-Chen Hu
- Department of Computer Science and Information Management, Providence University, 200, Sec. 7, Taiwan Boulevard, Shalu Dist, 43301 Taichung City, Taiwan, R.O.C
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Jin Z, Mantri Y, Retout M, Cheng Y, Zhou J, Jorns A, Fajtova P, Yim W, Moore C, Xu M, Creyer MN, Borum RM, Zhou J, Wu Z, He T, Penny WF, O’Donoghue A, Jokerst JV. A Charge-Switchable Zwitterionic Peptide for Rapid Detection of SARS-CoV-2 Main Protease. Angew Chem Int Ed Engl 2022; 61:e202112995. [PMID: 34936725 PMCID: PMC8854333 DOI: 10.1002/anie.202112995] [Citation(s) in RCA: 37] [Impact Index Per Article: 18.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2021] [Indexed: 11/06/2022]
Abstract
The transmission of SARS-CoV-2 coronavirus has led to the COVID-19 pandemic. Nucleic acid testing while specific has limitations for mass surveillance. One alternative is the main protease (Mpro ) due to its functional importance in mediating the viral life cycle. Here, we describe a combination of modular substrate and gold colloids to detect Mpro via visual readout. The strategy involves zwitterionic peptide that carries opposite charges at the C-/N-terminus to exploit the specific recognition by Mpro . Autolytic cleavage releases a positively charged moiety that assembles the nanoparticles with rapid color changes (t<10 min). We determine a limit of detection for Mpro in breath condensate matrices <10 nM. We further assayed ten COVID-negative subjects and found no false-positive result. In the light of simplicity, our test for viral protease is not limited to an equipped laboratory, but also is amenable to integrating as portable point-of-care devices including those on face-coverings.
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Affiliation(s)
- Zhicheng Jin
- Department of NanoEngineering, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA
| | - Yash Mantri
- Department of Bioengineering, University of California San Diego, 9500 Gilman Drive, La Jolla, California 92093, USA
| | - Maurice Retout
- Department of NanoEngineering, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA
| | - Yong Cheng
- Department of NanoEngineering, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA
| | - Jiajing Zhou
- Department of NanoEngineering, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA
| | - Alec Jorns
- Department of NanoEngineering, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA
| | - Pavla Fajtova
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, 9500 Gilman Drive, La Jolla, California 92093, USA
| | - Wonjun Yim
- Materials Science and Engineering Program, University of California San Diego, 9500 Gilman Drive, La Jolla, California 92093, USA
| | - Colman Moore
- Department of NanoEngineering, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA
| | - Ming Xu
- Department of NanoEngineering, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA
| | - Matthew N. Creyer
- Department of NanoEngineering, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA
| | - Raina M. Borum
- Department of NanoEngineering, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA
| | - Jingcheng Zhou
- Department of NanoEngineering, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA
| | - Zhuohong Wu
- Department of NanoEngineering, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA
| | - Tengyu He
- Materials Science and Engineering Program, University of California San Diego, 9500 Gilman Drive, La Jolla, California 92093, USA
| | - William F. Penny
- Department of Medicine, University of California San Diego, 9500 Gilman Drive, La Jolla, California 92093, USA
| | - Anthony O’Donoghue
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, 9500 Gilman Drive, La Jolla, California 92093, USA
| | - Jesse V. Jokerst
- Department of NanoEngineering, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA
- Materials Science and Engineering Program, University of California San Diego, 9500 Gilman Drive, La Jolla, California 92093, USA
- Department of Radiology, University of California San Diego, 9500 Gilman Drive, La Jolla, California 92093, USA
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