@inproceedings{Silva2021ab,

title = {Quantifying the Degradation of Radio Maps in Wi-Fi Fingerprinting},

author = {Ivo Silva and Cristiano Pendão and Joaquín Torres-Sospedra and Adriano Moreira},

doi = {https://doi.org/10.1109/IPIN51156.2021.9662558},

year  = {2021},

date = {2021-12-15},

booktitle = {Proceedings of the Eleventh International Conference on Indoor Positioning and Indoor Navigation},

publisher = {IEEE},

abstract = {One of the most common assumptions regarding indoor positioning systems based on Wi-Fi fingerprinting is that the Radio Map (RM) becomes outdated and has to be updated to maintain the positioning performance. It is known that propagation effects, the addition/removal of Access Points (APs), changes in the indoor layout, among others, cause RMs to become outdated. However, there is a lack of studies that show how the RM degrades over time. In this paper, we describe an empirical study, based on real-world experiments, to evaluate how and why RMs degrade over time. We conducted site surveys and deployed monitoring devices to analyse the radio environment of one building over 2+ years, which allowed us to identify significant changes/events that caused the degradation of RMs. To quantify the RM degradation, we use the positioning error and propose the RM degradation ratio, a metric to directly compare two RMs and measure how different they are. Obtained results show that the positioning performance is much better when RMs are collected on the same day as the test data, and although RM degradation tends to increase over time, it only leads to large positioning errors when significant changes occur in the Wi-Fi infrastructure, making previous RMs outdated.},

keywords = {Wi-Fi fingerprint, Wi-Fi mapping},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Torres-Sospedra2021b,

title = {Ensembling Multiple Radio Maps with Dynamic Noise in Fingerprint-based Indoor Positioning},

author = {Joaquín Torres-Sospedra and Fernando J. Aranda and Fernando J. Álvarez and Darwin Quezada-Gaibor and Ivo Silva and Cristiano Pendão and Adriano Moreira},

doi = {http://dx.doi.org/10.1109/VTC2021-Spring51267.2021.9448947},

isbn = {978-1-7281-8965-9},

year  = {2021},

date = {2021-06-15},

booktitle = {Proceedings of the 2021 IEEE 93rd Vehicular Technology Conference (VTC2021-Spring)},

pages = {1-5},

publisher = {IEEE},

abstract = {Fingerprint-based indoor positioning is widely used in many contexts, including pedestrian and autonomous vehicles navigation. Many approaches have used traditional Machine Learning models to deal with fingerprinting, being k-NN the most common used one. However, the reference data (or radio map) is generally limited, as data collection is a very demanding task, which degrades overall accuracy. In this work, we propose a novel approach to add random noise to the radio map which will be used in combination with an ensemble model. Instead of augmenting the radio map, we create n noisy versions of the same size, i.e. our proposed Indoor Positioning model will combine n estimations obtained by independent estimators built with the n noisy radio maps. The empirical results have shown that our proposed approach improves the baseline method results in around 10% on average.},

keywords = {Indoor positioning, Wi-Fi fingerprint, Wi-Fi mapping},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Quezada-Gaibor2020,

title = {Improving DBSCAN for Indoor Positioning Using Wi-Fi Radio Maps in Wearable and IoT Devices},

author = {Darwin Quezada-Gaibor and Lucie Klus and Joaquín Torres-Sospedra and Simona Elena Lohan and Jari Nurmi and Joaquín Huerta-Guijarro},

doi = {http://www.doi.org/10.1109/ICUMT51630.2020.9222411},

isbn = {978-1-7281-9281-9},

year  = {2020},

date = {2020-09-17},

booktitle = {Proceedings of the 12th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT), 5-8 October 2020. Online event},

pages = {208-213},

keywords = {A-wear, Indoor positioning, Internet of things, wearables, Wi-Fi mapping},

pubstate = {published},

tppubtype = {inproceedings}

}