人工智能增强边缘和雾计算用于健康物联网 (IoHT)
Deepika Rajagopal1, Pradeep Kumar Thimma Subramanian1
1Computer Science and Engineering, Vellore Institute of Technology University, Chennai, Tamil Nadu, India.
PeerJ. Computer science
|March 10, 2025
概括
由人工智能增强的边缘和雾计算为健康事物互联网 (IoHT) 中的实时健康数据分析提供了解决方案. 这种方法解决了基于云计算的医疗保健系统中的可扩展性和延迟问题.
科学领域:
- 专注于计算机科学,医疗保健技术和人工智能的交集.
- 探讨边缘/雾计算和健康物联网 (IoHT) 的进展.
- 研究人工智能和机器学习在远程医疗保健中的应用.
背景情况:
- 现代医疗保健需要个性化的系统,但当前的云计算具有可扩展性的局限性.
- 物联网 (IoT) 正在彻底改变医疗保健,需要适应性强的患者管理系统.
- 现有的IoHT研究主要涉及架构和网络,忽视了关键的计算技术.
研究的目的:
- 检查现有和未来的雾和边缘计算架构,并与IoHT应用程序的AI进行增强.
- 定义将雾和边缘计算集成到 IoHT 框架中的需求和挑战.
- 引导医疗保健专业人员和技术人员选择适合远程医疗保健解决方案的技术.
主要方法:
- 审查当前和未来的医疗保健中的雾和边缘计算架构.
- 对IoHT的人工智能 (AI) 和机器学习 (ML) 技术的分析.
- 探索启用技术,如5G,UCaaS,NB-IoT和IoHT的区块链.
主要成果:
- 与人工智能的边缘/雾计算满足了对实时健康数据的能源效率和低延迟需求.
- 人工智能和机器学习对于IoHT的高效资源管理至关重要.
- 像NB-IoT和区块链这样的技术正在通过提高覆盖范围和安全性来改变IoHT.
结论:
- 由AI增强的雾和边缘计算对于开发先进的IoHT框架至关重要.
- 解决资源管理,延迟和安全问题是有效实施IoHT的关键.
- 未来的研究应该专注于整合先进技术,以改善边缘和雾计算服务,以提高患者的生活质量.
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