[Paper Review] A Survey of Indoor Localization Systems and Technologies

Faheem Zafari, Athanasios Gkelias+1 more|arXiv (Cornell University)|Sep 4, 2017

Indoor and Outdoor Localization Technologies144 references182 citations

TL;DR

This survey reviews indoor localization techniques (AoA, ToF, RSS, CSI, etc.) across technologies (WiFi, RFID, UWB, BLE, etc.), evaluating systems by energy, availability, cost, range, latency, scalability, and tracking accuracy, and discusses IoT integration and remaining challenges.

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), 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. The 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.

Motivation & Objective

• Summarize indoor localization techniques and signal metrics used for localization (RSSI, CSI, AoA, ToF, TDoA, RToF, PoA) and fingerprinting methods.
• Survey technologies and systems enabling indoor localization (WiFi, Bluetooth, Zigbee, RFID, UWB, visible light, acoustics).
• Evaluate localization systems using an explicit framework across energy efficiency, availability, cost, range, latency, scalability, and accuracy.
• Discuss IoT opportunities and challenges for indoor localization, and contrast short-range versus long-range IoT technologies.

Proposed method

• Provide a taxonomy of localization techniques (RSSI, CSI, AoA, ToF, TDoA, RToF, PoA) and fingerprinting/scene analysis.
• Discuss technology options (WiFi, Bluetooth, Zigbee, RFID, UWB, VLC, acoustic) and their localization implications.
• Introduce an evaluation framework for comparing systems on multiple metrics (availability, cost, energy, range, latency, scalability, accuracy).
• Offer a primer on IoT and analyze emerging IoT technologies for indoor localization viability (sub-meter goals).
• Survey existing localization systems from 1997–2016/2018 and assess them against the framework.

Experimental results

Research questions

• RQ1 What are the main localization techniques and their operational principles across indoor environments?
• RQ2 How do different technologies (WiFi, BLE, RFID, UWB, etc.) support indoor localization, and what are their strengths and limitations?
• RQ3 How can an unified evaluation framework compare indoor localization systems across energy, cost, availability, range, latency, scalability, and accuracy?
• RQ4 What are the challenges and opportunities of integrating IoT technologies with indoor localization?
• RQ5 What are the remaining gaps and future directions for accurate indoor localization?

Key findings

• WiFi-based localization has achieved sub-meter accuracy in recent systems (median around 23 cm in cited works).
• CSI offers robustness to multipath and indoor noise, but is not readily available on off-the-shelf NICs.
• There is a trade-off between fingerprinting granularity and environmental stability over time, with fingerprints being sensitive to environmental changes.
• An explicit, generic evaluation framework helps compare diverse localization systems across energy, cost, availability, latency, range, scalability, and accuracy.
• IoT technologies are not yet suitable for sub-meter indoor localization, highlighting the need for collaboration between short- and long-range IoT approaches.
• The survey covers a broad spectrum of techniques (RSSI, ToF, TDoA, RToF, AoA, PoA) and emphasizes system-level evaluation over mere technique comparison.