Real-time Locating Systems (RTLSs) have the ability to precisely locate the position of things and people in real time. They are needed for security and emergency applications, but also for healthcare and home care appliances. The research aims for developing an analytical method to customize RTLSs, in order to improve localization performance in terms of precision. The proposed method is based on Angle of Arrival (AoA), a ranging...

Wireless sensor networks, WSN, for which development has begun by military applications, are nowadays applied to all human activities; e.g. in medicine for patience monitoring or to reduce the effects of disasters. Therefore, the WSNs area has been also one of the emerging and fast growing scientific fields. Increasing interest of WSNs is even caused by equally intense growth of interest in the Internet of Things domain, IoT, in...

The purpose of this research is to improve performance of the Hybrid Scene Analysis – Neural Network indoor localization algorithm applied in Real-time Locating System, RTLS. A properly customized structure of Neural Network and training algorithms for specific operating environment will enhance the system’s performance in terms of localization accuracy and precision. Due to nonlinearity and model complexity, a heuristic analysis...