The ongoing pandemic of Corona-Virus (COVID-19) induced by the coming forth category of SARS-CoV-2, has terrified worldwide human health. Primarily, COVID-19 challenges can be categorized into (a) way of epidemic prevention and blocking transmission, (b) live to monitor of infected / suspected persons (c) FDA approved vaccine. Leading to said COVID-19 (a), (b) challenges, digit technologies such Artificial Intelligence, Big data analytics, and Internet of Things (IoT), can play a vital role in epidemic prevention and blocking COVID-19 transmission. In this study, we have proposed a smart edge surveillance system that is effective in remote monitoring, advance warning, and detection of a person’s fever, heartbeat rate, cardiac conditions, and some of the radiological features to detect the infected (suspicious) person using wearable smart gadgets. The proposed framework provides a continually updated map/pattern of the communication chain of COVID-19 infected persons that may span around in our national community. The health and societal impact of suggested research is to help public health authorities, researchers and clinicians contain and manage this disease through smart edge surveillance systems. The proposed model will help to detect and track the contagious person. Moreover, it will also keep the patient’s data record for analysis and decision making using edge computing.
- IoT ,
- Edge Computing ,
- Cloud Computing ,
- Ubiquitous Computing ,
- graph transfusion ,
- Cloud computing ,
- Monitoring ,
- Internet of Things ,
- Artificial intelligence ,
- Diseases ,
- Edge computing ,
- Computer science
The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2; previously provisionally named 2019 novel coronavirus or 2019-nCoV) disease (COVID-19) in China at the end of 2019 has instigated a global outbreak with major public health issues. As per data provided by the World Health Organization (WHO) on 11thFebruary 2020 displayed more than 43000 confirmed cases acknowledged in 28 states/countries, with > 99% of cases being detected in China. On 30 January 2020, the WHO declared COVID-19 as the sixth public health emergency of international concern . According to the World Health Organization (WHO), this epidemic disease is prevailing in the human body up-to 14 days. Furthermore, the even most challenging task, no clear coronavirus (CoVID’19) symptoms observed in its preliminary stages . Therefore, in order to identify the CoVID’19 suspected person, we have to monitor his/her up to 14 days and also ensure to restrict that person in a self-isolation state during the quarantine period. The social distancing, home isolation and home quarantine could slow down the spread of the infection, interrupt transmission and reduce case numbers to low levels . The terminologies like internet of things (IoT) , Edge Computing  and Artificial Intelligence (AI)  taking into account in order to minimize the gigantic effect of this massacre disaster. By adopting these vital concepts, we can trace, monitor and analyze the suspected human-to-human (H2H) chain. This monitoring process could be more efficient by using parallel computing technologies , as well. Moreover, the suspected virus affected person tracking is one of the major issues in the current situation. As, this deadliest virus mostly transfer from H2H, so it is a prime concern of today’s time to keep away the virus affected persons or even suspected to, with the healthy ones. It’s not only the matter of one life or two, but it’s also a concern of the whole universe. So, we need to tackle this issue on a priority basis.
As mentioned above, the solution to this vital issue i.e. ‘H2H’ tracing lies under the phenomenon of IoT and edge computing mechanism . IoT is one of the most effective paradigms in the smart world. Through this concept, we can connect billions of devices with each other with the help of internet architecture under one globe . Moreover, edge computing technology enhances to minimize the overall constraint device’s energy utilization and back up resources. Furthermore, it uses virtual data storing model access anywhere in the world. Instead of storing the whole data on the central cloud, we can make multiple edge servers inside the cloud in order to get a quicker and robust response. Further, it also reduces the overall cloud computation through distributing the tasks among different edge, fog levels, which is the main beauty of this architecture . The health and societal impact of our research is to help public health authorities, researchers and clinicians contain and manage this disease by developing smart edge surveillance systems. Our intended research solution is five step tracking and monitoring surveillance system for disease suspected persons through which we analyze the person basic CoVID’19 preliminary symptoms right from the start of travel journey to reach the required destination along with highlighting each and every suspected person checkpoints during his/her voyage. The system is equipped with a wearable smart product (gadget) that is effective in remote monitoring, advance warning and detection of wearing person’s fever, heart beat rate, cardiac conditions and some of the radiological features to detect the disease infected person or suspicious ones.
Research outcomes of this project will provide a continually updated map/pattern of communication chain of infected persons for COVID-19 that may span around in our national community. It would make a significant contribution in better understanding of epidemics, patterns of spread and developing diagnostics. The rest of the paper organized as follows: Section II introduces literature study. Methodology and system components are presented in section III. Section IV presents a comprehensive future perspective plan. Lastly we conclude the study in section V.
While in 2020, the world continues to rely on classic public-health measures for undertaking the COVID-19 pandemic, a variety of digital technology is available that can be utilized to enhance worldwide human health strategies. In order to overcome COVID-19 pandemic challenges through digital technologies, current study propose a novel smart edge surveillance system which is capable to (a) diagnose coronavirus infection in human body with the help of health monitoring gadget, (b) recognize the virus suspected H2H chain with the help of deep edge computing and IoT and (c) monitor the suspected person live tracking through Application. The proposed model also provides a recommendation and alert mechanism module to secure healthy persons whenever an infected/suspected person enters in any public place. Leading to these concerns, we have presented proposed framework as well as layered architecture of the system. The health and societal impact of suggested research is to help public health authorities, researchers and clinicians contain and manage this disease through smart edge surveillance systems. From future perspectives, we will develop two sensor modules categorized as wearable and non-wearable modules to get real-time CoVID’19 suspected medical health parameters. An initial experimental setup of these gadgets has been proposed in this research. Moreover, we will develop a communication mechanism with the edge and cloud layers. We also need to consider the adoption of two viral technologies in current time i.e. IoT and Edge computing, to develop a hybrid mechanism that will detect and track the suspected CoVID’19 victims. While working on proposed model in future, security and privacy will also be the major concerns that can be addressed by using advance techniques .
The Kavian Scientific Research Association (KSRA) is a non-profit research organization to provide research / educational services in December 2013. The members of the community had formed a virtual group on the Viber social network. The core of the Kavian Scientific Association was formed with these members as founders. These individuals, led by Professor Siavosh Kaviani, decided to launch a scientific / research association with an emphasis on education.
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FULL Paper PDF file:Detection and Tracking Contagion using IoT-Edge Technologies: Confronting COVID-19 Pandemic
Detection and Tracking Contagion using IoT-Edge Technologies: Confronting COVID-19 Pandemic
Confronting COVID-19 Pandemic,” 2020 International Conference on Electrical, Communication, and Computer Engineering (ICECCE), Istanbul, Turkey, 2020, pp. 1-6,
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Professor Siavosh Kaviani was born in 1961 in Tehran. He had a professorship. He holds a Ph.D. in Software Engineering from the QL University of Software Development Methodology and an honorary Ph.D. from the University of Chelsea.