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机器学习辅助基于热水凝的自动供电身份识别,用于智能安全

Xueliang Ma¹, Wenxu Wang¹, Xiaojing Cui²

¹College of Electronic Information and Optical Engineering, Taiyuan University of Technology, Taiyuan, 030024, China.

Small (Weinheim an der Bergstrasse, Germany)

|May 10, 2024

概括

一个新的指头温度驱动的身份识别系统使用热水凝 (TGH) 阵列. 这种自动供电的生物识别安全实现了智能安全应用的高精度.

科学领域:

材料科学材料科学材料科学
生物技术是生物技术.
安全工程安全工程.

背景情况:

传统的身份识别系统在智能时代的准确性,复杂性和电力依赖性方面扎.
需要先进的生物识别安全解决方案,这些解决方案是强大的和自给自足的.
生物识别身份验证对于智能安全和人机交互至关重要.

研究的目的:

开发一个指头温度驱动的智能身份识别策略.
使用热水凝 (TGH) 进行活跃的生物特征识别.
通过创新的自动供电识别系统,增强安全性和人机互动.

主要方法:

使用双网络PVA/Agar水凝在H2O/糖二元溶剂中制造热化水凝 (TGH),并配有氧化还原对.
开发一个形的TGH阵列,从五个不同的位置捕获指纹内在温度特征.
集成机器学习算法用于基于提取的热生物识别数据的用户识别.

主要成果:

通过提取内在温度特征,TGH阵列成功地区分了用户特征.
使用TGH阵列与机器学习相结合,实现了97.6%的高平均识别精度.
自动识别身份识别策略在智能锁系统中成功实现.

结论:

指部温度驱动的TGH阵列为先进的身份识别提供了一个有前途的解决方案.
这种自动供电的生物识别策略比传统的基于密码的系统提供了更可靠的安全性.
这项技术对智能安全和未来万物互联网中的人机交互具有显著的优势.

关键词:

身份识别识别识别识别身份识别智能安全智能安全智能安全机器学习是机器学习.自动驱动的自动驱动汽车热的水凝是一种热的水凝.

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