用边缘设备进行实时活动和上下文监控的联合学习框架
Rania A Alharbey1, Faisal Jamil2
1Department of Mathematics, Faculty of Science, King Abdulaziz University, Jeddah 21589, Saudi Arabia.
Sensors (Basel, Switzerland)
|February 26, 2025
概括
这项研究引入了使用智能手机进行实时老年护理监控的联合学习系统. 它增强了活动识别和跟踪,以提高老年人的安全和生活质量.
科学领域:
- 计算机科学 计算机科学
- 老年学是一门学科.
- 可穿戴技术可穿戴技术
背景情况:
- 对于先进的老年护理解决方案的需求日益增长.
- 需要非侵入性的实时监控系统.
- 在健康应用中利用无处不在的智能手机技术.
研究的目的:
- 开发一个联合学习系统,使用智能手机实时监控老年护理.
- 加强对老年人的活动识别和上下文监测.
- 为改善老年人的安全和福祉提供可扩展和高效的解决方案.
主要方法:
- 使用智能手机作为装备有惯性测量单元 (IMU) 传感器 (加速计,气压计,陀螺计,磁力计) 的边缘设备.
- 在每个设备上实施本地数据处理以进行个性化模型培训.
- 使用联邦平均算法 (FedAvg) 在中央服务器上汇总本地模型.
- 整合活动识别与位置,高度和上下文数据进行全面监控.
主要成果:
- 成功开发老年护理的联合学习系统.
- 通过模型聚合,提高了活动识别的准确性.
- 实时跟踪和监控老年人的位置,高度和环境.
- 证明了拟议系统的可扩展性和效率.
结论:
- 联合学习方法为实时老年人护理提供了一个有希望的解决方案.
- 整合各种传感器数据可以提高监控的全面性.
- 该系统通过先进的技术提高了老年人的安全和生活质量.
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