Linoc:电容和无源电场传感的原型平台

Julian von Wilmsdorff, Malte Lenhart, Florian Kirchbuchner, Arjan Kuijper
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引用次数: 1

摘要

本文介绍了Linoc原型工具包。它是一个传感器工具包,专注于传感器系统的快速原型,特别是在电容式的。该工具包围绕两个电容和两个电位传感(EPS)组构建,在人机界面(HCI)领域提供不显眼的接近检测。该工具包的重点在于其可用性和连接性,以便适应未来的研究和新的用例。在项目开始时,一个常见的障碍是在实际的项目开始之前,熟悉现有的工具和系统所需要的时间。处理新任务时的另一个障碍是传感器与处理单元的实际物理连接。由于依赖于之前的工作,这种情况可能会变得更糟,即使原始设计师参与其中,大多数情况下也没有完整的文档记录和知识缺失。好的工具包可以通过提供一个抽象层并允许在更高的层次上工作来帮助克服这个问题。但是,如果工具包需要太多的时间来熟悉,或者行为过于严格,那么它的目标就没有实现,也不会产生任何好处。为了评估Linoc原型工具包的质量,它从三个不同的方面进行了评估:演示、使用和技术性能。使用研究发现了良好的接收,快速的学习曲线和在未来使用该工具包的兴趣。电容式传感器的技术基准显示,其可探测范围与前代产品相当,几个可操作的原型证明,该工具包实际上可以在项目中使用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Linoc: A Prototyping Platform for Capacitive and Passive Electrical Field Sensing
In this paper the Linoc prototyping toolkit is presented. It is a sensor toolkit that focuses on fast prototyping of sensor systems, especially on capacitive ones. The toolkit is built around two capacitive and two Electric Potential Sensing (EPS) groups providing unobtrusive proximity detection in the field of Human Computer Interface (HCI). The toolkits focus lies on its usability and connectivity in order to be adapted in future research and novel use cases. A common obstacle in the beginning of a project is the time required to familiarize with present tools and systems, before the actual project can be attended to. Another obstacle while tackling new tasks is the actual physical connection of sensors to the processing unit. This situation can be even worse due to dependencies on previous work, most of the times not fully documented and missing knowledge even if the the original designer is involved. Good toolkits can help to overcome this problem by providing a layer of abstraction and allowing to work on a higher level. If the toolkit however requires too much time to familiarize or behaves too restrictive, its goal has been missed and no benefits are generated. To assess the quality of the Linoc prototyping toolkit, it was evaluated in terms of three different aspects: demonstration, usage and technical performance. The usage study found good reception, a fast learning curve and an interest to use the toolkit in the future. Technical benchmarks for the capacitive sensors show a detectable range equal to its predecessors and several operational prototypes prove that the toolkit can actually be used in projects.
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