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Shapira S, Cauchard JR. Integrating drones in response to public health emergencies: A combined framework to explore technology acceptance. Front Public Health 2022; 10:1019626. [PMID: 36388358 PMCID: PMC9650287 DOI: 10.3389/fpubh.2022.1019626] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Accepted: 10/10/2022] [Indexed: 01/28/2023] Open
Abstract
The aim of the study was to propose and test an integrated model combining the technology acceptance model (TAM), task-technology fit (TTF), social motivation, and drone-related perceived risks to explore the intention to use drones in public health emergencies (PHEs). We conducted a survey among the Israeli population, yielding a sample of 568 participants. Structural equation modeling was implemented to test the research hypotheses. The results showed that our integrated model provided a robust and comprehensive framework to perform an in-depth investigation of the factors and mechanisms affecting drone acceptance in PHEs. First, ease of use, attitudes, individual-technology fit, task-technology fit, and social influence significantly and directly influenced users' behavioral intention to utilize drone technology. Second, attitudes were significant mediators of the effects of social influence and perceived risks on the intention to use drones. Finally, significant relationships between TAM, TTF, social motivation, and perceived risks were also observed. Theoretical aspects and practical implications-which can serve as the basis for shaping a positive development in drone public acceptance in PHEs and in general-are discussed.
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Affiliation(s)
- Stav Shapira
- School of Public Health, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer Sheva, Israel
| | - Jessica R. Cauchard
- Magic Lab, Department of Industrial Engineering and Management, Faculty of Engineering, Ben-Gurion University of the Negev, Beer Sheva, Israel
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Mohsan SAH, Zahra QUA, Khan MA, Alsharif MH, Elhaty IA, Jahid A. Role of Drone Technology Helping in Alleviating the COVID-19 Pandemic. MICROMACHINES 2022; 13:1593. [PMID: 36295946 PMCID: PMC9612140 DOI: 10.3390/mi13101593] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/21/2022] [Revised: 09/18/2022] [Accepted: 09/22/2022] [Indexed: 06/16/2023]
Abstract
The COVID-19 pandemic, caused by a new coronavirus, has affected economic and social standards as governments and healthcare regulatory agencies throughout the world expressed worry and explored harsh preventative measures to counteract the disease's spread and intensity. Several academics and experts are primarily concerned with halting the continuous spread of the unique virus. Social separation, the closing of borders, the avoidance of big gatherings, contactless transit, and quarantine are important methods. Multiple nations employ autonomous, digital, wireless, and other promising technologies to tackle this coronary pneumonia. This research examines a number of potential technologies, including unmanned aerial vehicles (UAVs), artificial intelligence (AI), blockchain, deep learning (DL), the Internet of Things (IoT), edge computing, and virtual reality (VR), in an effort to mitigate the danger of COVID-19. Due to their ability to transport food and medical supplies to a specific location, UAVs are currently being utilized as an innovative method to combat this illness. This research intends to examine the possibilities of UAVs in the context of the COVID-19 pandemic from several angles. UAVs offer intriguing options for delivering medical supplies, spraying disinfectants, broadcasting communications, conducting surveillance, inspecting, and screening patients for infection. This article examines the use of drones in healthcare as well as the advantages and disadvantages of strict adoption. Finally, challenges, opportunities, and future work are discussed to assist in adopting drone technology to tackle COVID-19-like diseases.
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Affiliation(s)
- Syed Agha Hassnain Mohsan
- Optical Communications Laboratory, Ocean College, Zhejiang University, Zheda Road 1, Zhoushan 316021, China
| | - Qurat ul Ain Zahra
- Department of Biomedical Engineering, Biomedical Imaging Centre, University of Science and Technology of China, Hefei 230009, China
| | - Muhammad Asghar Khan
- Department of Electrical Engineering, Hamdard Institute of Engineering & Technology, Islamabad 44000, Pakistan
| | - Mohammed H. Alsharif
- Department of Electrical Engineering, College of Electronics and Information Engineering, Sejong University, Seoul 05006, Korea
| | - Ismail A. Elhaty
- Department of Nutrition and Dietetics, Faculty of Health Sciences, Istanbul Gelisim University, Istanbul P.O. Box 34310, Turkey
| | - Abu Jahid
- School of Electrical Engineering and Computer Science, University of Ottawa, 25 Templeton St., Ottawa, ON K1N 6N5, Canada
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Using postal change-of-address data to predict second waves in infections near pandemic epicentres. Epidemiol Infect 2022; 150:e120. [PMID: 35321775 PMCID: PMC9254154 DOI: 10.1017/s0950268822000486] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023] Open
Abstract
We propose that postal Change-of-Address (CoA) data can be used to monitor/predict likely second wave caseloads in viral infections around urban epicentres. To illustrate the idea, we focus on the tri-state area consisting of New York City (NYC) and surrounding counties in New York, New Jersey and Connecticut States. NYC was an early epicentre of the coronavirus disease 2019 (Covid-19) pandemic, with a first peak in daily cases in early April 2020, followed by the second peak in May/June 2020. Using CoA data from the US Postal Service (USPS), we show that, despite a quarantine mandate, there was a large net movement of households from NYC to surrounding counties in the period April-June 2020. This net outward migration of households was strongly correlated with both the timing and the number of cases in the second peaks in Covid-19 cases in the surrounding counties. The timing of the second peak was also correlated with the distance of the county from NYC, suggesting that this was a directed flow and not random diffusion. Our analysis shows that CoA data is a useful method in tracking the spread of an infectious pandemic agent from urban epicentres.
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Internet of Things-based smart helmet to detect possible COVID-19 infections. CYBER-PHYSICAL SYSTEMS 2022. [PMCID: PMC9261912 DOI: 10.1016/b978-0-12-824557-6.00004-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
At the beginning of 2020, while the world was celebrating New Year’s Eve, China’s headquarter of the World Health Organization came across a case of pneumonia in the city of Wuhan, China and was termed as coronavirus. Initially the symptoms were fever, cold, and cough; so thermal screening was done that could cause infection to the medical staff. In this chapter we discuss the design of the system known as smart helmet that has the capability to detect coronavirus automatically by using thermal imaging, which is used to capture the image with less human interaction. The thermal camera technology is integrated with smart helmets and combined with Internet of Things technology for monitoring of the screening process to get the real-time data. It is equipped with facial recognition technology; it can also display personal information of the infectee, which can automatically take temperature and can detect more infectee than normal thermal screening.
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Angurala M, Bala M, Singh Bamber S. Implementing MRCRLB technique on modulation schemes in wireless rechargeable sensor networks. EGYPTIAN INFORMATICS JOURNAL 2021. [DOI: 10.1016/j.eij.2021.03.002] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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Mukati N, Namdev N, Dilip R, Hemalatha N, Dhiman V, Sahu B. Healthcare assistance to COVID-19 patient using internet of things (IoT) enabled technologies. ACTA ACUST UNITED AC 2021; 80:3777-3781. [PMID: 34336599 PMCID: PMC8302836 DOI: 10.1016/j.matpr.2021.07.379] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2021] [Accepted: 07/17/2021] [Indexed: 11/17/2022]
Abstract
The IoT can lead to disruptive healthcare innovation. Research articles on IoT in healthcare and COVID-19 pandemics are thus researched in order to discover the potential of this technology. This literature-based research may help professionals to explore solutions to associated issues and battle the COVID-19 epidemic. Using a process diagram, IoT's significant accomplishments were briefly evaluated. Then seven critical IoT technologies that look useful in healthcare during the COVID-19 Pandemic are identified and illustrated. Finally, in the COVID-19 Pandemic, potential fundamental IoT applications were identified for the medical industry with a short explanation. The present predicament has opened up a fresh avenue to creativity in our everyday lives. The Internet of Things is an up-and-coming technology that enhances and gives better solutions in the medical area, such as appropriate medical record-keeping, sample, device integration, and cause of sickness. IoT's sensor-based technology gives a remarkable ability to lower the danger of intervention in challenging circumstances and is helpful for the pandemic type COVID-19. In the sphere of medicine, IoT's emphasis is on helping to treat diverse COVID-19 situations accurately. It facilitates the work of the surgeon by reducing risks and enhancing overall performance. Using this technology, physicians may readily identify changes in the COVID-19′s vital parameters. These information-based services provide new prospects for healthcare as they advance towards the ideal technique for an information system to adapt world-class outcomes by improving hospital treatment systems. Medical students may now be better taught and led in the future for the identification of sickness. Proper use of IoT may assist handle several medical difficulties such as speed, affordability, and complexity appropriately. It may simply be adapted to track patients' calorific intake and therapy with COVID-19 asthma, diabetes, and arthritis. In COVID-19 pandemic days, this digitally managed health management system may enhance the overall healthcare performance.
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Affiliation(s)
- Naveen Mukati
- Department of Electronics and Communication Engineering, Prestige Institute of Engineering Management and Research, Indore, India
| | - Neha Namdev
- Department of Electronics and Instrumentation Engineering, Shri Govindram Seksaria Institute of Technology and Science, Indore, India
| | - R Dilip
- Acharya Institute of Technology, Department of Mechatronics Engineering, Bengaluru, India
| | - N Hemalatha
- Saveetha School Of Engineering(Simats), Chennai, India
| | - Viney Dhiman
- Postgraduate Institute of Medical Education and Research, Chandigarh, India
| | - Bharti Sahu
- Department of Computer Engineering, Dr. D.Y. Patil Institute of Technology, Pimpri, Pune18, India
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Patel P, Gohil P. Role of additive manufacturing in medical application COVID-19 scenario: India case study. JOURNAL OF MANUFACTURING SYSTEMS 2021; 60:811-822. [PMID: 33204048 PMCID: PMC7659810 DOI: 10.1016/j.jmsy.2020.11.006] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/07/2020] [Revised: 11/09/2020] [Accepted: 11/09/2020] [Indexed: 05/17/2023]
Abstract
This paper reviews how the Additive Manufacturing (AM) industry played a key role in stopping the spread of the Coronavirus by providing customized parts on-demand quickly and locally, reducing waste and eliminating the need for an extensive manufacturer. The AM technology uses digital files for the production of crucial medical parts, which has been proven essential during the COVID-19 crisis. Going ahead, the 3D printable clinical model resources described here will probably be extended in various centralized model storehouses with new inventive open-source models. Government agencies, individuals, corporations and universities are working together to quickly development of various 3D-printed products especially when established supply chains are under distress, and supply cannot keep up with demand.
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Affiliation(s)
- Piyush Patel
- Mechanical Engineering Department, Faculty of Technology and Engineering, M.S. University, Baroda, 390001, Gujarat, India
| | - Piyush Gohil
- Mechanical Engineering Department, Faculty of Technology and Engineering, Maharaja Sayajirao University of Baroda, Gujarat, India
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Kumar V, Singh D, Kaur M, Damaševičius R. Overview of current state of research on the application of artificial intelligence techniques for COVID-19. PeerJ Comput Sci 2021; 7:e564. [PMID: 34141890 PMCID: PMC8176528 DOI: 10.7717/peerj-cs.564] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2020] [Accepted: 05/05/2021] [Indexed: 05/09/2023]
Abstract
BACKGROUND Until now, there are still a limited number of resources available to predict and diagnose COVID-19 disease. The design of novel drug-drug interaction for COVID-19 patients is an open area of research. Also, the development of the COVID-19 rapid testing kits is still a challenging task. METHODOLOGY This review focuses on two prime challenges caused by urgent needs to effectively address the challenges of the COVID-19 pandemic, i.e., the development of COVID-19 classification tools and drug discovery models for COVID-19 infected patients with the help of artificial intelligence (AI) based techniques such as machine learning and deep learning models. RESULTS In this paper, various AI-based techniques are studied and evaluated by the means of applying these techniques for the prediction and diagnosis of COVID-19 disease. This study provides recommendations for future research and facilitates knowledge collection and formation on the application of the AI techniques for dealing with the COVID-19 epidemic and its consequences. CONCLUSIONS The AI techniques can be an effective tool to tackle the epidemic caused by COVID-19. These may be utilized in four main fields such as prediction, diagnosis, drug design, and analyzing social implications for COVID-19 infected patients.
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Affiliation(s)
- Vijay Kumar
- Computer Science and Engineering Department, National Institute of Technology, Hamirpur, Himachal Pradesh, India
| | - Dilbag Singh
- School of Engineering and Applied Sciences, Bennett University, Greater Noida, India
| | - Manjit Kaur
- School of Engineering and Applied Sciences, Bennett University, Greater Noida, India
| | - Robertas Damaševičius
- Faculty of Applied Mathematics, Silesian University of Technology, Gliwice, Poland
- Department of Applied Informatics, Vytautas Magnus University, Kaunas, Lithuania
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Singh PD, Kaur R, Singh KD, Dhiman G. A Novel Ensemble-based Classifier for Detecting the COVID-19 Disease for Infected Patients. INFORMATION SYSTEMS FRONTIERS : A JOURNAL OF RESEARCH AND INNOVATION 2021; 23:1385-1401. [PMID: 33935584 PMCID: PMC8068562 DOI: 10.1007/s10796-021-10132-w] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 03/30/2021] [Indexed: 05/02/2023]
Abstract
The recently discovered coronavirus, SARS-CoV-2, which was detected in Wuhan, China, has spread worldwide and is still being studied at the end of 2019. Detection of COVID-19 at an early stage is essential to provide adequate healthcare to affected patients and protect the uninfected community. This paper aims to design and develop a novel ensemble-based classifier to predict COVID-19 cases at a very early stage so that appropriate action can be taken by patients, doctors, health organizations, and the government. In this paper, a synthetic dataset of COVID-19 is generated by a dataset generation algorithm. A novel ensemble-based classifier of machine learning is employed on the COVID-19 dataset to predict the disease. A convex hull-based approach is also applied to the data to improve the proposed novel, ensemble-based classifier's accuracy and speed. The model is designed and developed through the python programming language and compares with the most popular classifier, i.e., Decision Tree, ID3, and support vector machine. The results indicate that the proposed novel classifier provides a more significant precision, kappa static, root means a square error, recall, F-measure, and accuracy.
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Affiliation(s)
- Prabh Deep Singh
- Department of Computer Science & Engineering, Punjabi University, Patiala, Punjab India
| | - Rajbir Kaur
- Department of Electronics & Communication Engineering, Punjabi University, Patiala, Punjab India
| | - Kiran Deep Singh
- Department of Computer Science & Engineering, IKG Punjab Technical University, Punjab, India
| | - Gaurav Dhiman
- Department of Computer Science, Government Bikram College of Commerce, Punjabi University, Patiala, Punjab India
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Drone Assisted Robust Emergency Service Management for Elderly Chronic Disease. JOURNAL OF HEALTHCARE ENGINEERING 2021; 2021:5552350. [PMID: 33897990 PMCID: PMC8052162 DOI: 10.1155/2021/5552350] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/06/2021] [Revised: 03/10/2021] [Accepted: 03/25/2021] [Indexed: 11/25/2022]
Abstract
It is important to monitor the early screening of chronic diseases, predict the risk, and provide the comprehensive management of chronic diseases for the elderly. However, it is difficult to provide the robust and real-time emergency service for elderly chronic disease because of the complex social network and diversity of elderly chronic disease service. To address these issues, we design a new drone assisted robust emergency service system. We formulate the Drone assisted Management (DM) problem to minimize the total time cost of drone subject to all elderly chronic disease services which can be guaranteed exactly once by the drone under its energy constraint. Then, we propose the DRS algorithm to solve the DM problem. To provide the robust and real-time service, we further formulate the Charging driven Drone assisted Management (CDM) problem and present the CDRS algorithm to solve the CDM problem. Through the theoretical analysis and numerical simulation experiments, we demonstrate that DRS and CDRS can decrease the total time cost by 37.61% and increase the QoE by 112.80% through the designed system, respectively.
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Javaid M, Khan IH. Internet of Things (IoT) enabled healthcare helps to take the challenges of COVID-19 Pandemic. J Oral Biol Craniofac Res 2021; 11:209-214. [PMID: 33665069 PMCID: PMC7897999 DOI: 10.1016/j.jobcr.2021.01.015] [Citation(s) in RCA: 53] [Impact Index Per Article: 17.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/25/2020] [Accepted: 01/23/2021] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND/OBJECTIVES The Internet of Things (IoT) can create disruptive innovation in healthcare. Thus, during COVID-19 Pandemic, there is a need to study different applications of IoT enabled healthcare. For this, a brief study is required for research directions. METHODS Research papers on IoT in healthcare and COVID-19 Pandemic are studied to identify this technology's capabilities. This literature-based study may guide professionals in envisaging solutions to related problems and fighting against the COVID-19 type pandemic. RESULTS Briefly studied the significant achievements of IoT with the help of a process chart. Then identifies seven major technologies of IoT that seem helpful for healthcare during COVID-19 Pandemic. Finally, the study identifies sixteen basic IoT applications for the medical field during the COVID-19 Pandemic with a brief description of them. CONCLUSIONS In the current scenario, advanced information technologies have opened a new door to innovation in our daily lives. Out of these information technologies, the Internet of Things is an emerging technology that provides enhancement and better solutions in the medical field, like proper medical record-keeping, sampling, integration of devices, and causes of diseases. IoT's sensor-based technology provides an excellent capability to reduce the risk of surgery during complicated cases and helpful for COVID-19 type pandemic. In the medical field, IoT's focus is to help perform the treatment of different COVID-19 cases precisely. It makes the surgeon job easier by minimising risks and increasing the overall performance. By using this technology, doctors can easily detect changes in critical parameters of the COVID-19 patient. This information-based service opens up new healthcare opportunities as it moves towards the best way of an information system to adapt world-class results as it enables improvement of treatment systems in the hospital. Medical students can now be better trained for disease detection and well guided for the future course of action. IoT's proper usage can help correctly resolve different medical challenges like speed, price, and complexity. It can easily be customised to monitor calorific intake and treatment like asthma, diabetes, and arthritis of the COVID-19 patient. This digitally controlled health management system can improve the overall performance of healthcare during COVID-19 pandemic days.
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Affiliation(s)
- Mohd Javaid
- Department of Mechanical Engineering, Jamia Millia Islamia, New Delhi, India
| | - Ibrahim Haleem Khan
- School of Engineering Sciences and Technology, Jamia Hamdard, New Delhi, India
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Singh P, Kaur R. An integrated fog and Artificial Intelligence smart health framework to predict and prevent COVID-19. GLOBAL TRANSITIONS 2020; 2:283-292. [PMID: 33205037 PMCID: PMC7659515 DOI: 10.1016/j.glt.2020.11.002] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/04/2020] [Revised: 10/09/2020] [Accepted: 11/01/2020] [Indexed: 05/18/2023]
Abstract
Nowadays, COVID-19 is spreading at a rapid rate in almost all the continents of the world. It has already affected many people who are further spreading it day by day. Hence, it is the most essential to alert nearby people to be aware of it due to its communicable behavior. Till May 2020, no vaccine is available for the treatment of this COVID-19, but the existing technologies can be used to minimize its effect. Cloud/fog computing could be used to monitor and control this rapidly spreading infection in a cost-effective and time-saving manner. To strengthen COVID-19 patient prediction, Artificial Intelligence(AI) can be integrated with cloud/fog computing for practical solutions. In this paper, fog assisted the internet of things based quality of service framework is presented to prevent and protect from COVID-19. It provides real-time processing of users' health data to predict the COVID-19 infection by observing their symptoms and immediately generates an emergency alert, medical reports, and significant precautions to the user, their guardian as well as doctors/experts. It collects sensitive information from the hospitals/quarantine shelters through the patient IoT devices for taking necessary actions/decisions. Further, it generates an alert message to the government health agencies for controlling the outbreak of chronic illness and for tanking quick and timely actions.
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Affiliation(s)
- Prabhdeep Singh
- Department of Computer Science & Engineering, Punjabi University, Patiala, IN, India
| | - Rajbir Kaur
- Department of Electronics & Communication Engineering, Punjabi University, Patiala, IN, India
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