A Survey of Indoor Localization Systems and Technologies

TLDR

Indoor localization has gained traction as IoT and ubiquitous connectivity enable a wide range of services, yet no recent survey consolidates the latest accurate and reliable systems. The paper surveys indoor localization techniques—AoA, ToF, RTOF, RSS—across WiFi, RFID, UWB, and Bluetooth, focusing on human users, highlighting strengths, and outlining remaining challenges. It evaluates systems on energy efficiency, availability, cost, range, latency, scalability, and accuracy, compares their working principles, and summarizes each system’s performance rather than merely contrasting technologies.

Abstract

Indoor localization has recently witnessed an increase in interest, due to the potential wide range of services it can provide by leveraging Internet of Things (IoT), and ubiquitous connectivity. Different techniques, wireless technologies and mechanisms have been proposed in the literature to provide indoor localization services in order to improve the services provided to the users. However, there is a lack of an up-to-date survey paper that incorporates some of the recently proposed accurate and reliable localization systems. In this paper, we aim to provide a detailed survey of different indoor localization techniques, such as angle of arrival (AoA), time of flight (ToF), return time of flight (RTOF), and received signal strength (RSS); based on technologies, such as WiFi, radio frequency identification device (RFID), ultra wideband (UWB), Bluetooth, and systems that have been proposed in the literature. This paper primarily discusses localization and positioning of human users and their devices. We highlight the strengths of the existing systems proposed in the literature. In contrast with the existing surveys, we also evaluate different systems from the perspective of energy efficiency, availability, cost, reception range, latency, scalability, and tracking accuracy. Rather than comparing the technologies or techniques, we compare the localization systems and summarize their working principle. We also discuss remaining challenges to accurate indoor localization.