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Location Estimation in a Smart Home: System Implementation and Evaluation Using Experimental Data

机译:智能家居中的位置估计:使用实验数据的系统实现和评估

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摘要

In the context of a constantly increasing aging population with cognitive deficiencies, insuring the autonomy of the elders at home becomes a priority. The DOMUS laboratory is addressing this issue by conceiving a smart home which can both assist people and preserve their quality of life. Obviously, the ability to monitor properly the occupant's activities and thus provide the pertinent assistance depends highly on location information inside the smart home. This paper proposes a solution to localize the occupant thanks to Bayesian filtering and a set of anonymous sensors disseminated throughout the house. The localization system is designed for a single person inside the house. It could however be used in conjunction with other localization systems in case more people are present. Our solution is functional in real conditions. We conceived an experiment to estimate precisely its accuracy and evaluate its robustness. The experiment consists of a scenario of daily routine meant to maximize the occupant's motion in meaningful activities. It was performed by 14 subjects,one subject at a time. The results are satisfactory: the system'saccuracy exceeds 85% and is independent of the occupant'sprofile. The system works in real time and behaves well inpresence of noise.
机译:在不断增长的具有认知缺陷的人口老龄化的背景下,确保老年人的自主权成为当务之急。 DOMUS实验室正在通过构思一个可以帮助人们并保持其生活质量的智能家居来解决这个问题。显然,正确监控乘员活动并因此提供相关协助的能力在很大程度上取决于智能家居内部的位置信息。本文提出了一种解决方案,可借助贝叶斯过滤和在整个房屋中分布的一组匿名传感器来对居住者进行定位。本地化系统是为房子内的一个人设计的。但是,如果有更多人,它可以与其他本地化系统结合使用。我们的解决方案可在实际条件下发挥作用。我们构想出一个实验,以精确估计其准确性并评估其鲁棒性。该实验包括一个日常场景,旨在使乘员在有意义的活动中的动作最大化。它由14名受试者表演,一次一个主题。结果令人满意:系统的准确度超过85%,并且独立于乘员的轮廓。该系统实时工作,并且在存在噪音。

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