Wireless Sensor Network Self-Localisation using Context information.

Wireless sensor networks (WSNs) are a key enabler for Internet of Things (IoT) applications in many different industries such as logistics, healthcare, agriculture, smart homes and smart vehicles. The location of one or more of the devices (nodes) in the network is interesting if not crucial information for the application. For this reason, algorithms for the self-localization of wireless sensor networks have been developed which are capable of automatically determining the position of the static nodes relative to each other. However, these methods are not equipped to effectively define a distance estimate in complex environments. Moreover, path loss exponents should be adapted to each link between the nodes in particular for better results. We hypothesize that we can model both the location and signal attenuation of WSN nodes so that the individual communication link distances can be ascribed to node mobility or environmental changes by incorporating context information such as environment layout or likely node locations.

Keywords:WIRELESS NETWORKS, SENSOR NETWORKS, REAL-TIME LOCALIZATION SYSTEMS, LOCALISATION

Disciplines:Wireless communication and positioning systems