2021
Mendoza-Silva, Germán Martin; Torres-Sospedra, Joaquín; Huerta-Guijarro, Joaquín
Local-level Analysis of Positioning Errors in Wi-Fi Fingerprinting Proceedings Article
In: Proceedings of the 2021 IEEE 93rd Vehicular Technology Conference (VTC2021-Spring), pp. 1-5, IEEE, 2021, ISBN: 978-1-7281-8964-2.
Abstract | Links | BibTeX | Tags: Indoor positioning, Wi-Fi fingerprint
@inproceedings{Mendoza-Silva2021a,
title = {Local-level Analysis of Positioning Errors in Wi-Fi Fingerprinting},
author = {Germán Martin Mendoza-Silva and Joaquín Torres-Sospedra and Joaquín Huerta-Guijarro},
doi = {https://doi.org/10.1109/VTC2021-Spring51267.2021.9448936},
isbn = {978-1-7281-8964-2},
year = {2021},
date = {2021-06-15},
booktitle = {Proceedings of the 2021 IEEE 93rd Vehicular Technology Conference (VTC2021-Spring)},
pages = {1-5},
publisher = {IEEE},
abstract = {Nowadays, Location Based Services run over a net of heterogeneous devices (mainly smartphones) with different location capabilities thanks to, for instance, signals of opportunity as Wi-Fi. In contrast to professional deployments in controlled scenarios, the positioning error highly depends not only on the environment but also on the location. Traditional metrics for evaluating indoor positioning system may fail in obtaining lower-level details on the reported results. This paper introduces a way to perform a local-level analysis of the positioning errors. Our approach is based on analyses of the position-wise variance of positioning errors.},
keywords = {Indoor positioning, Wi-Fi fingerprint},
pubstate = {published},
tppubtype = {inproceedings}
}
Nowadays, Location Based Services run over a net of heterogeneous devices (mainly smartphones) with different location capabilities thanks to, for instance, signals of opportunity as Wi-Fi. In contrast to professional deployments in controlled scenarios, the positioning error highly depends not only on the environment but also on the location. Traditional metrics for evaluating indoor positioning system may fail in obtaining lower-level details on the reported results. This paper introduces a way to perform a local-level analysis of the positioning errors. Our approach is based on analyses of the position-wise variance of positioning errors.
Furfari, Francesco; Crivello, Antonino; Baronti, Paolo; Barsocchi, Paolo; Girolami, Michele; Palumbo, Filippo; Quezada-Gaibor, Darwin; Mendoza-Silva, Germán Martin; Torres-Sospedra, Joaquín
Discovering location based services: A unified approach for heterogeneous indoor localization systems Journal Article
In: Internet of Things, vol. 13, no. 1001511, 2021, ISSN: 2542-6605.
Abstract | Links | BibTeX | Tags: Indoor localization, Indoor positioning, location-based services
@article{Furfari2021,
title = {Discovering location based services: A unified approach for heterogeneous indoor localization systems},
author = {Francesco Furfari and Antonino Crivello and Paolo Baronti and Paolo Barsocchi and Michele Girolami and Filippo Palumbo and Darwin Quezada-Gaibor and Germán Martin Mendoza-Silva and Joaquín Torres-Sospedra},
doi = {https://doi.org/10.1016/j.iot.2020.100334},
issn = {2542-6605},
year = {2021},
date = {2021-03-01},
journal = {Internet of Things},
volume = {13},
number = {1001511},
abstract = {The technological solutions and communication capabilities offered by the Internet of Things paradigm, in terms of raising availability of wearable devices, the ubiquitous internet connection, and the presence on the market of service-oriented solutions, have allowed a wide proposal of Location Based Services (LBS). In a close future, we foresee that companies and service providers will have developed reliable solutions to address indoor positioning, as basis for useful location based services. These solutions will be different from each other and they will adopt different hardware and processing techniques. This paper describes the proposal of a unified approach for Indoor Localization Systems that enables the cooperation between heterogeneous solutions and their functional modules. To this end, we designed an integrated architecture that, abstracting its main components, allows a seamless interaction among them. Finally, we present a working prototype of such architecture, which is based on the popular Telegram application for Android, as an integration demonstrator. The integration of the three main phases –namely the discovery phase, the User Agent self-configuration, and the indoor map retrieval/rendering– demonstrates the feasibility of the proposed integrated architecture.},
keywords = {Indoor localization, Indoor positioning, location-based services},
pubstate = {published},
tppubtype = {article}
}
The technological solutions and communication capabilities offered by the Internet of Things paradigm, in terms of raising availability of wearable devices, the ubiquitous internet connection, and the presence on the market of service-oriented solutions, have allowed a wide proposal of Location Based Services (LBS). In a close future, we foresee that companies and service providers will have developed reliable solutions to address indoor positioning, as basis for useful location based services. These solutions will be different from each other and they will adopt different hardware and processing techniques. This paper describes the proposal of a unified approach for Indoor Localization Systems that enables the cooperation between heterogeneous solutions and their functional modules. To this end, we designed an integrated architecture that, abstracting its main components, allows a seamless interaction among them. Finally, we present a working prototype of such architecture, which is based on the popular Telegram application for Android, as an integration demonstrator. The integration of the three main phases –namely the discovery phase, the User Agent self-configuration, and the indoor map retrieval/rendering– demonstrates the feasibility of the proposed integrated architecture.
2020
Potortì, Francesco; Park, Sangjoon; Crivello, Antonino; Palumbo, Filippo; Girolami, Michele; Barsocchi, Paolo; Lee, Soyeon; Torres-Sospedra, Joaquín; Jimenez, Antonio Ramón; Pérez-Navarro, Antoni; Mendoza-Silva, Germán Martin; Seco, Fernando; Ortiz, Miguel; Perul, Johan; Renaudin, Valerie; Kang, Hyunwoong; Park, Soyoung; Lee, Jae Hong; Park, Chan Gook; Ha, Jisu; Han, Jaeseung; Park, Changjun; Kim, Keunhye; Lee, Yonghyun; Gye, Seunghun; Lee, Keumryeol; Kim, Eunjee; Choi, Jeongsik; Choi, Yang-Seok; Talwar, Shilpa; Cho, Seong Yun; Ben-Moshe, Boaz; Scherbakov, Alex; Antsfeld, Leonid; Sansano-Sansano, Emilio; Chidlovskii, Boris; Kronenwett, Nikolai; Prophet, Silvia; Landau, Yael; Marbel, Revital; Zheng, Lingxiang; Peng, Ao; Lin, Zhichao; Wu, Bang; Ma, Chengqi; Poslad, Stefan; Selviah, David R.; Wu, Wei; Ma, Zixiang; Zhang, Wenchao; Wei, Dongyan; Yuan, Hong; Jiang, Jun-Bang; Huang, Shao-Yung; Liu, Jing-Wen; Su, Kuan-Wu; Leu, Jenq-Shiou; Nishiguchi, Kazuki; Bousselham, Walid; Uchiyama, Hideaki; Thomas, Diego; Shimada, Atsushi; Taniguchi, Rin-Ichiro; Cortés, Vicente; Lungenstrass, Tomás; Ashraf, Imran; Lee, Chanseok; Ali, Muhammad Usman; Im, Yeongjun; Kim, Gunzung; Eom, Jeongsook; Hur, Soojung; Park, Yongwan; Opiela, Miroslav; Moreira, Adriano; Nicolau, Maria João; Pendão, Cristiano; Silva, Ivo; Meneses, Filipe; Costa, António; Trogh, Jens; Plets, David; Chien, Ying-Ren; Chang, Tzu-Yu; Fang, Shih-Hau; Tsao, Yu
The IPIN 2019 Indoor Localisation Competition: Description and Results Journal Article
In: IEEE Access, vol. 8, pp. 206674-20671, 2020, ISSN: 2169-3536.
Abstract | Links | BibTeX | Tags: Indoor positioning
@article{Potortì2020,
title = {The IPIN 2019 Indoor Localisation Competition: Description and Results},
author = {Francesco Potortì and Sangjoon Park and Antonino Crivello and Filippo Palumbo and Michele Girolami and Paolo Barsocchi and Soyeon Lee and Joaquín Torres-Sospedra and Antonio Ramón Jimenez and Antoni Pérez-Navarro and Germán Martin Mendoza-Silva and Fernando Seco and Miguel Ortiz and Johan Perul and Valerie Renaudin and Hyunwoong Kang and Soyoung Park and Jae Hong Lee and Chan Gook Park and Jisu Ha and Jaeseung Han and Changjun Park and Keunhye Kim and Yonghyun Lee and Seunghun Gye and Keumryeol Lee and Eunjee Kim and Jeongsik Choi and Yang-Seok Choi and Shilpa Talwar and Seong Yun Cho and Boaz Ben-Moshe and Alex Scherbakov and Leonid Antsfeld and Emilio Sansano-Sansano and Boris Chidlovskii and Nikolai Kronenwett and Silvia Prophet and Yael Landau and Revital Marbel and Lingxiang Zheng and Ao Peng and Zhichao Lin and Bang Wu and Chengqi Ma and Stefan Poslad and David R. Selviah and Wei Wu and Zixiang Ma and Wenchao Zhang and Dongyan Wei and Hong Yuan and Jun-Bang Jiang and Shao-Yung Huang and Jing-Wen Liu and Kuan-Wu Su and Jenq-Shiou Leu and Kazuki Nishiguchi and Walid Bousselham and Hideaki Uchiyama and Diego Thomas and Atsushi Shimada and Rin-Ichiro Taniguchi and Vicente Cortés and Tomás Lungenstrass and Imran Ashraf and Chanseok Lee and Muhammad Usman Ali and Yeongjun Im and Gunzung Kim and Jeongsook Eom and Soojung Hur and Yongwan Park and Miroslav Opiela and Adriano Moreira and Maria João Nicolau and Cristiano Pendão and Ivo Silva and Filipe Meneses and António Costa and Jens Trogh and David Plets and Ying-Ren Chien and Tzu-Yu Chang and Shih-Hau Fang and Yu Tsao},
doi = {10.1109/ACCESS.2020.3037221},
issn = {2169-3536},
year = {2020},
date = {2020-09-01},
journal = {IEEE Access},
volume = {8},
pages = {206674-20671},
abstract = {IPIN 2019 Competition, sixth in a series of IPIN competitions, was held at the CNR Research Area of Pisa (IT), integrated into the program of the IPIN 2019 Conference. It included two on-site real-time Tracks and three off-site Tracks. The four Tracks presented in this paper were set in the same environment, made of two buildings close together for a total usable area of 1000 m 2 outdoors and and 6000 m 2 indoors over three floors, with a total path length exceeding 500 m. IPIN competitions, based on the EvAAL framework, have aimed at comparing the accuracy performance of personal positioning systems in fair and realistic conditions: past editions of the competition were carried in big conference settings, university campuses and a shopping mall. Positioning accuracy is computed while the person carrying the system under test walks at normal walking speed, uses lifts and goes up and down stairs or briefly stops at given points. Results presented here are a showcase of state-of-the-art systems tested side by side in real-world settings as part of the on-site real-time competition Tracks. Results for off-site Tracks allow a detailed and reproducible comparison of the most recent positioning and tracking algorithms in the same environment as the on-site Tracks.
},
keywords = {Indoor positioning},
pubstate = {published},
tppubtype = {article}
}
IPIN 2019 Competition, sixth in a series of IPIN competitions, was held at the CNR Research Area of Pisa (IT), integrated into the program of the IPIN 2019 Conference. It included two on-site real-time Tracks and three off-site Tracks. The four Tracks presented in this paper were set in the same environment, made of two buildings close together for a total usable area of 1000 m 2 outdoors and and 6000 m 2 indoors over three floors, with a total path length exceeding 500 m. IPIN competitions, based on the EvAAL framework, have aimed at comparing the accuracy performance of personal positioning systems in fair and realistic conditions: past editions of the competition were carried in big conference settings, university campuses and a shopping mall. Positioning accuracy is computed while the person carrying the system under test walks at normal walking speed, uses lifts and goes up and down stairs or briefly stops at given points. Results presented here are a showcase of state-of-the-art systems tested side by side in real-world settings as part of the on-site real-time competition Tracks. Results for off-site Tracks allow a detailed and reproducible comparison of the most recent positioning and tracking algorithms in the same environment as the on-site Tracks.
Torres-Sospedra, Joaquín; Quezada-Gaibor, Darwin; Mendoza-Silva, Germán Martín; Nurmi, Jari; Koucheryavy, Yevgeni; Huerta-Guijarro, Joaquín
New Cluster Selection and Fine-grained Search for k-Means Clustering and Wi-Fi Fingerprinting Proceedings Article
In: 2020 International Conference on Localization and GNSS (ICL-GNSS), Tampere, Finland, 2020, pp. 1-6, IEEE, 2020, ISBN: 978-1-7281-6455-7.
Abstract | Links | BibTeX | Tags: A-wear, Indoor positioning, Wi-Fi fingerprint
@inproceedings{Torres-Sospedra2020,
title = {New Cluster Selection and Fine-grained Search for k-Means Clustering and Wi-Fi Fingerprinting},
author = {Joaquín Torres-Sospedra and Darwin Quezada-Gaibor and Germán Martín Mendoza-Silva and Jari Nurmi and Yevgeni Koucheryavy and Joaquín Huerta-Guijarro},
doi = {http://www.doi.org/10.1109/ICL-GNSS49876.2020.9115419 },
isbn = {978-1-7281-6455-7},
year = {2020},
date = {2020-07-02},
booktitle = {2020 International Conference on Localization and GNSS (ICL-GNSS), Tampere, Finland, 2020},
pages = {1-6},
publisher = {IEEE},
abstract = {Wi-Fi fingerprinting is a popular technique for Indoor Positioning Systems (IPSs) thanks to its low complexity and the ubiquity of WLAN infrastructures. However, this technique
may present scalability issues when the reference dataset (radio map) is very large. To reduce the computational costs, k-Means Clustering has been successfully applied in the past. However, it is a general-purpose algorithm for unsupervised classification. This paper introduces three variants that apply heuristics based on radio propagation knowledge in the coarse and fine-grained searches. Due to the heterogeneity either in the IPS side (including radio map generation) and in the network infrastructure, we used an evaluation framework composed of 16 datasets. In terms of general positioning accuracy and computational costs, the best proposed k-means variant provided better general positioning
accuracy and a significantly better computational cost –around 40% lower– than the original k-means.},
keywords = {A-wear, Indoor positioning, Wi-Fi fingerprint},
pubstate = {published},
tppubtype = {inproceedings}
}
Wi-Fi fingerprinting is a popular technique for Indoor Positioning Systems (IPSs) thanks to its low complexity and the ubiquity of WLAN infrastructures. However, this technique
may present scalability issues when the reference dataset (radio map) is very large. To reduce the computational costs, k-Means Clustering has been successfully applied in the past. However, it is a general-purpose algorithm for unsupervised classification. This paper introduces three variants that apply heuristics based on radio propagation knowledge in the coarse and fine-grained searches. Due to the heterogeneity either in the IPS side (including radio map generation) and in the network infrastructure, we used an evaluation framework composed of 16 datasets. In terms of general positioning accuracy and computational costs, the best proposed k-means variant provided better general positioning
accuracy and a significantly better computational cost –around 40% lower– than the original k-means.
may present scalability issues when the reference dataset (radio map) is very large. To reduce the computational costs, k-Means Clustering has been successfully applied in the past. However, it is a general-purpose algorithm for unsupervised classification. This paper introduces three variants that apply heuristics based on radio propagation knowledge in the coarse and fine-grained searches. Due to the heterogeneity either in the IPS side (including radio map generation) and in the network infrastructure, we used an evaluation framework composed of 16 datasets. In terms of general positioning accuracy and computational costs, the best proposed k-means variant provided better general positioning
accuracy and a significantly better computational cost –around 40% lower– than the original k-means.
Karmacharya, Amrit; Mendoza-Silva, German Martín; Torres-Sospedra, Joaquín
Sensor Fusion and Well Condition Triangle Approach for BLE-based Indoor Positioning Proceedings Article
In: Ometov, A.; Nurmi, Jaarmi; Lohan, Elena Simona; Torres-Sospedra, Joaquín; (Eds), H. Kuusniemi (Ed.): Proceedings of the International Conference on Localization and GNSS (ICL GNSS 2020) CEUR Workshop Proceedings. Tampere, Finland, June 2-4 2020, CEUR, 2020, ISSN: 1613-0073 .
Abstract | Links | BibTeX | Tags: Indoor positioning, Mastergeotech
@inproceedings{Karmacharya2020b,
title = {Sensor Fusion and Well Condition Triangle Approach for BLE-based Indoor Positioning},
author = {Amrit Karmacharya and German Martín Mendoza-Silva and Joaquín Torres-Sospedra },
editor = {A. Ometov and Jaarmi Nurmi and Elena Simona Lohan and Joaquín Torres-Sospedra and H. Kuusniemi (Eds)},
url = {http://ceur-ws.org/Vol-2626/paper6.pdf },
issn = {1613-0073 },
year = {2020},
date = {2020-06-15},
booktitle = {Proceedings of the International Conference on Localization and GNSS (ICL GNSS 2020) CEUR Workshop Proceedings. Tampere, Finland, June 2-4 2020},
volume = {2626},
publisher = {CEUR},
abstract = {GPS has been a de-facto standard for outdoor positioning. For indoor positioning different systems exist. But there is no general solution to fit all situations. A popular choice among service provider is Bluetooth Low Energy (BLE) based Indoor Positioning System (IPS) . BLE has low cost, low power consumption, and it is compatible with newer smartphones. This paper introduces two ways for accuracy improvement i) a new algorithm for BLE-based IPS based on well-condition triangle and ii) fusion of BLE position estimates with IMU position estimates was implemented. Fusion generally gives better results but a noteworthy result from fusion was that the position estimates during turns were accurate. When used separately, both BLE and IMU estimates showed errors in turns. Fusion with IMU improved the accuracy of BLE based positioning.},
keywords = {Indoor positioning, Mastergeotech},
pubstate = {published},
tppubtype = {inproceedings}
}
GPS has been a de-facto standard for outdoor positioning. For indoor positioning different systems exist. But there is no general solution to fit all situations. A popular choice among service provider is Bluetooth Low Energy (BLE) based Indoor Positioning System (IPS) . BLE has low cost, low power consumption, and it is compatible with newer smartphones. This paper introduces two ways for accuracy improvement i) a new algorithm for BLE-based IPS based on well-condition triangle and ii) fusion of BLE position estimates with IMU position estimates was implemented. Fusion generally gives better results but a noteworthy result from fusion was that the position estimates during turns were accurate. When used separately, both BLE and IMU estimates showed errors in turns. Fusion with IMU improved the accuracy of BLE based positioning.
2019
Renaudin, Valerie; Ortiz, M.; Perul, J.; Torres-Sospedra, Joaquín; Jimenez, A. Ramón; Pérez-Navarro, Antoni; Mendoza-Silva, Germán Martín; Seco, F.; Landau, Y.; Marbel, R.; Ben-Moshe, B.; Zheng, X.; Ye, F.; Kuang, J.; Li, Y.; Niu, X.; Landa, V.; Hacohen, S.; Shvalb, N.; Lu, C.; Uchiyama, H.; Thomas, D.; Shimada, A.; Taniguchi, R.; Ding, Z.; Xu, F.; Kronenwett, N.; Vladimirov, B.; Lee, S.; Cho, E.; Jun, S.; Lee, C.; Park, S.; Lee, Y.; Rew, J.; Park, C.; Jeong, H.; Han, J.; Lee, K.; Zhang, W.; Li, X.; Wei, D.; Zhang, Y.; Park, S. Y.; Park, C. G.; Knauth, S.; Pipelidis, G.; Tsiamitros, N.; Lungenstrass, T.; Pablo Morales, J.; Trogh, J.; Plets, D.; Opiela, M.; Shih-Hau Fang Tsao, Y.; Chien, Y. -R.; Yang, S. -S.; Ye, S. -J.; Ali, M. U.; Hur, S.; Park, Y. I.
Evaluating Indoor Positioning Systems in a Shopping Mall: The Lessons Learned from the IPIN 2018 Competition Journal Article
In: IEEE Access, vol. 7, pp. 148594 – 148628, 2019.
Abstract | Links | BibTeX | Tags: Indoor positioning
@article{Renaudin2019,
title = {Evaluating Indoor Positioning Systems in a Shopping Mall: The Lessons Learned from the IPIN 2018 Competition},
author = {Valerie Renaudin and M. Ortiz and J. Perul and Joaquín Torres-Sospedra and A. Ramón Jimenez and Antoni Pérez-Navarro and Germán Martín Mendoza-Silva and F. Seco and Y. Landau and Marbel, R. and Ben-Moshe, B. and Zheng, X. and Ye, F. and Kuang, J. and Li, Y. and Niu, X. and Landa, V. and Hacohen, S. and Shvalb, N. and Lu, C. and Uchiyama, H. and Thomas, D. and Shimada, A. and Taniguchi, R. and Ding, Z. and Xu, F. and Kronenwett, N. and Vladimirov, B. and Lee, S. and Cho, E. and Jun, S. and Lee, C. and Park, S. and Lee, Y. and Rew, J. and Park, C. and Jeong, H. and Han, J. and Lee, K. and Zhang, W. and Li, X. and Wei, D. and Zhang, Y. and Park, S. Y. and Park, C. G. and Knauth, S. and Pipelidis, G. and Tsiamitros, N. and Lungenstrass, T. and Pablo Morales, J. and Trogh, J. and Plets, D. and Opiela, M. and Shih-Hau Fang Tsao, Y. and Chien, Y.-R. and Yang, S.-S. and Ye, S.-J. and Ali, M. U. and S. Hur and Y.I. Park},
url = {https://ieeexplore.ieee.org/document/8852722 },
year = {2019},
date = {2019-12-01},
journal = {IEEE Access},
volume = {7},
pages = {148594 – 148628},
abstract = {The Indoor Positioning and Indoor Navigation (IPIN) conference holds an annual competition in which indoor localization systems from different research groupsworldwide are evaluated empirically. The objective of this competition is to establish a systematic evaluation methodology with rigorous metrics both for real-time (on-site) and post-processing (off-site) situations, in a realistic environment unfamiliar to the prototype developers. For the IPIN 2018 conference, this competition was held on September 22nd, 2018, in Atlantis, a large shopping mall in Nantes (France). Four competition tracks (two on-site and two off-site) were designed. They consisted of several 1 km routes traversing several oors of the mall. Along these paths, 180 points were topographically surveyed with a 10 cm accuracy, to serve as ground truth landmarks, combining theodolite measurements, differential global navigation satellite system (GNSS) and 3D scanner systems. 34 teams effectively competed. The accuracy score corresponds to the third quartile (75th percentile) of an error metric that combines the horizontal positioning error and the oor detection. The best results for the on-site tracks showed an accuracy score of 11.70 m (Track 1) and 5.50 m (Track 2), while the best results for the off-site tracks showed an accuracy score of 0.90 m (Track 3) and 1.30m(Track 4). These results showed that it is possible to obtain high accuracy indoor positioning solutions in large, realistic environments using wearable light-weight sensors without deploying any beacon. This paper describes the organization work of the tracks, analyzes the methodology used to quantify the results, reviews the lessons learned from the competition and discusses its future},
keywords = {Indoor positioning},
pubstate = {published},
tppubtype = {article}
}
The Indoor Positioning and Indoor Navigation (IPIN) conference holds an annual competition in which indoor localization systems from different research groupsworldwide are evaluated empirically. The objective of this competition is to establish a systematic evaluation methodology with rigorous metrics both for real-time (on-site) and post-processing (off-site) situations, in a realistic environment unfamiliar to the prototype developers. For the IPIN 2018 conference, this competition was held on September 22nd, 2018, in Atlantis, a large shopping mall in Nantes (France). Four competition tracks (two on-site and two off-site) were designed. They consisted of several 1 km routes traversing several oors of the mall. Along these paths, 180 points were topographically surveyed with a 10 cm accuracy, to serve as ground truth landmarks, combining theodolite measurements, differential global navigation satellite system (GNSS) and 3D scanner systems. 34 teams effectively competed. The accuracy score corresponds to the third quartile (75th percentile) of an error metric that combines the horizontal positioning error and the oor detection. The best results for the on-site tracks showed an accuracy score of 11.70 m (Track 1) and 5.50 m (Track 2), while the best results for the off-site tracks showed an accuracy score of 0.90 m (Track 3) and 1.30m(Track 4). These results showed that it is possible to obtain high accuracy indoor positioning solutions in large, realistic environments using wearable light-weight sensors without deploying any beacon. This paper describes the organization work of the tracks, analyzes the methodology used to quantify the results, reviews the lessons learned from the competition and discusses its future
Torres-Sospedra, Joaquín; Moreira, A.; Mendoza-Silva, Germán Martín; Nicolau, M. J.; Matey-Sanz, Miguel; Silva, I.; Huerta-Guijarro, Joaquín; Pendão, C.
Exploiting Different Combinations of Complementary Sensor's data for Fingerprint-based Indoor Positioning in Industrial Environments Proceedings Article
In: Proceedings of the Tenth International Conference on Indoor Positioning and Indoor Navigation, 30 Sept. – 3 Oct. 2019, Pisa, Italy. , IEEE, 2019, ISBN: 978-1-7281-1788-1 .
Abstract | Links | BibTeX | Tags: Indoor positioning, Sensors, Wi-Fi fingerprint
@inproceedings{Torres-Sospedra2019b,
title = {Exploiting Different Combinations of Complementary Sensor's data for Fingerprint-based Indoor Positioning in Industrial Environments},
author = {Joaquín Torres-Sospedra and A. Moreira and Germán Martín Mendoza-Silva and M. J. Nicolau and Miguel Matey-Sanz and I. Silva and Joaquín Huerta-Guijarro and C. Pendão },
doi = {10.1109/IPIN.2019.8911758 },
isbn = {978-1-7281-1788-1 },
year = {2019},
date = {2019-12-01},
booktitle = {Proceedings of the Tenth International Conference on Indoor Positioning and Indoor Navigation, 30 Sept. – 3 Oct. 2019, Pisa, Italy. },
publisher = {IEEE},
abstract = {Wi-Fi fingerprinting is a popular technique for smartphone-based indoor positioning. However, well-known RF propagation issues create signal fluctuations that translate into large positioning errors. Large errors limit the usage of Wi-Fi fingerprinting in industrial environments, where the reliability of position estimates is a key requirement. One successful approach to deal with signal fluctuations is to average the signals collected simultaneously through independent Wi-Fi interfaces. Another successful approach is to average the estimates provided by models built on independent radio maps. This paper explores multiple combinations of both approaches and determines the procedure to select the best model based on them through a simulated environment. The evaluation of the proposed model in a real-world industrial scenario shows that the positioning error (according to different metrics including the 95th and 99th percentiles) is highly improved with respect to the traditional fingerprint.},
keywords = {Indoor positioning, Sensors, Wi-Fi fingerprint},
pubstate = {published},
tppubtype = {inproceedings}
}
Wi-Fi fingerprinting is a popular technique for smartphone-based indoor positioning. However, well-known RF propagation issues create signal fluctuations that translate into large positioning errors. Large errors limit the usage of Wi-Fi fingerprinting in industrial environments, where the reliability of position estimates is a key requirement. One successful approach to deal with signal fluctuations is to average the signals collected simultaneously through independent Wi-Fi interfaces. Another successful approach is to average the estimates provided by models built on independent radio maps. This paper explores multiple combinations of both approaches and determines the procedure to select the best model based on them through a simulated environment. The evaluation of the proposed model in a real-world industrial scenario shows that the positioning error (according to different metrics including the 95th and 99th percentiles) is highly improved with respect to the traditional fingerprint.
Mendoza-Silva, Germán Martín; Matey-Sanz, Miguel; Torres-Sospedra, Joaquín; Huerta-Guijarro, Joaquín
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 Martín Mendoza-Silva and Miguel Matey-Sanz and Joaquín Torres-Sospedra and Joaquín Huerta-Guijarro},
doi = {https://doi.org/10.3390/data4010012},
issn = {2306-5729},
year = {2019},
date = {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.
Mendoza-Silva, Germán Martín; Torres-Sospedra, Joaquín; Huerta-Guijarro, Joaquín
A Meta-Review of Indoor Positioning Systems Journal Article
In: Sensors, vol. 19, no. 20, pp. 4507, 2019.
Links | BibTeX | Tags: Indoor positioning
@article{Mendoza-Silva2019b,
title = {A Meta-Review of Indoor Positioning Systems },
author = {Germán Martín Mendoza-Silva and Joaquín Torres-Sospedra and Joaquín Huerta-Guijarro},
doi = {https://doi.org/10.3390/s19204507 },
year = {2019},
date = {2019-01-01},
journal = {Sensors},
volume = {19},
number = {20},
pages = {4507},
keywords = {Indoor positioning},
pubstate = {published},
tppubtype = {article}
}
2018
Torres-Sospedra, Joaquín; Richter, Philipp; Mendoza-Silva, Germán Martín; Lohan, Elena Simona; Huerta-Guijarro, Joaquín
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 = {Joaquín Torres-Sospedra and Philipp Richter and Germán Martín Mendoza-Silva and Elena Simona Lohan and Joaquín 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, Joaquín; Jiménez, Antonio R.; Moreira, Adriano; Lungenstrass, Tomás; Lu, Wei-Chung; Knauth, Stefan; Mendoza-Silva, Germán Martín; Seco, Fernando; Pérez-Navarro, Antoni; Nicolau, Maria João; Costa, António; Meneses, Filipe; Farina, Joaquín; Morales, Juan Pablo; Lu, Wen-Chen; Cheng, Ho-Ti; Yang, Shi-Shen; Fang, Shih-Hau; Chien, Ying-Ren; Tsao, Yu
Off-line evaluation of mobile-centric Indoor Positioning Systems: the experiences from the 2017 IPIN competition Journal Article
In: Sensors, vol. 18, no. 2, pp. 487, 2018, ISSN: 1424-8220.
Abstract | Links | BibTeX | Tags: Indoor localization, Indoor positioning
@article{Torres-Sospedra2018,
title = {Off-line evaluation of mobile-centric Indoor Positioning Systems: the experiences from the 2017 IPIN competition},
author = {Joaquín Torres-Sospedra and Antonio R. Jiménez and Adriano Moreira and Tomás Lungenstrass and Wei-Chung Lu and Stefan Knauth and Germán Martín Mendoza-Silva and Fernando Seco and Antoni Pérez-Navarro and Maria João Nicolau and António Costa and Filipe Meneses and Joaquín Farina and Juan Pablo Morales and Wen-Chen Lu and Ho-Ti Cheng and Shi-Shen Yang and Shih-Hau Fang and Ying-Ren Chien and Yu Tsao },
doi = {https://doi.org/10.3390/s18020487},
issn = {1424-8220},
year = {2018},
date = {2018-03-01},
journal = {Sensors},
volume = {18},
number = {2},
pages = {487},
abstract = {The development of indoor positioning solutions using smartphones is a growing activity with an enormous potential for everyday life and professional applications. The research activities on this topic concentrate on the development of new positioning solutions that are tested in specific environments under their own evaluation metrics. To explore the real positioning quality of smartphone-based solutions and their capabilities for seamlessly adapting to different scenarios, it is needed to find fair evaluation frameworks. The design of competitions using extensive pre-recorded datasets is a valid way to generate open data for comparing the different solutions created by research teams. In this paper, we discuss the details of the 2017 IPIN indoor localization competition, the different datasets created, the teams participating in the event, and the results they obtained. We compare these results with other competition-based approaches (Microsoft and Perf-loc) and on-line evaluation web sites. The lessons learned by organising these competitions and the benefits for the community are addressed along the paper. Our analysis paves the way for future developments on the standardization of evaluations and for creating a widely-adopted benchmark strategy for researchers and companies in the field},
keywords = {Indoor localization, Indoor positioning},
pubstate = {published},
tppubtype = {article}
}
The development of indoor positioning solutions using smartphones is a growing activity with an enormous potential for everyday life and professional applications. The research activities on this topic concentrate on the development of new positioning solutions that are tested in specific environments under their own evaluation metrics. To explore the real positioning quality of smartphone-based solutions and their capabilities for seamlessly adapting to different scenarios, it is needed to find fair evaluation frameworks. The design of competitions using extensive pre-recorded datasets is a valid way to generate open data for comparing the different solutions created by research teams. In this paper, we discuss the details of the 2017 IPIN indoor localization competition, the different datasets created, the teams participating in the event, and the results they obtained. We compare these results with other competition-based approaches (Microsoft and Perf-loc) and on-line evaluation web sites. The lessons learned by organising these competitions and the benefits for the community are addressed along the paper. Our analysis paves the way for future developments on the standardization of evaluations and for creating a widely-adopted benchmark strategy for researchers and companies in the field
Torres-Sospedra, Joaquín; Richter, Philipp; Mendoza-Silva, Germán Martín; Lohan, Elena Simona; Huerta-Guijarro, Joaquín
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 = {Joaquín Torres-Sospedra and Philipp Richter and Germán Martín Mendoza-Silva and Elena Simona Lohan and Joaquín 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 Martín; Torres-Sospedra, Joaquín; Huerta-Guijarro, Joaquín
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 Martín Mendoza-Silva and Joaquín Torres-Sospedra and Joaquín 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 Martín; Richter, Philipp; Torres-Sospedra, Joaquín; Lohan, Elana Simona; Huerta-Guijarro, Joaquín
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 Martín Mendoza-Silva and Philipp Richter and Joaquín Torres-Sospedra and Elana Simona Lohan and Joaquín 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
Mendoza-Silva, Germán Martín; Torres-Sospedra, Joaquín; Huerta-Guijarro, Joaquín
A More Realistic Error Distance Calculation for WiFi Indoor Positioning Systems Accuracy Evaluation Proceedings Article
In: Proceedings of the Eigth International Conference on Indoor Positioning and Indoor Navigation, 2017. Sapporo, Japan, 18-21 Sep 2017, IEEE, 2017, ISBN: 10.1109/IPIN.2017.8115914.
Abstract | Links | BibTeX | Tags: Indoor positioning, Wi-Fi
@inproceedings{Mendoza-Silva2017b,
title = {A More Realistic Error Distance Calculation for WiFi Indoor Positioning Systems Accuracy Evaluation},
author = {Germán Martín Mendoza-Silva and Joaquín Torres-Sospedra and Joaquín Huerta-Guijarro},
doi = {10.1109/IPIN.2017.8115950},
isbn = {10.1109/IPIN.2017.8115914},
year = {2017},
date = {2017-12-01},
booktitle = {Proceedings of the Eigth International Conference on Indoor Positioning and Indoor Navigation, 2017. Sapporo, Japan, 18-21 Sep 2017},
publisher = {IEEE},
abstract = {The accuracy of indoor positioning systems is commonly computed as a metric based on the Euclidean distance from estimated locations to actual locations. This paper suggests that positioning error distances should be computed as the lengths of the paths that a person may follow when going from wrongly estimated positions to the real positions. The paper proposes a method that calculates the paths from floor plan and obstacles information using the visibility graphs and offsetting techniques, which are commonly used in robotics and CAD/CAM for navigation and manufacturing, respectively. Demonstration of the proposed method was done using a WiFi fingerprinting method based on kNN for pedestrian navigation. Comparisons between our proposed distance and the simple Euclidean distance have shown that the error distances are underestimated and that the differences between the two distances cannot be accurately represented by a fixed quantity in the context of an Indoor Positioning System (IPS) deployed in a library building. We consider that our proposed positioning error distance is more in line with the subjective error perceived by IPS users},
keywords = {Indoor positioning, Wi-Fi},
pubstate = {published},
tppubtype = {inproceedings}
}
The accuracy of indoor positioning systems is commonly computed as a metric based on the Euclidean distance from estimated locations to actual locations. This paper suggests that positioning error distances should be computed as the lengths of the paths that a person may follow when going from wrongly estimated positions to the real positions. The paper proposes a method that calculates the paths from floor plan and obstacles information using the visibility graphs and offsetting techniques, which are commonly used in robotics and CAD/CAM for navigation and manufacturing, respectively. Demonstration of the proposed method was done using a WiFi fingerprinting method based on kNN for pedestrian navigation. Comparisons between our proposed distance and the simple Euclidean distance have shown that the error distances are underestimated and that the differences between the two distances cannot be accurately represented by a fixed quantity in the context of an Indoor Positioning System (IPS) deployed in a library building. We consider that our proposed positioning error distance is more in line with the subjective error perceived by IPS users
Potortì, Francesco; Park, Sangjoon; Ruiz, Antonio Ramón Jiménez; Barsocchi, Paolo; Girolami, Michele; Crivello, Antonino; Lee, So Yeon; Lim, Jae Hyun; Torres-Sospedra, Joaquín; Seco, Fernando; Montoliu, Raul; Mendoza-Silva, Germán Martín; Rubio, Maria Del Carmen Pérez; Losada-Gutiérrez, Cristina; Espinosa, Felipe; Macias-Guarasa, Javier
Comparing the Performance of Indoor Localization Systems through the EvAAL Framework Journal Article
In: Sensors, vol. 17, no. 10, pp. 2327, 2017, ISSN: 1424-8220.
Abstract | Links | BibTeX | Tags: Indoor positioning, Wi-Fi fingerprint
@article{s17102327,
title = {Comparing the Performance of Indoor Localization Systems through the EvAAL Framework},
author = {Francesco Potortì and Sangjoon Park and Antonio Ramón Jiménez Ruiz and Paolo Barsocchi and Michele Girolami and Antonino Crivello and So Yeon Lee and Jae Hyun Lim and Joaquín Torres-Sospedra and Fernando Seco and Raul Montoliu and Germán Martín Mendoza-Silva and Maria Del Carmen Pérez Rubio and Cristina Losada-Gutiérrez and Felipe Espinosa and Javier Macias-Guarasa},
url = {http://www.mdpi.com/1424-8220/17/10/2327},
doi = {10.3390/s17102327},
issn = {1424-8220},
year = {2017},
date = {2017-10-03},
journal = {Sensors},
volume = {17},
number = {10},
pages = {2327},
abstract = {In recent years, indoor localization systems have been the object of significant research activity and of growing interest for their great expected social impact and their impressive business potential. Application areas include tracking and navigation, activity monitoring, personalized advertising, Active and Assisted Living (AAL), traceability, Internet of Things (IoT) networks, and Home-land Security. In spite of the numerous research advances and the great industrial interest, no canned solutions have yet been defined. The diversity and heterogeneity of applications, scenarios, sensor and user requirements, make it difficult to create uniform solutions. From that diverse reality, a main problem is derived that consists in the lack of a consensus both in terms of the metrics and the procedures used to measure the performance of the different indoor localization and navigation proposals. This paper introduces the general lines of the EvAAL benchmarking framework, which is aimed at a fair comparison of indoor positioning systems through a challenging competition under complex, realistic conditions. To evaluate the framework capabilities, we show how it was used in the 2016 Indoor Positioning and Indoor Navigation (IPIN) Competition. The 2016 IPIN competition considered three different scenario dimensions, with a variety of use cases: (1) pedestrian versus robotic navigation, (2) smartphones versus custom hardware usage and (3) real-time positioning versus off-line post-processing. A total of four competition tracks were evaluated under the same EvAAL benchmark framework in order to validate its potential to become a standard for evaluating indoor localization solutions. The experience gained during the competition and feedback from track organizers and competitors showed that the EvAAL framework is flexible enough to successfully fit the very different tracks and appears adequate to compare indoor positioning systems.},
keywords = {Indoor positioning, Wi-Fi fingerprint},
pubstate = {published},
tppubtype = {article}
}
In recent years, indoor localization systems have been the object of significant research activity and of growing interest for their great expected social impact and their impressive business potential. Application areas include tracking and navigation, activity monitoring, personalized advertising, Active and Assisted Living (AAL), traceability, Internet of Things (IoT) networks, and Home-land Security. In spite of the numerous research advances and the great industrial interest, no canned solutions have yet been defined. The diversity and heterogeneity of applications, scenarios, sensor and user requirements, make it difficult to create uniform solutions. From that diverse reality, a main problem is derived that consists in the lack of a consensus both in terms of the metrics and the procedures used to measure the performance of the different indoor localization and navigation proposals. This paper introduces the general lines of the EvAAL benchmarking framework, which is aimed at a fair comparison of indoor positioning systems through a challenging competition under complex, realistic conditions. To evaluate the framework capabilities, we show how it was used in the 2016 Indoor Positioning and Indoor Navigation (IPIN) Competition. The 2016 IPIN competition considered three different scenario dimensions, with a variety of use cases: (1) pedestrian versus robotic navigation, (2) smartphones versus custom hardware usage and (3) real-time positioning versus off-line post-processing. A total of four competition tracks were evaluated under the same EvAAL benchmark framework in order to validate its potential to become a standard for evaluating indoor localization solutions. The experience gained during the competition and feedback from track organizers and competitors showed that the EvAAL framework is flexible enough to successfully fit the very different tracks and appears adequate to compare indoor positioning systems.
2016
Torres-Sospedra, Joaquín; Mendoza-Silva, Germán Martín; Montoliu-Colás, Raúl; Belmonte-Fernández, Óscar; Benítez-Paéz, Fernando; Huerta-Guijarro, Joaquín
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 = { Joaquín Torres-Sospedra and Germán Martín Mendoza-Silva and Raúl Montoliu-Colás and Óscar Belmonte-Fernández and Fernando Benítez-Paéz and Joaquín 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, Joaquín; Montoliu-Colás, Raúl; Mendoza-Silva, Germán Martín; Belmonte-Fernández, Óscar; Rambla-Risueño, David; Huerta-Guijarro, Joaquín
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 = { Joaquín Torres-Sospedra and Raúl Montoliu-Colás and Germán Martín Mendoza-Silva and Óscar Belmonte-Fernández and David Rambla-Risueño and Joaquín 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}
}