2019
Mendoza-Silva, Germán MartÃn; Matey-Sanz, Miguel; Torres-Sospedra, JoaquÃn; Huerta-Guijarro, JoaquÃn
BLE RSS Measurements Dataset for Research on Accurate Indoor Positioning Journal Article
In: Data, vol. 4, no. 1, pp. 12, 2019, ISSN: 2306-5729.
Abstract | Links | BibTeX | Tags: academic libraries, Indoor positioning, Wi-Fi fingerprint
@article{germanb,
title = {BLE RSS Measurements Dataset for Research on Accurate Indoor Positioning},
author = {Germán MartÃn Mendoza-Silva and Miguel Matey-Sanz and JoaquÃn Torres-Sospedra and JoaquÃn Huerta-Guijarro},
doi = {https://doi.org/10.3390/data4010012},
issn = {2306-5729},
year = {2019},
date = {2019-01-04},
urldate = {2019-01-04},
journal = {Data},
volume = {4},
number = {1},
pages = {12},
abstract = {RSS-based indoor positioning is a consolidated research field for which several techniques have been proposed. Among them, Bluetooth Low Energy (BLE) beacons are a popular option for practical applications. This paper presents a new BLE RSS database that was created to aid in the development of new BLE RSS-based positioning methods and to encourage their reproducibility and comparability. The measurements were collected in two university zones: an area among bookshelves in a library and an area of an office space. Each zone had its own batch of deployed iBKS 105 beacons, configured to broadcast advertisements every 200 ms. The collection in the library zone was performed using three Android smartphones of different brands and models, with beacons broadcasting at −12 dBm transmission power, while in the other zone the collection was performed using of one those smartphones with beacons configured to advertise at the −4 dBm, −12 dBm and −20 dBm transmission powers. Supporting materials and scripts are provided along with the database, which annotate the BLE readings, provide details on the collection, the environment, and the BLE beacon deployments, ease the database usage, and introduce the reader to BLE RSS-based positioning and its challenges. The BLE RSS database and its supporting materials are available at the Zenodo repository under the open-source MIT license.},
keywords = {academic libraries, Indoor positioning, Wi-Fi fingerprint},
pubstate = {published},
tppubtype = {article}
}
RSS-based indoor positioning is a consolidated research field for which several techniques have been proposed. Among them, Bluetooth Low Energy (BLE) beacons are a popular option for practical applications. This paper presents a new BLE RSS database that was created to aid in the development of new BLE RSS-based positioning methods and to encourage their reproducibility and comparability. The measurements were collected in two university zones: an area among bookshelves in a library and an area of an office space. Each zone had its own batch of deployed iBKS 105 beacons, configured to broadcast advertisements every 200 ms. The collection in the library zone was performed using three Android smartphones of different brands and models, with beacons broadcasting at −12 dBm transmission power, while in the other zone the collection was performed using of one those smartphones with beacons configured to advertise at the −4 dBm, −12 dBm and −20 dBm transmission powers. Supporting materials and scripts are provided along with the database, which annotate the BLE readings, provide details on the collection, the environment, and the BLE beacon deployments, ease the database usage, and introduce the reader to BLE RSS-based positioning and its challenges. The BLE RSS database and its supporting materials are available at the Zenodo repository under the open-source MIT license.
2018
Torres-Sospedra, JoaquÃn; Richter, Philipp; Mendoza-Silva, Germán MartÃn; Lohan, Elena Simona; Huerta-Guijarro, JoaquÃn
Supporting Materials for Characterising the Alteration in the AP Distribution with the RSS Distance and the Position Estimates Proceedings Article
In: Proceedings of the Ninth International Conference on Indoor Positioning and Indoor Navigation (IPIN), 2018, pp. 1-7, IEEE, 2018, ISBN: 978-1-5386-5635-8/18.
Abstract | Links | BibTeX | Tags: Indoor positioning
@inproceedings{zenodo2018ipin,
title = {Supporting Materials for Characterising the Alteration in the AP Distribution with the RSS Distance and the Position Estimates},
author = {JoaquÃn Torres-Sospedra and Philipp Richter and Germán MartÃn Mendoza-Silva and Elena Simona Lohan and JoaquÃn Huerta-Guijarro},
url = {https://doi.org/10.5281/zenodo.1305414},
doi = {10.5281/zenodo.1305414},
isbn = {978-1-5386-5635-8/18},
year = {2018},
date = {2018-07-01},
booktitle = {Proceedings of the Ninth International Conference on Indoor Positioning and Indoor Navigation (IPIN), 2018},
number = {art. no. 8533791 },
pages = {1-7},
publisher = {IEEE},
abstract = {Fingerprinting is widely used for indoor positioning, where pattern matching techniques are usually applied to signals from APs or Beacons. However, the real-time monitoring of the emitters is not an easy task in most cases. When an alteration in the emitters is not detected or properly fixed, it might have a severe impact in the accuracy of the indoor positioning algorithm. Simple but common alterations are energy failure, emitter replacement, wrong emitter placement after maintenance and AP displacement. This paper explores how the AP alteration might be automatically detected by computing the average of the RSS distance to the best match over multiple operational points. The experimental setup consider one simulated and two real scenarios to validate the proposed metric for detecting AP alternation. The results show that it is possible to detect AP alteration when it has a considerable impact in the IPS accuracy},
keywords = {Indoor positioning},
pubstate = {published},
tppubtype = {inproceedings}
}
Fingerprinting is widely used for indoor positioning, where pattern matching techniques are usually applied to signals from APs or Beacons. However, the real-time monitoring of the emitters is not an easy task in most cases. When an alteration in the emitters is not detected or properly fixed, it might have a severe impact in the accuracy of the indoor positioning algorithm. Simple but common alterations are energy failure, emitter replacement, wrong emitter placement after maintenance and AP displacement. This paper explores how the AP alteration might be automatically detected by computing the average of the RSS distance to the best match over multiple operational points. The experimental setup consider one simulated and two real scenarios to validate the proposed metric for detecting AP alternation. The results show that it is possible to detect AP alteration when it has a considerable impact in the IPS accuracy
Torres-Sospedra, JoaquÃn; Richter, Philipp; Mendoza-Silva, Germán MartÃn; Lohan, Elena Simona; Huerta-Guijarro, JoaquÃn
Characterising the Alteration in the AP Distribution with the RSS Distance and the Position Estimates Proceedings Article
In: Proceedings of the Ninth International Conference on Indoor Positioning and Indoor Navigation (IPIN), 2018.
BibTeX | Tags: Indoor positioning
@inproceedings{ipin2018characterizing,
title = {Characterising the Alteration in the AP Distribution with the RSS Distance and the Position Estimates},
author = {JoaquÃn Torres-Sospedra and Philipp Richter and Germán MartÃn Mendoza-Silva and Elena Simona Lohan and JoaquÃn Huerta-Guijarro},
year = {2018},
date = {2018-01-01},
booktitle = {Proceedings of the Ninth International Conference on Indoor Positioning and Indoor Navigation (IPIN)},
keywords = {Indoor positioning},
pubstate = {published},
tppubtype = {inproceedings}
}
Mendoza-Silva, Germán MartÃn; Torres-Sospedra, JoaquÃn; Huerta-Guijarro, JoaquÃn
Locations Selection for Periodic Radio Map Update in WiFi Fingerprinting Conference
Progress in Location Based Services 2018, Springer International Publishing, Cham, 2018, ISBN: 978-3-319-71470-7.
Abstract | Links | BibTeX | Tags: Indoor positioning, Wi-Fi fingerprint
@conference{Mendoza-Silva2018,
title = {Locations Selection for Periodic Radio Map Update in WiFi Fingerprinting},
author = {Germán MartÃn Mendoza-Silva and JoaquÃn Torres-Sospedra and JoaquÃn Huerta-Guijarro},
editor = {Kiefer, Peter and Huang, Haosheng and Van de Weghe, Nico and Raubal, Martin},
url = {https://doi.org/10.1007/978-3-319-71470-7_1},
doi = {10.1007/978-3-319-71470-7_1},
isbn = {978-3-319-71470-7},
year = {2018},
date = {2018-01-01},
booktitle = {Progress in Location Based Services 2018},
pages = {3-24},
publisher = {Springer International Publishing},
address = {Cham},
abstract = {The construction and update of a radio map are usually referred as the main drawbacks of WiFi fingerprinting, a very popular method in indoor localization research. For radio map update, some studies suggest taking new measurements at some random locations, usually from the ones used in the radio map construction. In this paper, we argue that the locations should not be random, and propose how to determine them. Given the set locations where the measurements used for the initial radio map construction were taken, a subset of locations for the update measurements is chosen through optimization so that the remaining locations found in the initial measurements are best approximated through regression. The regression method is Support Vector Regression (SVR) and the optimization is achieved using a genetic algorithm approach. We tested our approach using a database of WiFi measurements collected at a relatively dense set of locations during ten months in a university library setting. The experiments results show that, if no dramatic event occurs (e.g., relevant WiFi networks are changed), our approach outperforms other strategies for determining the collection locations for periodic updates. We also present a clear guide on how to conduct the radio map updates.},
keywords = {Indoor positioning, Wi-Fi fingerprint},
pubstate = {published},
tppubtype = {conference}
}
The construction and update of a radio map are usually referred as the main drawbacks of WiFi fingerprinting, a very popular method in indoor localization research. For radio map update, some studies suggest taking new measurements at some random locations, usually from the ones used in the radio map construction. In this paper, we argue that the locations should not be random, and propose how to determine them. Given the set locations where the measurements used for the initial radio map construction were taken, a subset of locations for the update measurements is chosen through optimization so that the remaining locations found in the initial measurements are best approximated through regression. The regression method is Support Vector Regression (SVR) and the optimization is achieved using a genetic algorithm approach. We tested our approach using a database of WiFi measurements collected at a relatively dense set of locations during ten months in a university library setting. The experiments results show that, if no dramatic event occurs (e.g., relevant WiFi networks are changed), our approach outperforms other strategies for determining the collection locations for periodic updates. We also present a clear guide on how to conduct the radio map updates.
Mendoza-Silva, Germán MartÃn; Richter, Philipp; Torres-Sospedra, JoaquÃn; Lohan, Elana Simona; Huerta-Guijarro, JoaquÃn
Long-Term WiFi Fingerprinting Dataset for Research on Robust Indoor Positioning Journal Article
In: Data, vol. 3, no. 1, pp. 3, 2018, ISSN: 2306-5729.
Abstract | Links | BibTeX | Tags: Indoor positioning, Wi-Fi fingerprint
@article{data3010003,
title = {Long-Term WiFi Fingerprinting Dataset for Research on Robust Indoor Positioning},
author = {Germán MartÃn Mendoza-Silva and Philipp Richter and JoaquÃn Torres-Sospedra and Elana Simona Lohan and JoaquÃn Huerta-Guijarro},
url = {http://www.mdpi.com/2306-5729/3/1/3},
doi = {10.3390/data3010003},
issn = {2306-5729},
year = {2018},
date = {2018-01-01},
journal = {Data},
volume = {3},
number = {1},
pages = {3},
abstract = {WiFi fingerprinting, one of the most popular methods employed in indoor positioning, currently faces two major problems: lack of robustness to short and long time signal changes and difficult reproducibility of new methods presented in the relevant literature. This paper presents a WiFi RSS (Received Signal Strength) database created to foster and ease research works that address the above-mentioned two problems. A trained professional took several consecutive fingerprints while standing at specific positions and facing specific directions. The consecutive fingerprints may enable the study of short-term signals variations. The data collection spanned over 15 months, and, for each month, one type of training datasets and five types of test datasets were collected. The measurements of a dataset type (training or test) were taken at the same positions and directions every month, in order to enable the analysis of long-term signal variations. The database is provided with supporting materials and software, which give more information about the collection environment and eases the database utilization, respectively. The WiFi measurements and the supporting materials are available at the Zenodo repository under the open-source MIT license.},
keywords = {Indoor positioning, Wi-Fi fingerprint},
pubstate = {published},
tppubtype = {article}
}
WiFi fingerprinting, one of the most popular methods employed in indoor positioning, currently faces two major problems: lack of robustness to short and long time signal changes and difficult reproducibility of new methods presented in the relevant literature. This paper presents a WiFi RSS (Received Signal Strength) database created to foster and ease research works that address the above-mentioned two problems. A trained professional took several consecutive fingerprints while standing at specific positions and facing specific directions. The consecutive fingerprints may enable the study of short-term signals variations. The data collection spanned over 15 months, and, for each month, one type of training datasets and five types of test datasets were collected. The measurements of a dataset type (training or test) were taken at the same positions and directions every month, in order to enable the analysis of long-term signal variations. The database is provided with supporting materials and software, which give more information about the collection environment and eases the database utilization, respectively. The WiFi measurements and the supporting materials are available at the Zenodo repository under the open-source MIT license.
2017
Lohan, Elena Simona; Torres-Sospedra, JoaquÃn; Leppäkoski, Helena; Richter, Philipp; Peng, Zhe; Huerta-Guijarro, JoaquÃn
Wi-Fi Crowdsourced Fingerprinting Dataset for Indoor Positioning Journal Article
In: Data, vol. 2, no. 4, ARTICLE NUMBER = 32, 2017, ISSN: 2306-5729.
Abstract | Links | BibTeX | Tags: Indoor positioning, Wi-Fi fingerprint
@article{data2040032,
title = {Wi-Fi Crowdsourced Fingerprinting Dataset for Indoor Positioning},
author = {Elena Simona Lohan and JoaquÃn Torres-Sospedra and Helena Leppäkoski and Philipp Richter and Zhe Peng and JoaquÃn Huerta-Guijarro},
url = {http://www.mdpi.com/2306-5729/2/4/32},
doi = {10.3390/data2040032},
issn = {2306-5729},
year = {2017},
date = {2017-10-03},
journal = {Data},
volume = {2},
number = {4, ARTICLE NUMBER = 32},
abstract = {Benchmark open-source Wi-Fi fingerprinting datasets for indoor positioning studies are still hard to find in the current literature and existing public repositories. This is unlike other research fields, such as the image processing field, where benchmark test images such as the Lenna image or Face Recognition Technology (FERET) databases exist, or the machine learning field, where huge datasets are available for example at the University of California Irvine (UCI) Machine Learning Repository. It is the purpose of this paper to present a new openly available Wi-Fi fingerprint dataset, comprised of 4648 fingerprints collected with 21 devices in a university building in Tampere, Finland, and to present some benchmark indoor positioning results using these data. The datasets and the benchmarking software are distributed under the open-source MIT license and can be found on the EU Zenodo repository.},
keywords = {Indoor positioning, Wi-Fi fingerprint},
pubstate = {published},
tppubtype = {article}
}
Benchmark open-source Wi-Fi fingerprinting datasets for indoor positioning studies are still hard to find in the current literature and existing public repositories. This is unlike other research fields, such as the image processing field, where benchmark test images such as the Lenna image or Face Recognition Technology (FERET) databases exist, or the machine learning field, where huge datasets are available for example at the University of California Irvine (UCI) Machine Learning Repository. It is the purpose of this paper to present a new openly available Wi-Fi fingerprint dataset, comprised of 4648 fingerprints collected with 21 devices in a university building in Tampere, Finland, and to present some benchmark indoor positioning results using these data. The datasets and the benchmarking software are distributed under the open-source MIT license and can be found on the EU Zenodo repository.
Lohan, Elena Simona; Torres-Sospedra, JoaquÃn; Richter, Philipp; Leppäkoski, Helena; Huerta-Guijarro, JoaquÃn; Cramariuc, Andrei
Crowdsourced WiFi database and benchmark software for indoor positioning Miscellaneous
2017.
Links | BibTeX | Tags: crowdsourcing, Indoor positioning, Wi-Fi
@misc{zenodo2017crddb,
title = {Crowdsourced WiFi database and benchmark software for indoor positioning},
author = {Elena Simona Lohan and JoaquÃn Torres-Sospedra and Philipp Richter and Helena Leppäkoski and JoaquÃn Huerta-Guijarro and Andrei Cramariuc},
url = {https://doi.org/10.5281/zenodo.889797},
doi = {10.5281/zenodo.889797},
year = {2017},
date = {2017-01-01},
keywords = {crowdsourcing, Indoor positioning, Wi-Fi},
pubstate = {published},
tppubtype = {misc}
}
2016
Torres-Sospedra, JoaquÃn; Mendoza-Silva, Germán MartÃn; Montoliu-Colás, Raúl; Belmonte-Fernández, Óscar; BenÃtez-Paéz, Fernando; Huerta-Guijarro, JoaquÃn
Ensembles of Indoor Positioning Systems Based on Fingerprinting: Simplifying Parameter Selection and Obtaining Robust Systems Proceedings Article
In: Proceedings of the Seventh International Conference on Indoor Positioning and Indoor Navigation IPIN 2016, University of Alcala, Alcalá de Henares (Madrid), Spain October 4-7, 2016, pp. in press, 2016.
BibTeX | Tags: GEO-C, Indoor positioning, Wi-Fi fingerprint
@inproceedings{TorresSospedra2016a,
title = {Ensembles of Indoor Positioning Systems Based on Fingerprinting: Simplifying Parameter Selection and Obtaining Robust Systems},
author = { JoaquÃn Torres-Sospedra and Germán MartÃn Mendoza-Silva and Raúl Montoliu-Colás and Óscar Belmonte-Fernández and Fernando BenÃtez-Paéz and JoaquÃn Huerta-Guijarro},
year = {2016},
date = {2016-01-01},
booktitle = {Proceedings of the Seventh International Conference on Indoor Positioning and Indoor Navigation IPIN 2016, University of Alcala, Alcalá de Henares (Madrid), Spain October 4-7, 2016},
pages = {in press},
keywords = {GEO-C, Indoor positioning, Wi-Fi fingerprint},
pubstate = {published},
tppubtype = {inproceedings}
}
Torres-Sospedra, JoaquÃn; Montoliu-Colás, Raúl; Mendoza-Silva, Germán MartÃn; Belmonte-Fernández, Óscar; Rambla-Risueño, David; Huerta-Guijarro, JoaquÃn
Providing Databases for Different Indoor Positioning Technologies: Pros and Cons of Magnetic field and Wi-Fi based Positioning Journal Article
In: Mobile information systems, pp. in press, 2016, (IF: 0.849 121/146 (Q4) Computer science – information systems 0.849 79/89 (Q4) Telecommunications ).
BibTeX | Tags: Database, Indoor positioning, Magnetic field, REPNIN, Wi-Fi fingerprint
@article{TorresSospedra2016b,
title = {Providing Databases for Different Indoor Positioning Technologies: Pros and Cons of Magnetic field and Wi-Fi based Positioning},
author = { JoaquÃn Torres-Sospedra and Raúl Montoliu-Colás and Germán MartÃn Mendoza-Silva and Óscar Belmonte-Fernández and David Rambla-Risueño and JoaquÃn Huerta-Guijarro},
year = {2016},
date = {2016-01-01},
journal = {Mobile information systems},
pages = {in press},
note = {IF: 0.849 121/146 (Q4) Computer science – information systems
0.849 79/89 (Q4) Telecommunications
},
keywords = {Database, Indoor positioning, Magnetic field, REPNIN, Wi-Fi fingerprint},
pubstate = {published},
tppubtype = {article}
}
2015
Torres-Sospedra, JoaquÃn; Avariento-Vicent, Joan Pere; Rambla-Risueño, David; Montoliu-Colás, Raúl; Casteleyn, Sven; Benedito-Bordonau, Mauricia; Gould, Michael; Huerta-Guijarro, JoaquÃn
Enhancing integrated indoor/outdoor mobility in a smart campus Journal Article
In: International Journal of Geographical Information Science, vol. 29, no. 11, pp. 1955–1968, 2015, ISSN: 1365-8816, (IF: 2.065, Q1).
Abstract | Links | BibTeX | Tags: augmented reality, Indoor positioning, mobile GIS, Smart Campus
@article{TorresSospedra2015,
title = {Enhancing integrated indoor/outdoor mobility in a smart campus},
author = { JoaquÃn Torres-Sospedra and Joan Pere Avariento-Vicent and David Rambla-Risueño and Raúl Montoliu-Colás and Sven Casteleyn and Mauricia Benedito-Bordonau and Michael Gould and JoaquÃn Huerta-Guijarro},
url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-84942195059&partnerID=tZOtx3y1},
doi = {10.1080/13658816.2015.1049541},
issn = {1365-8816},
year = {2015},
date = {2015-01-01},
journal = {International Journal of Geographical Information Science},
volume = {29},
number = {11},
pages = {1955--1968},
abstract = {A Smart City relies on six key factors: Smart Governance, Smart People, Smart Economy, Smart Environment, Smart Living and Smart Mobility. This paper focuses on Smart Mobility by improving one of its key components: positioning. We developed and deployed a novel indoor positioning system (IPS) that is combined with an outdoor positioning system to support seamless indoor and outdoor navigation and wayfinding. The positioning system is implemented as a service in our broader cartography-based smart university platform, called SmartUJI, which centralizes access to a diverse collection of campus information and provides basic and complex services for the Universitat Jaume I (Spain), which serves as surrogate of a small city. Using our IPS and based on the SmartUJI services, we developed, deployed and evaluated two end-user mobile applications: the SmartUJI APP that allows users to obtain map-based information about the different facilities of the campus, and the SmartUJI AR that allows users to interact with the campus through an augmented reality interface. Students, university staff and visitors who tested the applications reported their usefulness in locating university facilities and generally improving spatial orientation.},
note = {IF: 2.065, Q1},
keywords = {augmented reality, Indoor positioning, mobile GIS, Smart Campus},
pubstate = {published},
tppubtype = {article}
}
A Smart City relies on six key factors: Smart Governance, Smart People, Smart Economy, Smart Environment, Smart Living and Smart Mobility. This paper focuses on Smart Mobility by improving one of its key components: positioning. We developed and deployed a novel indoor positioning system (IPS) that is combined with an outdoor positioning system to support seamless indoor and outdoor navigation and wayfinding. The positioning system is implemented as a service in our broader cartography-based smart university platform, called SmartUJI, which centralizes access to a diverse collection of campus information and provides basic and complex services for the Universitat Jaume I (Spain), which serves as surrogate of a small city. Using our IPS and based on the SmartUJI services, we developed, deployed and evaluated two end-user mobile applications: the SmartUJI APP that allows users to obtain map-based information about the different facilities of the campus, and the SmartUJI AR that allows users to interact with the campus through an augmented reality interface. Students, university staff and visitors who tested the applications reported their usefulness in locating university facilities and generally improving spatial orientation.