## 7 Discussion  
In the context of WBANs, which facilitate communication between devices located on or within the human body, the challenges associated with traditional radio frequency (RF) communication methods--such as high power consumption and susceptibility to interference--can be effectively mitigated through the use of Intrabody Communication [1, 2, 3]. IBC utilizes the human body as a conductive medium, allowing for more reliable data transmission while significantly reducing power requirements. This characteristic aligns well with the goals of NB-IoT, which seeks to enable long-range communication with low energy consumption. Moreover, the incorporation of biometric identity into IBC-enabled WBANs enhances both security and personalization [26, 39, 40, 41]. By leveraging the unique biological and geometric characteristics of individuals, such as height, weight, and body composition, the IBC channel gain can serve as a biometric identifier. This capability not only improves the accuracy of user identification but also provides new opportunities for industrial applications in various fields, including healthcare and security.  
The results of our research indicate that the identification accuracy achieved through the KNN algorithm, based on IBC channel characteristics, reached 99.9% as a modeling result. Usage of the KNN algorithm has advantages like simplicity, no training phase, and effective for small datasets, as well as limitations like computationally intensive for large datasets and sensitivity to irrelevant features. Further application of the K-Dimensional Tree (also known as KD Tree) might influence the accuracy and processing power requirements. It is necessary to mention the dataset that was used was the most advanced for the time modeling was provided. Diversification and further development of the experimental dataset are suggestions for future research, as these limit the study, where we have only 30 subjects being recorded and their dataset being analyzed. The high level of accuracy underscores the potential for biometric identification to be seamlessly integrated into IBC systems, thereby enhancing the overall functionality of WBANs. As the technology continues to evolve, the combination of NB-IoT, IBC, LTE-M, and biometric identity could revolutionize the way we approach health monitoring and personal security, making these systems more efficient, reliable, and user-centric. In the future, it is planned to investigate how body movements will affect the channel gain profile and, therefore, the functionality of a real biometric identification system.  
In conclusion, the synergy between NB-IoT and WBANs (with the use of LTE-M), coupled with the innovative use of biometric identity, presents a transformative opportunity in the field of wearable technology. This integration not only addresses existing challenges in communication and power consumption but also enhances the security and personalization of health-monitoring systems, paving the way for broader adoption and application in various domains. As research and development in this area progress, we anticipate significant advancements that will further expand the capabilities and applications of IBC-enabled WBANs.