Although different interaction modalities have been proposed in the field of human-computer interface (HCI), only a few of these techniques could reach the end users because of scalability and usability issues. Given the popularity and the growing number of IoT devices, selecting one out of many devices becomes a hurdle in a typical smarthome environment. Therefore, an easy-to-learn, scalable, and non-intrusive interaction modality has to be explored. In this paper, we propose a pointing approach to interact with devices, as pointing is arguably a natural way for device selection. We introduce SeleCon for device selection and control which uses an ultra-wideband (UWB) equipped smartwatch. To interact with a device in our system, people can point to the device to select it then draw a hand gesture in the air to specify a control action. To this end, SeleCon employs inertial sensors for pointing gesture detection and a UWB transceiver for identifying the selected device from ranging measurements. Furthermore, SeleCon supports an alphabet of gestures that can be used for controlling the selected devices. We performed our experiment in a 9m-by-10m lab space with eight deployed devices. The results demonstrate that SeleCon can achieve 84.5% accuracy for device selection and 97% accuracy for hand gesture recognition. We also show that SeleCon is power efficient to sustain daily use by turning off the UWB transceiver, when a user’s wrist is stationary.
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机译：尽管在人机界面（HCI）领域已提出了不同的交互方式，但是由于可伸缩性和可用性问题，这些技术中只有少数可以到达最终用户。鉴于物联网设备的普及和数量的增长，在典型的智能家居环境中，从众多设备中选择一个成为一项障碍。因此，必须探索一种易于学习，可扩展且非侵入式的交互方式。在本文中，我们提出了一种与设备交互的指向方法，因为指向可以说是设备选择的自然方法。我们介绍SeleCon用于设备选择和控制，它使用配备了超宽带（UWB）的智能手表。要与我们系统中的设备进行交互，人们可以指向该设备以选择它，然后在空中画一个手势以指定控制动作。为此，SeleCon使用惯性传感器进行指向手势检测，并使用UWB收发器从测距测量中识别所选设备。此外，SeleCon支持可用于控制所选设备的手势字母。我们在9m x 10m的实验室空间中部署了8个设备，进行了实验。结果表明，SeleCon可以达到84.5％的设备选择精度和97％的手势识别精度。我们还表明，当用户的手腕处于静止状态时，通过关闭UWB收发器，SeleCon可以有效地维持日常使用。
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