IndoorWaze: A Crowdsourcing-Based Context-Aware Indoor Navigation System
Autor: | Yanchao Zhang, Rui Zhang, Tao Li, Terri Hedgpeth, Dianqi Han, Yimin Chen |
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Rok vydání: | 2020 |
Předmět: |
Computer science
business.industry Applied Mathematics Shopping mall Real-time computing Navigation system 020206 networking & telecommunications 02 engineering and technology Floor plan Crowdsourcing Computer Science Applications 0202 electrical engineering electronic engineering information engineering Wireless Electrical and Electronic Engineering Android (operating system) business |
Zdroj: | IEEE Transactions on Wireless Communications. 19:5461-5472 |
ISSN: | 1558-2248 1536-1276 |
Popis: | Indoor navigation systems are very useful in large complex indoor environments such as shopping malls. Current systems focus on improving indoor localization accuracy and must be combined with an accurate labeled floor plan to provide usable indoor navigation services. Such labeled floor plans are often unavailable or involve a prohibitive cost to manually obtain. In this paper, we present IndoorWaze, a novel crowdsourcing-based context-aware indoor navigation system that can automatically generate an accurate context-aware floor plan with labeled indoor POIs for the first time in literature. IndoorWaze combines the Wi-Fi fingerprints of indoor walkers with the Wi-Fi fingerprints and POI labels provided by POI employees to produce a high-fidelity labeled floor plan. As a lightweight crowdsourcing-based system, IndoorWaze involves very little effort from indoor walkers and POI employees. We prototype IndoorWaze on Android smartphones and evaluate it in a large shopping mall. Our results show that IndoorWaze can generate a high-fidelity labeled floor plan, in which all the stores are correctly labeled and arranged, all the pathways and crossings are correctly shown, and the median estimation error for the store dimension is below 12%. |
Databáze: | OpenAIRE |
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