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Ambient water usage sensor for the identification of daily activities

机译:环境用水量传感器,用于识别日常活动

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Dementia patients, like most older adults, prefer to live in their own home as long as possible. This requires, however, that they are able to perform activities of daily living (ADL). Therefore, many research projects install different sensor setups to identify ADLs. Though the water usage correlates with many ADLs (i.e.: bathing, cooking) only few of these systems use water usage sensors. The reason is that there is no water usage sensor available that is unobtrusive, ambient and precise. In this article, we propose a water usage sensor that is based on a piezoelectric element that fulfills these requirements. We describe the implementation of the sensor system in a living lab. Additionally, we discuss different features that were extracted from the sensor signal and different machine learning algorithms that were used to classify the data. Finally, we present the results to several tests we performed to determine the accuracy of our sensor system under different environmental conditions.
机译:像大多数老年人一样,痴呆症患者喜欢尽可能长时间地呆在自己的家中。但是,这要求他们能够执行日常生活活动(ADL)。因此,许多研究项目都安装了不同的传感器设置来识别ADL。尽管用水量与许多ADL(即沐浴,煮饭)有关,但这些系统中只有很少的系统使用用水量传感器。原因是没有可用的用水量传感器不引人注目,环境和精确。在本文中,我们提出了一种用水量传感器,该传感器基于满足这些要求的压电元件。我们描述了在生活实验室中传感器系统的实现。此外,我们讨论了从传感器信号中提取的不同特征以及用于对数据进行分类的不同机器学习算法。最后,我们将结果提供给我们执行的多项测试,以确定在不同环境条件下传感器系统的精度。

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