A Multitasking Flexible Sensor via Reservoir Computing

人类多任务处理 数码产品 无线传感器网络 体积热力学 洪水(心理学) 计算机科学 实时计算 信号(编程语言) 材料科学 电气工程 工程类 心理学 计算机网络 物理 量子力学 认知心理学 程序设计语言 心理治疗师
作者
S. Wakabayashi,Takayuki Arie,Seiji Akita,Kohei Nakajima,Kuniharu Takei
出处
期刊:Advanced Materials [Wiley]
卷期号:34 (26) 被引量:36
标识
DOI:10.1002/adma.202201663
摘要

Natural disasters are reported globally, and one source of severe damage to cities is flooding caused by locally heavy rain. Sharing of local weather information can save lives. However, it is difficult to collect local weather information in real-time because such data collection requires bulky, expensive sensors. For local, real-time monitoring of heavy rain and wind, a sensor system should be simple and low-cost so that it can be attached to a variety of surfaces, including roofs, vehicles, and umbrellas. To develop simple, low-cost multitasking sensors located on nonplanar surfaces, a flexible rain sensor to monitor waterdrop volume and wind velocity is devised. To monitor both simultaneously, a laser-induced graphene-based superhydrophobic conductive film is introduced. Using the superhydrophobic surface, water dynamics are measured when waterdrops collide with the sensor surface, and obtained time-series data are processed using "reservoir computing" to extract the volume and velocity from a single sensor as multitasking electronics. As a proof-of-concept, it is shown that the sensor measures continuous, long-term volume and wind-change dynamics. The results demonstrate feasibility of multitasking electronics with reservoir computing to reduce sensor integration complexity with low power consumption for both sensor and signal processing.
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