Ma Xueliang, Wang Wenxu, Cui Xiaojing, Li Yunsheng, Yang Kun, Huang Zhiquan, Zhang Hulin
College of Electronic Information and Optical Engineering, Taiyuan University of Technology, Taiyuan, 030024, China.
School of Physics and Information Engineering, Shanxi Normal University, Taiyuan, 030031, China.
Small. 2024 Sep;20(37):e2402700. doi: 10.1002/smll.202402700. Epub 2024 May 10.
Identity recognition as the first barrier of intelligent security plays a vital role, which is facing new challenges that are unable to meet the need of intelligent era due to low accuracy, complex configuration and dependence on power supply. Here, a finger temperature-driven intelligent identity recognition strategy is presented based on a thermogalvanic hydrogel (TGH) by actively discerning biometric characteristics of fingers. The TGH is a dual network PVA/Agar hydrogel in an HO/glycerol binary solvent with [Fe(CN)] as a redox couple. Using a concave-arranged TGH array, the characteristics of users can be distinguished adequately even under an open environment by extracting self-existent intrinsic temperature features from five typical sites of fingers. Combined with machine learning, the TGH array can recognize different users with a high average accuracy of 97.6%. This self-powered identity recognition strategy is further applied to a smart lock, attaining a more reliable security protection from biometric characteristics than bare passwords. This work provides a promising solution for achieving better identity recognition, which has great advantages in intelligent security and human-machine interaction toward future Internet of everything.
身份识别作为智能安全的第一道防线起着至关重要的作用，但其正面临着新的挑战，由于准确率低、配置复杂以及对电源的依赖，无法满足智能时代的需求。在此，基于热致电流水凝胶（TGH），通过主动识别手指的生物特征，提出了一种手指温度驱动的智能身份识别策略。TGH是一种在HO/甘油二元溶剂中以[Fe(CN)]作为氧化还原对的双网络PVA/琼脂水凝胶。使用凹形排列的TGH阵列，通过从手指的五个典型部位提取自身存在的固有温度特征，即使在开放环境下也能充分区分用户特征。结合机器学习，TGH阵列能够以97.6%的高平均准确率识别不同用户。这种自供电身份识别策略进一步应用于智能锁，与单纯密码相比，从生物特征上获得了更可靠的安全保护。这项工作为实现更好的身份识别提供了一个有前景的解决方案，在面向未来万物互联的智能安全和人机交互方面具有巨大优势。
