Enabling Healthcare 4.0 for Pandemics. Группа авторов
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country in the production of complex tools to deal with COVID-19 [32]. In France, the PSA group has teamed up with Valeo, Schneider Electric and Air Liquide for the production of the ventilators [33]. In Spain, cars manufacture SEAT in record time, just one week, reshaped for the fabrication of ventilators, and PPE. In the UK this practice in large companies, Airbus, Dyson, Ford and Rolls-Royce that are pooling their resources and reconfigure the production line for the production of 30 thousand of ventilators. Similar practices took over in industrialized countries of the world. Important is that business and government combine their efforts to maximize the use of national productive resources to combat COVID-19 and to stimulate economic activity of domestic manufacturers in conditions of economic crisis.
The reaction of the digital communities was quite similar—within 1–2 months we saw the flow of new products, projects and solutions to explore COVID-19 pandemic involving Big Data, neural networks, the possibility of AI [7]. In the framework of prevention, early diagnosis and monitoring COVID-19, coordinating scale and managing data necessary for implementing such strategies effectively in the highly successful countries dependent upon the integration of digital technologies in system health [34]. Thanks to the technology of AI, the IoT, augmented and virtual reality (AR/VR), capabilities of ML and Data Science, digital neural networks (DNN), and biotechnology, mankind has reached a new level of digital age with a new set of possibilities [35, 36].
Processing a large amount of information from the interconnected IoT devices has made possible the emergence of intelligent networks for proper health management systems, individually or collectively. This network monitors and prevents any types of diseases to improve patient safety. Without requiring human intervention, in language of facts it records data and information about the patient and starts the process of making solutions. Since in a pandemic, there is a great need to use appropriate and organized medical events, using the concept of IoT makes medical care more accessible to patients. Thanks to the technology of IoT, the patient can monitor glucometer data, blood pressure, heart rate, or online consulting with a doctor. An important application of this technology in the field of health is tracking sites for medical instruments and devices timely for robust management. This would enhance effectively the workflow of patient management and also useful for making decision in difficult conditions [37].
Efficiently working through big data, AI helped to simplify tracking people infected with COVID-19. Detecting the level of infection of this virus requires not only finding the accumulation “hot spots”, but also predicting the spread of infection and the risk of complications associated with COVID-19 for people of different ages, and with different comorbid pathology. Using such algorithms, all countries have taken necessary measures to halt COVID-19 transmission, especially among vulnerable societal groups. Such tools as maps of migration that use mobile phones, applications for social media and mobile payments to gather data timely on the whereabouts of individuals helped to build a novel system for the detecting and treating cases of COVID-19, providing faster decision-making, which is economically advantageous. Special technology based on AI is able to recognize and remove false information about COVID-19 in the Internet and social platforms.
Thanks to the technology of AI, scientists have learned more about the nature of the virus, its characteristics and use it to develop vaccines and drugs to combat this disease. Scientists have turned to AI technology and IoT to optimize the procedure of the study drugs for managing COVID-19 patients. These technologies, together with DNN and ML capabilities can quickly and efficiently process the huge data to speed-up the process of testing vaccines and medicines developed by the samples in real-time.
2.4 Opportunities and Limitations
HCS 4.0 techniques would offer innovative digital interventions during everyday living in the crisis [38]. For example, evaluating risk worldwide, planning public health emergency actions against COVID-19, producing the protective equipment and delivering timely medical supplies via the intelligent supply chain, using robots in caring for infected patients and reducing the risk of exposure to infection among healthcare providers, training staff using virtual reality, supporting more adaptable healthcare setting, performing everyday living activities in the lockdown, and detecting misinformation in the different media channels [6].
The speed and scale of the COVID-19 pandemic is more or less ahead of the health systems of all countries. Diagnosing, maintaining, treating, and tracking people with suspected infections has become physically difficult because existing healthcare systems based on a historically necessary model of interaction between patients and their physicians have facilitated viral transmission. Globally, several governments have realized the need of an immediate digital revolution to counter this. Therefore, countries around the world have had to take steps to transform healthcare and expand it through the power of digital technology. Unfortunately, even in the developed world, where telemedicine has existed for decades, it has had a weak penetration of the services market, due to rigid, unresolved regulatory mechanisms. With the advent of the pandemic of COVID-19, several countries, including the US, repealed all provisions restricting remote and telemedicine services and began to actively implement it in healthcare.
In turn, prolonged and improper use of various trackers and mobile applications for smartphones can cause users side effects such as neck pain, elbows, upper back, shoulder girdle, and numbness in both fingers and hands. It is worth noting that long-term use of smartphones contributes to the development of a specific syndrome of “Text neck”, which is accompanied by pain and curvature in the cervical spine. In addition, long-term use of smartphones and tablets contributes to the appearance of such unpleasant phenomena as: “smartphone”, “selfie-wrist”, “self-elbow”, “computer hump”. “Click finger”, “Cell phone-elbow”.
The development of tools for prevention, early diagnosis and forecasting based on the use of DL and ML with the involvement of IoT technologies and AI requires a huge amount of quality data. The key word—Quality! In order for these technologies to be able to generate qualitative conclusions, they must learn from qualitative and sufficient examples. After all, bad results would be obtained while training models on non-representative data. Unfortunately, data sets of medical images and textual analysis are limited in comparison to the needs of in-depth training. Many of them are not digitized in real time, or contain errors. The key cause of the shortage of collected data is their usual incompatibility in different geographical regions, poor accessibility of the population to medical facilities in developing countries.
2.5 Future Perspectives
HCS 4.0 techniques could offer disruptive innovations, mitigating the COVID-19 crisis. They are expected to grow, storing health-related data on COVID-19 to be used for similar pandemics. Such technologies could rapidly be applied by healthcare providers in managing COVID-19 or similar pandemics, hence making a smarter health system. However, upgrading the current software infrastructure and devices is required. Of course, the industry of trackers and smartphones with the latest applications can help in part. But in developing them, manufacturers must take into account elements like minimal expanses, constrained consumer resources, access for illiterate or disabled subject, and support for several languages to be effectively adopted in different areas. To overcome these limitations, we must apply analytical approach and critical thinking.
Thanks to the active use of AI-based robotics, contactless drug delivery and remote treatment of patients has been made possible, reducing the need for medical personnel to contact infected people. AI can also predict the risk of serious COVID-19-related illnesses for people of all ages and take proactive measures to halt the virus transmitting to vulnerable groups. Thus, the analysis of the literature showed how AI, advanced mathematical modeling, ML, and cloud computing could expect the epidemic growth, and how the future state of global health depends on their coordinated and high-quality work.
2.6 Conclusion
HCS 4.0 applies sensors that are connected wirelessly with a system to display and monitor the entire intelligent manufacturing processes, for example, designing and producing the needed medical disposables and equipment to meet the gap caused by the COVID-19 crisis through an intelligent