# Exploitation of Emerging Technologies and Advanced Networks for a Smart Healthcare System
## 5 System Architecture  
The main goal of a smart health care system is the successful combination of the emerging technologies for the enhanced medical detection, diagnosis, and treatment of an illness or disease. Such a system integrates the benefits delivered by WSN and the immediacy of the data produced by IoT, with the computation power offered from a CC server, established in a 5G wireless network, due to the high transmission data rate and low latency that could offer, in order to provide immediate disorder detection. VR, AR, and MR can offer access to volumetric data in a 3D environment, which may help with a medical diagnosis. Furthermore, the system could manage and control the BD produced by sensors and analyze it through ML and DL algorithms and DNN to propose both accurate medical diagnosis and treatment. Through the aid of haptics, a potential surgical operation could become less painful for the patient and more convenient for the surgeon, while the  
Figure 7: Virtual Reality, Augmented Reality, and Mixed Reality. use of AI could go a step forward such an operation, which could be contacted wholly unsupervised by robotic devices. In order to transfer the exaggerated amount of data produced by different devices such as sensors and cameras, the Extensible Messaging and Presence Protocol (XMPP) has been chosen. This protocol is an open standard and has been used and tested widely. The publish/subscribe model of XMPP is presented in Figure 8[68]. This model provides a safe and efficient data exchange, where a publisher sends the data to the broker device. Then, the broker device forwards the updated data to any subscriber device that asks for a specific topic. For example, a temperature sensor will publish the temperature data to the broker under the temperature topic. These data will be available to anyone who requests the temperature topic. The XMPP is a protocol that fits the cloud and storage systems' needs. Moreover, a framework was applied for the implementation of the system and the communication of all devices, servers, and databases providing an abstraction of the network devices. This framework simplifies the interaction between the Application Programming Interface (API), which is hosted in the user's device, and the IoT devices. Specifically, the framework was used for data fetching, data visualization, and authentication of the users. Firstly, the IoT devices should be installed and programmed in order to produce data over time. Most of the data usually are in a form and volume that many times are unmanageable. In addition, to make the data have a valuable meaning, suitable ML algorithms should be integrated. Then, the data should be published into a database, the Redis database, where they can be stored and manipulated. Redis can also be used as a broker device. Thereafter, the application used and connected to the system via 5G connectivity will be responsible for the visualization of the data, for the real-time update of the API, and for the valuable notifications. Finally, for the more complex outcomes, a cloud server should be used that provides deep learning techniques to have a better insight of the data collected and stored in the database. Regarding the detection phase of an illness or disorder, the cloud server is responsible for the supervision of each surveillance infrastructure. Additionally, the cloud server may accept data from an installed infrastructure that is not directly connected to it. All the data  
Figure 8: Publish/Subscribe communication model. collected from the system should be then managed and preceded in the cloud server in order to export the necessary conclusions via BDA for each monitoring area. Thermal-IR cameras help to detect the temperature of the environment, and more specifically, from the individuals when entering or moving into the surveillance space. The images captured from each camera are sent to the cloud server via 5G networks.