为手机在线活动识别的比较研究定义路线图

M. Shoaib, S. Bosch, Özlem Durmaz Incel, H. Scholten, P. Havinga
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引用次数: 6

摘要

许多基于活动识别的上下文感知应用程序目前正在使用手机。大部分工作都是以离线的方式完成的。然而,在最近的研究中,有一种转向在线方法的转变,即在移动电话上实施活动识别系统。不幸的是,这些研究大多缺乏适当的可重复性、资源消耗分析、验证、位置独立性和个性化。而且由于实验设置的不同,在很多方面很难进行比较。在本文中,我们简要概述了目前使用手机进行在线活动识别的研究,并强调了它们的局限性。我们将从实验设置、位置独立性、资源消耗分析、性能评估和验证等方面讨论这些研究。基于这一分析,我们定义了一个路线图,以更好地利用手机进行在线活动识别的比较研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Defining a roadmap towards comparative research in online activity recognition on mobile phones
Many context-aware applications based on activity recognition are currently using mobile phones. Most of this work is done in an offline way. However, there is a shift towards an online approach in recent studies, where activity recognition systems are implemented on mobile phones. Unfortunately, most of these studies lack proper reproducibility, resource consumption analysis, validation, position-independence, and personalization. Moreover, they are hard to compare in various aspects due to different experimental setups. In this paper, we present a short overview of the current research on online activity recognition using mobile phones, and highlight their limitations. We discuss these studies in terms of various aspects, such as their experimental setups, position-independence, resource consumption analysis, performance evaluation, and validation. Based on this analysis, we define a roadmap towards a better comparative research on online activity recognition using mobile phones.
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