首页> 外文会议>2019 IEEE International Conference on Flexible and Printable Sensors and Systems >Detectors and light-sources for optical spectrometry: from a 3D-printed light-source to a self-powered sensor fabricated on a flexible polymeric substrate, and from there on to an IoT-enabled 'smart' system
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Detectors and light-sources for optical spectrometry: from a 3D-printed light-source to a self-powered sensor fabricated on a flexible polymeric substrate, and from there on to an IoT-enabled 'smart' system

机译:光谱仪的检测器和光源:从3D打印的光源到在柔性聚合物基板上制造的自供电传感器,再从那里到支持IoT的“智能”系统

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We are developing detectors to sense the visible part of the spectrum. We are also developing light-sources that generate spectral signals from micro-samples introduced (for compatibility reasons) into micro-plasmas. Our battery- operated microplasmas are coupled to a portable, fiber-optic spectrometer and this combination (or system) can be thought of as a "multi parameter" or "multi-element sensor" for the UV and the Vis parts of the spectrum. Initially, our Micro Plasma Devices (MPDs) were fabricated using technologies borrowed from the semiconductor industry (e.g., microfluidics, micromachining) [1] . To reduce fabrication costs and to enable rapid prototyping [2] , we fabricated Micro Plasma Devices using 3D-printing of polymeric materials [3] . We also fabricated (and continue to characterize) a relatively- inexpensive self-powered detector on a flexible polymeric substrate [4] . The detector responds to light from the visible part of the spectrum. To enable portability for chemical measurements on-site (i.e., in the field) we often used a smartphone for data acquisition and signal processing, thus enabling a sensor-system to be placed on the Internet of Things (IoT) and potentially, to be employed in Society 5.0 applications [5] . To further facilitate use on-site (i.e., in the field), portable optical spectrometers with a short focal length must be used. But as focal length decreases, spectral overlaps (often called spectral interference effects) arise. To address them, we employed Artificial Intelligence (AI) methods using Artificial Neural Networks (ANNs) and Deep Learning approaches, thus (in many respects) making sensor-systems smarter [6] . In this paper (due to space limitations), emphasis will be will be placed on recent developments.
机译:我们正在开发检测器,以感知光谱的可见部分。我们还正在开发光源,这些光源可从(出于兼容性原因)引入微等离子体的微样品中产生光谱信号。我们的电池操作等离子仪与便携式光纤光谱仪相连,可以将这种组合(或系统)视为UV和Vis部件的“多参数”或“多元素传感器”。的频谱。最初,我们的微等离子体设备(MPD)是使用从半导体行业借鉴的技术(例如,微流体技术,微加工技术)制造的[1]。为了降低制造成本并实现快速原型制作[2],我们使用聚合物材料的3D打印技术制造了微等离子体设备[3]。我们还在柔性聚合物基板上制造(并继续表征)相对便宜的自供电检测器[4]。检测器对来自光谱可见部分的光做出响应。为了实现现场(即在现场)化学测量的便携性,我们经常使用智能手机进行数据采集和信号处理,从而使传感器系统可以放置在物联网(IoT)上,并且有可能在Society 5.0应用程序中使用[5]。为了进一步促进现场使用(即在现场),必须使用焦距短的便携式光学光谱仪。但是随着焦距的减小,会出现光谱重叠(通常称为光谱干扰效应)。为了解决这些问题,我们采用了使用人工神经网络(ANN)和深度学习方法的人工智能(AI)方法,从而(在许多方面)使传感器系统更智能[6]。在本文中(由于篇幅所限),重点将放在最新的发展上。

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