International Journal of Clinical Case Reports 2024, Vol.14, No.6, 339-350 http://medscipublisher.com/index.php/ijccr 346 7.2 Multi-device connectivity and remote management The advent of IoT and 5G technologies is revolutionizing the connectivity and management of smart health devices, thereby enhancing community care services. IoT enables the seamless integration of various health monitoring devices, facilitating real-time data collection and remote patient monitoring (Alshamrani, 2021). The deployment of 5G networks further supports this integration by providing the necessary bandwidth, low latency, and high reliability required for efficient data transmission and device communication (Kang et al., 2018). This combination allows for more robust and responsive healthcare systems, enabling remote diagnostics, continuous monitoring, and timely interventions, which are crucial for improving the quality of community care (Kang et al., 2018; Chen et al., 2022a). 7.3 Personalized and precision health management Smart health devices are pivotal in advancing personalized and precision health management by offering customized healthcare services tailored to individual needs. These devices can monitor various health parameters, such as heart rate, blood glucose levels, and body temperature, and use AI to analyze this data to provide personalized health recommendations (Alshamrani, 2021). The integration of AI with wearable IoT systems in long-term care environments exemplifies how personalized care can be achieved, focusing on individual health, nutrition, and lifestyle management (Wang and Hsu, 2023). This approach not only enhances patient outcomes but also empowers individuals to take an active role in managing their health (Chen et al., 2022b). 7.4 Cross-sector collaboration between community care and smart devices The successful implementation of smart health devices in community care requires cross-sector collaboration among various stakeholders, including communities, hospitals, families, and government entities (Zhang, 2024). Such collaboration ensures a holistic approach to healthcare, leveraging the strengths of each sector to improve care quality. For example, federated learning in smart healthcare allows multiple entities, such as hospitals, to collaborate on AI training without sharing raw data, thus addressing privacy concerns while enhancing the collective intelligence of healthcare systems (Ahad et al., 2019). Additionally, integrating AI and IoT in healthcare systems facilitates comprehensive communication and coordination among different care providers, promoting a more cohesive and efficient healthcare delivery model (Sharma et al., 2022; Wang and Hsu, 2023). This collaborative approach is essential for addressing the complex and dynamic needs of community care, ultimately leading to better health outcomes and more sustainable healthcare systems. Acknowledgments Thank you for the constructive comments on the draft of this manuscript provided through peer review. Conflict of Interest Disclosure The authors affirm that this research was conducted without any commercial or financial relationships that could be construed as a potential conflict of interest. References Ajakwe S., Nwakanma C., Kim D., and Lee J., 2022, Key wearable device technologies parameters for innovative healthcare delivery in b5g network:a review, IEEE Access, 10: 49956-49974. https://doi.org/10.1109/ACCESS.2022.3173643 Ahad A., Tahir M., and Yau K., 2019, 5G-Based smart healthcare network: architecture, taxonomy, challenges and future research directions, IEEE Access, 7: 100747-100762. https://doi.org/10.1109/ACCESS.2019.2930628 Ahad A., Tahir M., Sheikh M., Ahmed K., Mughees A., and Numani A., 2020, Technologies trend towards 5G network for smart health-care using IoT: a review, Sensors (Basel, Switzerland), 20(14): 4047. https://doi.org/10.3390/s20144047 Alshamrani M., 2021, IoT and artificial intelligence implementations for remote healthcare monitoring systems: a survey, J. King Saud Univ. Comput. Inf. Sci., 34: 4687-4701. https://doi.org/10.1016/j.jksuci.2021.06.005 Al-rawashdeh M., Keikhosrokiani P., Belaton B., Alawida M., and Zwiri A., 2022, IoT adoption and application for smart healthcare: a systematic review, Sensors (Basel, Switzerland), 22(14): 5377. https://doi.org/10.3390/s22145377 PMID: 35891056 PMCID: PMC9316993
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