Efficient Multi-Sensor Localization for the Internet-of-Things

In the era of the Internet-of-Things (IoT), efficient localization is essential for emerging mass-market services and applications. IoT devices are heterogeneous in signaling, sensing, and mobility as well as their resources for computation and communication are typically limited. Therefore, to enable location-awareness in large-scale IoT networks, there is a need for efficient, scalable, and distributed multi-sensor fusion algorithms. This paper presents a framework to design network localization and navigation (NLN) for IoT. Multi-sensor localization and operation algorithms developed within NLN can exploit spatiotemporal cooperation, are suitable for arbitrary large network sizes, and only rely on an information exchange among neighboring devices. The advantages of NLN are evaluated in a large-scale IoT network with five hundreds agents. In particular, it is demonstrated that due to multi-sensor fusion and cooperation, the presented network localization and operation algorithms can provide attractive localization performance and reduce communication overhead and energy consumption.