由人工智能驱动的边缘物联网架构的改进,用于智能健康慢性疾病管理
William Alberto Cruz Castañeda1, Pedro Bertemes Filho1
1Electrical Engineering Department, Santa Catarina State University, Joinville 89219-710, Brazil.
Sensors (Basel, Switzerland)
|January 8, 2025
概括
本研究介绍了使用物联网 (IoT) 和边缘计算用于预防非传染性疾病的智能健康架构. CatBoost在非侵入性葡萄糖预测方面表现出色,证明了该系统对更智能的医疗保健的潜力.
科学领域:
- 医疗信息学 医疗信息学
- 人工智能的人工智能
- 物联网的物联网,就是物联网.
背景情况:
- 非传染性疾病是21世纪的重大健康挑战.
- 智能城市提供了一种技术解决方案,以提高医疗保健和居民福祉.
- 重新思考预防策略对于公共卫生的进步至关重要.
研究的目的:
- 提出一个新的智能健康架构,整合物联网 (IoT) 和边缘计算.
- 利用人工智能 (AI) 开发智能护理的基础层.
- 通过非侵入性葡萄糖预测案例研究来评估架构的有效性.
主要方法:
- 开发了一个基于物联网和边缘计算的架构,由AI驱动.
- 实施了一项以非侵入性葡萄糖预测为重点的案例研究.
- 基于基准的十二个回归算法,使用平均平方误差 (MSE),根平均平方误差 (RMSE) 和R平方 (R2) 评分来评估性能.
主要成果:
- 拟议的架构成功地感知并获得了用于葡萄糖预测的相关数据.
- CatBoost回归器表现出卓越的性能,MSE达到218.91 (训练) 和782.30 (测试),RMSE为14.80 (训练) 和27.97 (测试),R2为0.81 (训练) 和0.31 (测试).
- 建立了非侵入性葡萄糖预测算法性能的基线.
结论:
- 拟议的智能健康架构对于智能城市的数据采集和分析是有效的.
- 人工智能驱动的物联网和边缘计算对预防非传染性疾病充满希望.
- 未来的工作包括优化嵌入式人工智能模型,并探索用于可扩展智能健康解决方案的联合学习.
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