7 documents found, page 1 of 1
Offsite evaluation of localization systems: criteria, systems, and results from...
Potortì, Francesco; Crivello, Antonino; Lee, Soyeon; Vladimirov, Blagovest; Park, Sangjoon; Chen, Yushi; Wang, Long; Chen, Runze; Zhao, Fang; Zhuge, YueIndoor positioning is a thriving research area, which is slowly gaining market momentum. Its applications are mostly customized, ad hoc installations; ubiquitous applications analogous to Global Navigation Satellite System for outdoors are not available because of the lack of generic platforms, widely accepted standards and interoperability protocols. In this context, the indoor positioning and indoor navigatio...
Accuracy of a single position estimate for <italic>k</italic>NN-based fingerpri...
Perez-Navarro, Antoni; Montoliu, Raul; Sansano-Sansano, Emilio; Martinez-Garcia, Marina; Femenia, Ruben; Torres-Sospedra, JoaquínIndoor Positioning Systems usually consider the average positioning error over a set of evaluation samples, or a quartile of that value, as the global error. However, they do not provide a metric for the uncertainty for each individual position estimation. In this paper, we apply the error propagation theory to the kNN algorithm in Wi-Fi fingerprint-based indoor positioning. Our proposed method does not only re...
Comprehensive analysis of applied machine learning in indoor positioning based ...
Bellavista-Parent, Vladimir; Torres-Sospedra, Joaquín; Perez-Navarro, AntoniNowadays, there are a multitude of solutions for indoor positioning, as opposed to standards for outdoor positioning such as GPS. Among the different existing studies on indoor positioning, the use of Wi-Fi signals together with Machine Learning algorithms is one of the most important, as it takes advantage of the current deployment of Wi-Fi networks and the increase in the computing power of computers. Thanks ...
Off-line evaluation of indoor positioning systems in different scenarios: the e...
Potorti, Francesco; Torres-Sospedra, Joaquín; Quezada-Gaibor, Darwin; Jimenez, Antonio Ramon; Seco, Fernando; Perez-Navarro, Antoni; Ortiz, MiguelEvery year, for ten years now, the IPIN competition has aimed at evaluating real-world indoor localisation systems by testing them in a realistic environment, with realistic movement, using the EvAAL framework. The competition provided a unique overview of the state-of-the-art of systems, technologies, and methods for indoor positioning and navigation purposes. Through fair comparison of the performance achieve...
Advances in indoor positioning and indoor navigation
Perez-Navarro, Antoni; Montoliu, Raúl; Torres-Sospedra, JoaquínLocating devices in indoor environments has become a key issue for many emerging location-based applications and intelligent spaces in different fields [...]
Efficient tuning of k NN hyperparameters for indoor positioning with N-TBEA
Montoliu, Raul; Perez-Navarro, Antoni; Torres-Sospedra, JoaquínMachine Learning is a very popular approach for indoor positioning. However, most of models rely on a set of hyperparameters, which need to be properly set. When the number of hyperparameters is large, exploring all the combinations of values (what is known as brute force) can be computationally prohibitive, especially in those cases where the training or operational time is high, such as in the kNN algorithm i...
The IPIN 2019 indoor localisation competition-description and results
Potorti, Francesco; Park, Sangjoon; Crivello, Antonino; Palumbo, Filippo; Girolami, Michele; Barsocchi, Paolo; Lee, Soyeon; Torres-Sospedra, JoaquínIPIN 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 m2 outdoors and and 6000 m2 indoors...