A Multitasking Flexible Sensor via Reservoir Computing
Source abstract
Abstract
Abstract 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.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Neural Networks and Reservoir Computing · Advanced Memory and Neural Computing · Random lasers and scattering media
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Physics and Electronics Osaka Prefecture University Sakai Osaka 599‐8531 Japan
Department of Physics and Electronics Osaka Metropolitan University Sakai Osaka 599‐8531 Japan
Graduate School of Information Science and Technology The University of Tokyo Tokyo 113‐8656 Japan
Next Generation Artificial Intelligence Research Center The University of Tokyo Tokyo 113‐8656 Japan
Funding
TEPCO Memorial Foundation
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