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Smart city article details
| Title | Efficient Ble Fingerprinting Through Uwb Sensors For Indoor Localization |
|---|---|
| ID_Doc | 22261 |
| Authors | Zhang Q.; D'Souza M.; Balogh U.; Smallbon V. |
| Year | 2019 |
| Published | Proceedings - 2019 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Internet of People and Smart City Innovation, SmartWorld/UIC/ATC/SCALCOM/IOP/SCI 2019 |
| DOI | http://dx.doi.org/10.1109/SmartWorld-UIC-ATC-SCALCOM-IOP-SCI.2019.00065 |
| Abstract | Indoor localization through Bluetooth Low Energy (BLE) signals has attracted a lot of interest due to its simplicity in implementation and low cost in deployment. Many techniques have been developed to predict locations through received BLE signal strength. Among them, signal fingerprinting is arguably the most accurate approach. However, this solution heavily relies on high quality fingerprint mapping constructed through costly site surveying. Moreover, such established fingerprints usually need to be updated frequently when the existing environment changes drastically. In this preliminary work, we propose an efficient fingerprinting surveying system prototype through leveraging the Ultra-Wide Band localization sensors to provide accurate location information as ground truth. Our system automatically collects and uploads locations and signal strengths with minimum human interference, and thus is able to quickly and continuously build fingerprints effortlessly. We demonstrate the accuracy of our fingerprinting approach and its benefits in enabling location estimation algorithms, which achieve high prediction accuracy through extensive experiments. © 2019 IEEE. |
| Author Keywords | Bluetooth low energy; Fingerprint; Indoor localization; Ultra-wide band |
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