A Comprehensive Survey on Indoor Navigation System Leveraging Augumented Reality

DOI

10.2991/978-94-6239-616-6_82How to use a DOI?

Keywords

Indoor Navigation; Fingerprinting; Path Finding; Augmented Reality; Accessibility; Survey

Abstract

Indoor navigation is increasingly important for helping people move smoothly through large and complex indoor spaces such as airports, malls, universities, and hospitals. Because GPS signals are weak or unavailable inside buildings, most indoor navigation systems rely on alternative technologies, yet many of these solutions still struggle with accuracy, real-time performance, and usability—especially for individuals with visual impairments. This survey examines how augmented reality (AR)–based navigation frameworks attempt to address these challenges by combining multiple techniques for localization, path planning, and multimodal feedback. It categorizes current approaches based on the technologies they use to determine a user’s position, the algorithms that guide route selection, and the various feedback channels—visual, auditory, or haptic—that support intuitive navigation. The survey evaluates existing systems in terms of precision, robustness in dynamic environments, scalability to large spaces, and accessibility for diverse users. By comparing state-of-the-art solutions, it highlights current strengths, persistent limitations, and gaps that need further exploration. Ultimately, the survey outlines several promising research directions, including automating the creation of fingerprint databases to reduce setup effort, optimizing AR rendering pipelines to ensure real-time responsiveness on mobile devices, and integrating privacy-preserving mechanisms to protect user data. Together, these insights point toward the development of indoor navigation systems that are more accurate, efficient, inclusive, and adaptable, enabling seamless navigation experiences for a wide range of users within increasingly complex indoor environments.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - C. Vanaja
AU  - K. Pavan
AU  - M. Harishbabu
AU  - H. Nandha Gopal
PY  - 2026
DA  - 2026/03/31
TI  - A Comprehensive Survey on Indoor Navigation System Leveraging Augumented Reality
BT  - Proceedings of the International Conference on Artificial Intelligence and Secure Data Analytics (ICAISDA 2025)
PB  - Atlantis Press
SP  - 1128
EP  - 1137
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6239-616-6_82
DO  - 10.2991/978-94-6239-616-6_82
ID  - Vanaja2026
ER  -