首页> 外文期刊>Automation Science and Engineering, IEEE Transactions on >Robust Location-Aware Activity Recognition Using Wireless Sensor Network in an Attentive Home
【24h】

Robust Location-Aware Activity Recognition Using Wireless Sensor Network in an Attentive Home

机译:在细心的家庭中使用无线传感器网络进行可靠的位置感知活动识别

获取原文
获取原文并翻译 | 示例

摘要

This paper presents a robust location-aware activity recognition approach for establishing ambient intelligence applications in a smart home. With observations from a variety of multimodal and unobtrusive wireless sensors seamlessly integrated into ambient-intelligence compliant objects (AICOs), the approach infers a single resident's interleaved activities by utilizing a generalized and enhanced Bayesian Network fusion engine with inputs from a set of the most informative features. These features are collected by ranking their usefulness in estimating activities of interest. Additionally, each feature reckons its corresponding reliability to control its contribution in cases of possible device failure, therefore making the system more tolerant to inevitable device failure or interference commonly encountered in a wireless sensor network, and thus improving overall robustness. This work is part of an interdisciplinary Attentive Home pilot project with the goal of fulfilling real human needs by utilizing context-aware attentive services. We have also created a novel application called ldquoActivity Maprdquo to graphically display ambient-intelligence-related contextual information gathered from both humans and the environment in a more convenient and user-accessible way. All experiments were conducted in an instrumented living lab and their results demonstrate the effectiveness of the system.
机译:本文提出了一种健壮的位置感知活动识别方法,用于在智能家居中建立环境智能应用程序。通过将多种多模态和无干扰无线传感器无缝集成到符合环境智能要求的对象(AICO)中的观察结果,该方法通过利用广义和增强的贝叶斯网络融合引擎,并结合来自一组最全面信息的输入,推断单个居民的交错活动。特征。通过对它们在估计感兴趣的活动中的有用性进行排名,来收集这些特征。此外,每个功能都考虑到其相应的可靠性,以在可能出现设备故障的情况下控制其贡献,因此使系统更能容忍无线传感器网络中常见的不可避免的设备故障或干扰,从而提高了整体鲁棒性。这项工作是跨学科的“关注家园”试点项目的一部分,其目标是通过利用上下文感知的关注服务来满足实际的人类需求。我们还创建了一个名为ldquoActivity Maprdquo的新颖应用程序,以更方便和用户可访问的方式以图形方式显示从人类和环境中收集的与环境智能相关的上下文信息。所有实验均在有仪器的生活实验室中进行,其结果证明了该系统的有效性。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号