Real time indoor localization integrating a model based pedestrian dead reckoning on smartphone and BLE beacons

Mobile and pervasive computing enabled a new realm of possibilities into the indoor positioning domain. Although many candidate technologies have been proposed, no one can still adapt to every use case. A case centered design and the implementation of the solution within the specific domain is the c...

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Bibliographic Details
Published in:Journal of ambient intelligence and humanized computing 2019-01, Vol.10 (1), p.1-12
Main Authors: Ciabattoni, Lucio, Foresi, Gabriele, Monteriù, Andrea, Pepa, Lucia, Pagnotta, Daniele Proietti, Spalazzi, Luca, Verdini, Federica
Format: Article
Language:English
Subjects:
Accuracy
Algorithms
Artificial Intelligence
Beacons
Computational Intelligence
Dead reckoning
Emergency management
Engineering
Infrastructure
Kalman filters
Localization
Mobile computing
Original Research
Photogrammetry
Propagation
Real time
Robotics and Automation
Sensors
Signal strength
Smartphones
Ubiquitous computing
Ultrasonic imaging
User Interfaces and Human Computer Interaction
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Summary:Mobile and pervasive computing enabled a new realm of possibilities into the indoor positioning domain. Although many candidate technologies have been proposed, no one can still adapt to every use case. A case centered design and the implementation of the solution within the specific domain is the current research trend. With the rise of Bluetooth Low Energy (BLE) Beacons, i.e., platforms used to interact digitally with the real world, more standard positioning solutions are emerging in different contexts. However the reachable positioning accuracy with this technology is still unacceptable for some real applications (e.g., in the healthcare sector or the emergency management). In this paper, an hybrid localization application coupling a real time model based Pedestrian Dead Reckoning (PDR) technique and the analysis of the Received Signal Strength Indicator (RSSI) of BLE beacons is proposed. In particular, the smartphone application is composed by three main real time threads: a model based step length estimation, heading determination and the fusion of beacon information to reset the position and the drift error of the PDR. In order to give soundness to our approach we firstly validated the step length smartphone app with a stereo-photogrammetric system. The whole proposed solution was then tested on fifteen healthy subjects.
ISSN:1868-5137
1868-5145
DOI:10.1007/s12652-017-0579-0