IoT-enabled Smart Healthcare Systems, Services and Applications. Группа авторов

      The emerging technologies discussed before having contributed a great part in smart medication, telemedicine, and to provide remote assistance to the patients. Another smart technology named 5G is currently one of the fastest growing industries. 5G is proposed by researchers and experts to continue to assist and monitor patients in several diseases. Smartly designed gadgets and sensors collect information from a number of resources and provide guidance to anyone from anywhere to assist them in taking the right medication in the right manner so that the mistakes can be prevented to use medicines as well as to reduce the cost of treatments and medicines [21].

5G is the upcoming generation of today’s 4G network, so 5G can deliver the speedy, extensible network having the larger volume. Instead of providing the fastest Internet connection, the healthcare industry is also getting benefit due to 5G's reliable connectivity for heavy medical devices with increased spectrum, greater capacity, more users as compared to previous LTE networks. 5G can technically provide a low latency of 1 ms, as compared to the previous 20 ms latency. It is good enough to strengthen medical sensors and devices, medical equipment, and video streaming, which may be helpful in telemedicine, teleconsultation, and remote surgery with clean streaming and detailed information deliverance. 5G has also overcome the data transfer issues faced in high‐latency networks with stable high speed. 5G provides a greater number of facilities as compared to 4G in smart diabetes detection. It can provide the following five benefits to the patients as well as paramedical staff.

       Profitability: It makes users aware of a pre‐diabetic condition if there is one and provides them with a healthy way of life, which can save their expenditures on treatment and medicines For older people who are long‐term patients and unable to attend doctors, it provides tele‐treatment.

       Convenience: 5G does not discomfort the patient as it supports smart‐clothing glucose monitoring. Another instance is that healthcare providers are extending their duties outside the hospital through real‐time video conferencing.

       Personification: 5G uses several machine learning algorithms and different computing techniques for the prevention of diabetes. Depending on patients’ health records, 5G generates a personalized treatment for e patient.

       Durability: 5G supports efficient sharing of useful information between doctors and patients and friends and family to change the mental condition of patients so that they can feel self‐motivated and produce good changes in their environment and be prepared for a better future treatment.

       Elegance: With its intellectual characteristics toward patient health and resources, it can detect diabetes sooner and prevent its causes.

1.3 Realization of SHC through Emerging Technologies (Applications)

      1.3.1 Applications of AI

Early detection of healthcare conditions, smart diagnosis, telemedicine, and discovery of several treatments are possible due to the emergence of AI. AI in healthcare produces an advantage in care and quality services. Smart healthcare is a supreme platform for AI applications and systems, where the health industry depends on information and logic to improve the patient’s state. There has been a fantastic improvement in the collection of data containing genetic, environmental, mental, and behavioral information. If we use AI in our daily healthcare routine, then it will not only improve our health condition, but it will also recognize the detection and upcoming illness occurring in our body. Some of the important facts of health where AI goes revolutionize this sector with its full zoom. Fei Jiang illustrates the analytical techniques of AI in healthcare either structured in modern deep learning and neural networks or unstructured in terms of natural language processing (NLP). AI uses algorithms to take structures from the bulk of healthcare data and target them to assist in the clinic. This paper mentions the future of AI and surveys its application for managing the healthcare system [4].

      1.3.1.1 Patient Care Improvement

      Patient care in terms of clinical and in home–based settings have both been greatly enhanced by AI. In the healthcare sector AI plays the role of a backbone for developing and improving patient care in predictive analytics and decision support systems. OECD hosted a Global Partnership on AI (GPAI) that directs the route of AI to behave responsibly in respecting patients’ rights by bridging the gap between experts from academia, civilians, stakeholders, and industry by proper implementation of theory and practice [13, 14]. Precision medicine can take part in improving patient health by recruiting complex datasets from a variety of complex situations, for example, health records, morphological data, and psychological reactions. AI‐enhanced technologies can point out dangerous conditions or encourage emotional health. These technologies are more beneficial for older people and people having special abnormalities.

      1.3.1.2 Maintaining Health Records

Medical practice has become transformed due to computerized patient healthcare charts. Electronic health record (EHR) systems are increasingly adopted in many developed countries; they also establish mobile health to allow mobile services in support with the usage of medicines for daily health routine checkups. EHR systems diminish errors of medication and improve coordination of care. The data extracted from EHR systems for statistics and research give support to many countries to achieve the goal for a high‐level achievement. Healthcare still captures the data in devices and is separately analyzed. Interoperability is a basic challenge that must be known about the full future of EHRs. One of the articles described the situation of young man, Roger, who came to the hospital in emergency grumbling with nausea and belly pain. This article showed 55 doctors to identify the usability of EHRs. These digital versions of paper charts are used by caretakers to record patients’ history, lab tests, early diagnosed prescriptions, disease background, and so forth, for medication doctor transfer in the EHR system and the search contained 500‐mg dosage of Tylenol because Roger was 26 years old. The doctor selected the appropriate option and prescribed the medication dose [16]. Availability of data is a basic element of EHR implementation, and EHR makes a perfect match for machine learning for fueling the data science operations. Machine learning is a remarkable milestone for fundamentals of EHR for example, data mining, NLP for document searching, transcription of report generation, data visualization, privatization and data, and predictive analysis. Thus we can say without AI we cannot imagine the medical world today.

      1.3.2 Applications of IoT

      IoT made the profession of healthcare more vigilantly connected with a survivor. Chronic diseases are increasing very fast and the population is aging, so there is a deep necessity of connectivity with pocket devices that can be easily accessible for both patients and doctors. Most people have a scarce situation to fight with the basics of healthcare but emerging technology at least IoT can ensure access to healthcare accessories easily and help to reach your doorstep. IoT has a significant role in healthcare innovations; according to statistical projections the use of healthcare devices is anticipated to increase to about 25.8 million units by 2025 [18]. From many types of research, IoT for healthcare in the context of remote patient monitoring for the care of the patient through sensor usage by gathering and inspecting the data and sending inspected patients’ information remote to the hospitals and care organization allows for prescribed quick action [11]. Sensors, digital assistance, and radio frequency identification tags (RFID) are made pervasive to collect on‐time data and help to make quick decisions. Controlling and monitoring play an important role for the implementation of IoT [10].

      1.3.2.1 Glucose Monitoring

Diabetes is now becoming a common disease in developing countries due to unhealthy environments and food processing; older people is especially affected so they must watch their glucose levels to avoid any bad situation. IoT introduces a glucose monitoring system for continuous surveillance. Diabetes patients would have devices equipped with sensors embedded below their dermis. The sensor in the device sends continuous signals toward the personal gadget when glucose level is too low and stores history for them too. In this way, the