Assessing the Compatibility of Arduino with 6G for Real-Time Patient Monitoring
| Autor: | Tetiana Soloviova, Marwa Mahmood Younis, Bassam H. Habib, Manar Adnan Nassrat Al-Ubaidi, Samer Saeed Issa, Yaser Issam Hamodi Aljanabi, Moamin Ibrahim Jameel Al-Obaidi |
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| Jazyk: | angličtina |
| Rok vydání: | 2024 |
| Předmět: | |
| Zdroj: | Proceedings of the XXth Conference of Open Innovations Association FRUCT, Vol 36, Iss 1, Pp 445-459 (2024) |
| Druh dokumentu: | article |
| ISSN: | 2305-7254 2343-0737 |
| DOI: | 10.23919/FRUCT64283.2024.10749898 |
| Popis: | Background: The adoption of sixth generation (6G) networks is expected to revolutionize various sectors like health care by providing unprecedented data transfer capabilities and reliability. This transition is particularly applicable to real-time health monitoring where the speed and consistency of data transmission matters. Objective: The article explores the integration of Arduino Bluetooth modules, specifically the Bluetooth HC-05 module, with 6G technologies for betterment in remote health monitoring systems. By merging the ultra-reliable, low-latency communication (URLLC) characteristics of 6G with the relatively cheap and user-friendly nature of Arduino platforms, a more intelligent health monitoring system could be established. Methodology: The article proposes Arduino sensor modules with a 6G-based real-time uplink to transmit high-resolution biometric data. The study also uses machine learning and edge computing methodologies to improve data processing for patient diagnosis. Factors such as power usage, scalability, and network integration are thoroughly explored to reach a holistic strategy. Results: The results suggest that the use of Arduino Bluetooth and 6G together can enable much better monitoring of many categories in health metrics to meet very different patient profiles. In this collaboration, we are also going to include the two main things that need everyone's attention, data privacy and security. Moreover, the utilization of artificial intelligence (AI) and edge computing led to improved diagnoses and quicker responses. Conclusions: The study demonstrates the promise of Arduino Bluetooth for future healthcare monitoring over 6G networks, and serves as a benchmark toward such ends. It paves the way for cheaper, more available, and innovative healthcare options in the era of the Internet of Things (IoT) and beyond, transforming patient treatment. |
| Databáze: | Directory of Open Access Journals |
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