3D Passive-Vision-Aided Pedestrian Dead Reckoning for Indoor Positioning

The vision-aided Pedestrian Dead Reckoning (PDR) systems have become increasingly popular, thanks to the ubiquitous mobile phone embedded with several sensors. This is particularly important for indoor use, where other indoor positioning technologies require additional installation or body-attachment of specific sensors. This paper proposes and develops a novel 3D Passive Vision-aided PDR system that uses multiple surveillance cameras and smartphone-based PDR. The proposed system can continuously track users’ movement on different floors by integrating results of inertial navigation and Faster R-CNN-based real-time pedestrian detection, while utilizing existing camera locations and embedded barometers to provide floor/height information to identify user positions in 3D space. This novel system provides a relatively low-cost and user-friendly solution, which requires no modifications to currently available mobile devices and also the existing indoor infrastructures available at many public buildings for the purpose of 3D indoor positioning. This paper shows the case of testing the prototype in a four-floor building, where it can provide the horizontal accuracy of 0.16m and the vertical accuracy of 0.5m. This level of accuracy is even better than required accuracy targeted by several emergency services, including the Federal Communications Commission (FCC). This system is developed for both Android and iOS-running devices

A review of smartphones based indoor positioning: challenges and applications

The continual proliferation of mobile devices has encouraged much effort in using the smartphones for indoor positioning. This article is dedicated to review the most recent and interesting smartphones based indoor navigation systems, ranging from electromagnetic to inertia to visible light ones, with an emphasis on their unique challenges and potential real-world applications. A taxonomy of smartphones sensors will be introduced, which serves as the basis to categorise different positioning systems for reviewing. A set of criteria to be used for the evaluation purpose will be devised. For each sensor category, the most recent, interesting and practical systems will be examined, with detailed discussion on the open research questions for the academics, and the practicality for the potential clients

An indoor navigation architecture using variable data sources for blind and visually impaired persons

Contrary to outdoor positioning and navigation systems, there isn’t a counterpart global solution for indoor environments. Usually, the deployment of an indoor positioning system must be adapted case by case, according to the infrastructure and the objective of the localization. A particularly delicate case is related with persons who are blind or visually impaired. A robust and easy to use indoor navigation solution would be extremely useful, but this would also be particularly difficult to develop, given the special requirements of the system that would have to be more accurate and user friendly than a general solution. This paper presents a contribute to this subject, by proposing a hybrid indoor positioning system adaptable to the surrounding indoor structure, and dealing with different types of signals to increase accuracy. This would permit lower the deployment costs, since it could be done gradually, beginning with the likely existing Wi-Fi infrastructure to get a fairy accuracy up to a high accuracy using visual tags and NFC tags when necessary and possible.info:eu-repo/semantics/publishedVersio

Barometric phone sensors: More hype than hope!

Singapore National Research Foundation under International Research Centre @ Singapore Funding Initiative; Ministry of Education, Singapore under its Academic Research Funding Tier

SELF-CALIBRATING PARTICIPATORY WIRELESS INDOOR LOCALIZATION

Ph.DDOCTOR OF PHILOSOPH

The smartphone-based offline indoor location competition at IPIN 2016: analysis and future work

This paper presents the analysis and discussion of the off-site localization competition track, which took place during the Seventh International Conference on Indoor Positioning and Indoor Navigation (IPIN 2016). Five international teams proposed different strategies for smartphone-based indoor positioning using the same reference data. The competitors were provided with several smartphone-collected signal datasets, some of which were used for training (known trajectories), and others for evaluating (unknown trajectories). The competition permits a coherent evaluation method of the competitors' estimations, where inside information to fine-tune their systems is not offered, and thus provides, in our opinion, a good starting point to introduce a fair comparison between the smartphone-based systems found in the literature. The methodology, experience, feedback from competitors and future working lines are described.We would like to thank Tecnalia Research & Innovation Foundation for sponsoring the competition track with an award for the winning team. We are also grateful to Francesco Potortì, Sangjoon Park, Jesús Ureña and Kyle O’Keefe for their invaluable help in promoting the IPIN competition and conference. Parts of this work was carried out with the financial support received from projects and grants: LORIS (TIN2012-38080-C04-04), TARSIUS (TIN2015-71564-C4-2-R (MINECO/FEDER)), SmartLoc (CSIC-PIE Ref.201450E011), “Metodologías avanzadas para el diseño, desarrollo, evaluación e integración de algoritmos de localización en interiores” (TIN2015-70202-P), REPNIN network (TEC2015-71426-REDT) and the José Castillejo mobility grant (CAS16/00072). The HFTS team has been supported in the frame of the German Federal Ministry of Education and Research programme “FHprofUnt2013” under contract 03FH035PB3 (Project SPIRIT). The UMinho team has been supported by COMPETE: POCI-01-0145-FEDER-007043 and FCT — Fundação para a Ciência e Tecnologia within the Project Scope: UID/CEC/00319/2013.info:eu-repo/semantics/publishedVersio