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Identifying users from the interaction with a door handle
Pervasive and Mobile Computing ( IF 4.3 ) Pub Date : 2020-11-16 , DOI: 10.1016/j.pmcj.2020.101293
Jesús Vegas , César Llamas , Manuel A. González , Carmen Hernández

Ambient intelligence pursues the integration of intelligent approaches on an IoT infrastructure, mainly using everyday objects of the environment. The main hypothesis of the work is that the way in which a user interacts with a door handle is suitable to be used in the identification task. Our proposal contributes with a new method to identify persons in a seamless and unobstrusive way, suitable to be used in a smart building scenery without the need to bring any additional device. In this case, we embed accelerometers and gyroscopes in a door handle in order to obtain a data set comprising samples of 47 individuals. A parametric approximation is adopted to reduce each sample to a feature vector by using a dynamic time warping technique. A study has been made of the outcomes of different classification techniques over six different feature sets in order to assess the feasibility of this identification challenge. The AUC values observed with the selected feature set show promising results above 0.90 using neural networks and SVM classifiers.



中文翻译:

从与门把手的互动中识别用户

环境智能主要使用环境的日常对象,致力于在物联网基础设施上集成智能方法。这项工作的主要假设是,用户与门把手互动的方式适合用于识别任务。我们的提案提出了一种新的方法,可以无缝,不干扰地识别人员,适合在智能建筑场景中使用,而无需携带任何其他设备。在这种情况下,我们将加速度计和陀螺仪嵌入门把手中,以获得包含47个人的样本的数据集。通过使用动态时间规整技术,采用参数逼近将每个样本还原为特征向量。为了评估这种识别挑战的可行性,已经对六种不同特征集上不同分类技术的结果进行了研究。使用神经网络和SVM分类器,使用所选功能集观察到的AUC值显示出令人满意的结果,高于0.90。

更新日期:2020-11-26
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