Poster: am i indoor or outdoor?

Valentin Radu, P. Katsikouli, Rik Sarkar, M. Marina
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引用次数: 9

Abstract

The environmental context of a mobile device determines where/how it is used, which can be exploited for efficient operation and better usability. In this work we describe a general method using only the lightweight sensors on a smartphone to detect if a device is indoor or outdoor. Using semi-supervised machine learning techniques, our method automatically learns characteristics of new environments and devices, thereby achieves detection accuracy of over 90% even in unfamiliar circumstances. Therefore, it easily outperforms existing indoor-outdoor detection techniques based on static algorithms, or relying on energy hungry and unreliable GPS.
海报:我在室内还是室外?
移动设备的环境上下文决定了它的使用地点和方式,这可以用于有效的操作和更好的可用性。在这项工作中,我们描述了一种仅使用智能手机上的轻量级传感器来检测设备是室内还是室外的一般方法。使用半监督机器学习技术,我们的方法自动学习新环境和设备的特征,从而即使在不熟悉的环境中也能达到90%以上的检测准确率。因此,它很容易优于现有的基于静态算法的室内外检测技术,或者依赖于耗能大且不可靠的GPS。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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