Smart Systems for Industrial Applications. Группа авторов

environment of Remote Healthcare because the speed and efficiency of resources play a critical role in patient health. Response time should not be lost at the cost of security as well. SAB-UAS performs well compared to other authentication systems. Maybe with increasing communication nodes, it has lower efficiency in PDR and ETE. This proposed SAB-UAS scheme can substantially improve performance at the storage, computation, and communication level at the same time, keeping costs at lower. This, in turn, makes Remote Healthcare Management a real-time application. SAB-UAS has robust security when it comes to both formal and informal security threats and potential attacks. The essential of IoT and security of collected information are summarized in Table 1.5.

1.6 AI-Driven Augmented and Virtual Reality–Based Communication Technologies and Healthcare Applications

      Technology is getting better, smaller, and faster. Virtual reality (VR) is a highly interactive, computer-based multimedia environment in which the user becomes the participant in a computer-generated world. VR and augmented reality (AR) are having an impact on most aspects of modern life. AR is an integration of the real world and the virtual world, with the aim of providing additional information about something in the real world with information displayed in the virtual world. In recent times, the scope of AR applications has expanded to include innovation for the domains of Research, Science, Medicine, Telecommunications, etc. For instance, a person could look at a painting or a machine in the real world, hold up their smartphones or tablet in front of the painting or machine, and see on the screen the painting or machine with additional useful information, thus augmenting reality. It is becoming ever more in demand in every segment of the economy, particularly in healthcare. With the technological advancements in AI, their demand is also increasing progressively in healthcare applications. Not just in healthcare, VR is helping organizations in different sectors to train their workforce as a good communicator. In reference to Healthcare and Medical Clinics, simulations are developed with a pre-defined script and one or more avatars with whom the player can interact. This article describes the impact of VR and AR in communication technologies and healthcare applications.

Table 1.5 Role of AI-driven IoT in healthcare services.

Source	Subject matter	Applications	Related performance measures
[26]	Digital transformation	Automated management and monitoring chronic conditions	Sensor devices usage increases up to 23.8% Compound Annual Growth Rate (CAGR)
[27]	Hierarchical computing Architecture for Healthcare IoT	Machine learning–based data analyticsClosed-loop autonomous system	Employed in arrhythmia detection for patients suffering from cardiovascular diseasesAchieves 93.6 accuracy using k-fold cross validation method.
[28]	Regulation of wireless devices operation	Dynamic and interoperable communication framework	Enhances the decision-making capabilities of wearable sensors.Optimizes device lifetime, storage capacity and handling multiple communication channel
[29]	Security parameters	Secure-Anonymous Biometric-based User Authentication Scheme (SAB-UAS)	Achieves delay up to 0.02 seconds in a network with 160 sensor nodes.Also achieves throughput of 2500bps with a same network

      1.6.1 Clinical Applications of Communication-Based AI and Augmented Reality

      AI, together with AR, has vast clinical and surgical applications in healthcare. The unsupervised models allow the system to recognize the patterns followed by the initiation of the algorithm based on previous patterns. In addition, reinforcement learning algorithms use positive and negative rewards or punishments in their learning methodologies [30]. Whether the relationship between input and output is linear or not, the programs go through more decision-making layers to deduce a mathematical rule to create outputs based on specific inputs. The disciplines of medicine that rely on deep learning that include radiology and pattern recognition have become more precise than human intervention methods [31]. Deep learning algorithms are applied in finding out malignancy and improving neonatal imaging and neurologic imaging qualities.

The AI models are used to forecast the readmission and delayed discharge [32]. There are various lung cancer models used to aid in the prediction, diagnosis, and planning of treatments [33]. The prediction of survival rate after surgery is modeled for cervical cancer patients [34]. From applications like simple prognostic tools to big and complex models, AI is used. There is also a saying that AI models are superior to traditional regression models for outcome prediction [34]. All the way, virtual AI is yet to reach its high potential in gynecology. There are various opportunities that exist to improve the treatment and diagnosis, especially in gynecologic oncology.

      1.6.2 Surgical Applications of Communication-Based on Artificial Intelligence and Augmented Reality

      There are developments in the new paradigm that enhance human abilities more than AI to support, along with decision-making and surgery. The development of AI-based AR communication systems can reduce natural limitations, improve awareness so that it can minimize error, and improve the efficiency of movement. The AR-based AI communication has already proved to reduce surgery time and they verify the improved accuracy [35]. The communication assisted AR is applied in gynecologic surgery in the way of robotic tools to overcome the drawback in surgical skills. The communication-based and robotic-assisted tools reduce the human tremor so that the accuracy can be maximized.

      The anatomical relationship that exists between healthy organs and pathologic was well understood by surgeons by exhibiting the preoperative available images. Particularly if the organs of interest are immobile, then AR-based surgeries are successfully implemented. The recent application of AR in improved myoma detection and fibroid mapping are very good examples [36]. Some other similar techniques are used in gynecologic oncology for the identification of sentinel lymph nodes that have reduced the morbidity incorporated with group lymphadenectomy [37]. The communication technologies associated with three-dimensional printing to create physical models for better visualization of organ configuration offers an AR, which is unrealizable through other traditional imaging techniques. With recent techniques, advanced communication-enabled 3D printers can emulate various tissue types [38]. Given the changes in myoma size, position, and length within a uterus, 3D printing of a uterus can help the surgeon come up with good prior operative planning. In this manner, communication technologies associated with AI and AR offer a great deal in helping gynecological surgeons.

We concluded that further research and application of VR and AR in the healthcare and communication technologies are necessary. The summary of above discussed article is given in Table 1.6.

Table 1.6 Impact of AI-driven augmented and virtual reality in healthcare.

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