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Smart Surface: RFID-Based Gesture Recognition Using k-Means Algorithm

机译:智能表面:使用k-Means算法的基于RFID的手势识​​别

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Elder adults may have some dependence on performing common activities like zapping on the television through a remote control (i.e. due to possible hand mobility problems). The Internet of Things (IoT), including the Radio Frequency Identification (RFID), interconnects devices to provide a higher variety of services. Together, and by applying intelligence through Machine Learning (ML) techniques, advanced applications can be implemented improving people's life. We present the Smart Surface system, relying on state of the art RFID equipment. It uses the unsupervised machine learning technique K-means clustering to detect and trigger actions by means of simple gestures, in real time and in a non-intrusive way. We implemented and evaluated a prototype of the Smart Surface system achieving an accuracy of 100% gesture recognition.
机译:老年人可能会对通过遥控器在电视上进行跳台等普通活动有所依赖(即由于可能的手部移动性问题)。包括射频识别(RFID)在内的物联网(IoT)将设备互连以提供更多种类的服务。在一起,并通过机器学习(ML)技术应用智能,可以实现高级应用程序,从而改善人们的生活。我们将依靠最先进的RFID设备展示Smart Surface系统。它使用无监督的机器学习技术K-means聚类,以简单的手势实时,非侵入式地检测和触发动作。我们实施并评估了Smart Surface系统的原型,该原型可实现100%手势识别的准确性。

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