The rise of big data and the internet of things has driven the demand for multimodal sensing and high-efficiency low-latency processing. Inspired by the human sensory system, we present a multifunctional optoelectronic-memristor-based reservoir computing (OM-RC) system by utilizing a CuSCN/PbS quantum dots (QDs) heterojunction. The OM-RC system exhibits volatile and nonlinear responses to electrical signals and wide-spectrum optical stimuli covering ultraviolet, visible, and near-infrared (NIR) regions, enabling multitask processing of dynamic signals. The OM-RC system accurately performs health monitoring through dynamic electroencephalogram and electrocardiogram signal analysis and achieves object and traffic trajectory recognition for intelligent driving under challenging conditions like foggy environments. By collaboratively using the NIR perception and trajectory recognition, we develop a human–computer interaction authentication system that integrates finger veins and motion behaviors of humans, significantly enhancing the security of traditional fingerprint anticounterfeiting systems. This work demonstrates the potential of QD-based optoelectronic-memristor for multitask in-sensor processing applications.

中文翻译：

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面向多任务储层计算的基于 PbS 量子点的光电忆阻器


大数据和物联网的兴起推动了对多模态传感和高效低延迟处理的需求。受人类感觉系统的启发，我们利用 CuSCN/PbS 量子点 （QD） 异质结提出了一种基于光电忆阻器的多功能储层计算 （OM-RC） 系统。OM-RC 系统对电信号和覆盖紫外、可见光和近红外 （NIR） 区域的宽光谱光刺激表现出易失性和非线性响应，可实现动态信号的多任务处理。OM-RC 系统通过动态脑电图和心电图信号分析准确进行健康监测，实现物体和交通轨迹识别，在雾化环境等挑战性条件下实现智能驾驶。通过协同利用近红外感知和轨迹识别，我们开发了一个集成了人类手指静脉和运动行为的人机交互认证系统，显著增强了传统指纹防伪系统的安全性。这项工作展示了基于 QD 的光电忆阻器在多任务传感器内处理应用中的潜力。