The revolution in wireless technology has assisted humanity by connecting them anywhere , anytime. The purpose of this design is to create a safe and optimized motivational mechanism for the patient while maintaining privacy in the design of digital information packets in health care.

Although , the risks and challenges are considerably raised for communication on high-frequency bands that enable a massive number of wireless applications to produce and store huge amounts of sensitive data in different fields , especially in healthcare.

To take advantage of progresses in technology, the research community is still proposing exquisite theories, algorithms and models for the detection of various diseases in their early stages, using wearable sensors, smart sensors, mobile applications, machines and deep learning models. These can all increase the authenticity of medical decision making for patients.

However, individuals and organizations are averse to adopt Internet of Things based healthcare systems due to concerns regarding data privacy, implementation cost, and application reliability.

It is therefore important to investigate distributed models, such as federated learning or blockchain encryption, rather than centralized models so that individuals and hospitals may keep their sensitive data while sharing the global output with the server, enabling decision making while preserving privacy.

Similarly, optimized and efficient machine and deep learning algorithms and cost-effective and powerful smart sensors may be proposed to improve application reliability and data aggregation and processing, respectively.

The hospital staff should be informed about the assignment of solutions related to the continuous examination of the patient's health as well as the early diagnosis of diseases.

However, it is very challenging to examine a large amount of data gathered from different patients simultaneously, and so secured smart detection procedures are necessary for timely identification and to take preventive measures. Therefore, it is essential to enable artificial intelligence at every stage, from data collection by smart sensors to data analysis.