Indoor Localisation of IoT Devices by Dynamic Radio Environment Mapping

Radiolocation within indoor environments is a challenge due to the dynamic variations caused by movement of objects and the complex multipath radio propagation. Therefore techniques that are suitable for indoor scenarios need to be robust to the multipath effects, which leads to additional power consumption and complexity. For instance, Ultra-wideband transmission can overcome multipath impact at the expense of requiring at least three access points in range with high bandwidth transmission. Such approaches are not feasible in commodity and low power IoT device tracking using legacy transmitter devices, such as WiFi or Bluetooth. Therefore, the proposed approach to address this problem is to selectively use Angle of Arrival (AoA) capabilities in access points, with the need for only two, to adaptively take measurements as compatible devices move around the environment in order to update radio maps used for optimising this process. In doing so important inferences about the dynamic environment can be exploited to adapt the measurement intervals to reduce the measurements and processing required and conserve power.