论文标题
使用灯泡网络启用无缝设备与DevLoc进行室内IoT环境的关联
Enabling Seamless Device Association with DevLoc using Light Bulb Networks for Indoor IoT Environments
论文作者
论文摘要
为了启用室内IoT环境的偶然性交互，自发设备关联特别有趣，因此用户以临时的方式建立了连接。基于光信号的相似性，我们的名为DevLoc的系统利用了我们周围无处不在的光源来执行连续和无缝的设备分组。我们提供了一个配置框架，以通过自定义的可见光通信管理照明基础架构来控制用户接近的空间粒度。为了实现基于接近度或基于位置的服务，我们支持不同实体之间的两种设备关联模式：设备到设备和设备之间的区域。关于设备分组的最佳性能方法，与距离和相关指标相比，基于机器学习的信号相似性通常是最佳的。此外，我们通过识别语义设备组（例如个人和陌生人的设备）来分析设备关联的模式，以改善数据隐私，从而允许自动数据共享策略。
To enable serendipitous interaction for indoor IoT environments, spontaneous device associations are of particular interest so that users set up a connection in an ad-hoc manner. Based on the similarity of light signals, our system named DevLoc takes advantage of ubiquitous light sources around us to perform continuous and seamless device grouping. We provide a configuration framework to control the spatial granularity of user's proximity by managing the lighting infrastructure through customized visible light communication. To realize either proximity-based or location-based services, we support two modes of device associations between different entities: device-to-device and device-to-area. Regarding the best performing method for device grouping, machine learning-based signal similarity performs in general best compared to distance and correlation metrics. Furthermore, we analyze patterns of device associations to improve the data privacy by recognizing semantic device groups, such as personal and stranger's devices, allowing automated data sharing policies.
