ABSTRACT
Indoor positioning systems have recently gained a lot of attention for multiple reasons, including the modern construction trend of high-rise buildings in metropolitan cities, dominant voice and data services utilization in indoor environments, and the lack of positioning accuracy in traditional positioning techniques. In this chapter, we discuss the need for indoor localization, the hurdles to using outdoor positioning systems for indoor navigation, and the options available for indoor navigation. A detailed comparison of radio frequencies (RFs), and acoustic and visible light-based positioning systems is given. Furthermore, we discuss the traditional approaches which are adopted for indoor positioning. Artificial intelligence and machine learning approaches are penetrating and successfully yielding good results in many walks of life, and indoor positioning is no exception. Finally, we also present current artificial intelligence and machine learning-based techniques for indoor positioning.
