Wearable indoor localisation approach in Internet of Things

Localisation is an essential and important research issue in Internet of Things (IoT). Most localisation schemes focus on outdoor IoT. However, indoor IoT is required in some applications such as target detection and tracking, and emerging smarter healthcare. As such, localisation approaches designed for indoor IoT are necessary. Note that the smarter healthcare emerges at an unprecedented speed while few localisation schemes can be directly exploited for them with accuracy guarantee. In this study, the authors propose a wearable indoor localisation approach to improve the localisation accuracy of previous work. In this approach, the wearable devices embedded into person are used to realise their displacement vector in mobile environments, thus estimating their own locations. In addition, the authors propose a walking prediction mechanism to increase localisation accuracy. The real-world experiment results demonstrate that the proposed approach achieves lower localisation error in various moving speeds.