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Conference Paper
Comparative Analysis on WiFi-based Indoor Positioning Techniques
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- Authors
- Kyounghyun Park, Yangkoo Lee, Seonghun Seo, Jiwoo Han, Jaejun Yoo, Daesub Yoon
- Issue Date
- 2024-10
- Citation
- International Conference on Information and Communication Technology Convergence (ICTC) 2024, pp.1360-1362
- Publisher
- IEEE
- Language
- English
- Type
- Conference Paper
- Abstract
- With the proliferation of smartphones and artificial intelligence, WiFi-based indoor positioning techniques has diversified and advanced significantly. Fingerprinting techniques utilize RSSI from WiFi Access Points to estimate indoor locations. However, due to the sensitivity of WiFi signals to environmental changes, we face challenges of rebuilding fingerprint maps whenever the environment undergoes changes. Artificial intelligence techniques overcome these limitations of fingerprinting methods and enhance the accuracy of indoor positioning. Ultimately, artificial intelligence techniques improve the performance of indoor positioning techniques compared to traditional statistical methods. This paper aims to explore the performance of various artificial intelligence algorithms applied to indoor positioning and discuss how to improve the performance of indoor positioning algorithms
- KSP Keywords
- Access point, Artificial intelligence algorithms, Artificial intelligence techniques, Comparative analysis, Environmental changes, Fingerprinting technique, Positioning algorithm, Statistical methods, Wi-Fi signals, WiFi-based indoor positioning, positioning techniques