ListarInstitute of New Imaging Technologies (INIT) por tema "fingerprinting"

Mostrando ítems 1-7 de 7

    • openAccess   Analysis of Received Signal Strength Quantization in Fingerprinting Localization 

      Khandker, Syed; Torres-Sospedra, Joaquín; Ristaniemi, Tapani MDPI (2020)
      In recent times, Received Signal Strength (RSS)-based Wi-Fi fingerprinting localization has become one of the most promising techniques for indoor localization. The primary aim of RSS is to check the quality of the signal ...

    • openAccess   Ensembling Multiple Radio Maps with Dynamic Noise in Fingerprint-based Indoor Positioning 

      Torres-Sospedra, Joaquín; Aranda Polo, Fernando Jesús; Álvarez, Fernando J.; Quezada Gaibor, Darwin; Silva, Ivo; Pendão, Cristiano; Moreira, Adriano Institute of Electrical and Electronics Engineers (2021-06-15)
      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, ...

    • openAccess   RSS Fingerprinting Dataset Size Reduction Using Feature-Wise Adaptive k-Means Clustering 

      Klus, Lucie; Quezada Gaibor, Darwin; Torres-Sospedra, Joaquín; Lohan, Elena Simona; Granell, Carlos; Nurmi, Jari IEEE (2020-10)
      Modern IoT devices, that include smartphones and wearables, usually have limited resources. They require efficient methods to optimize the use of internal storage, provide computational efficiency, and reduce energy ...

    • openAccess   Scalable and Efficient Clustering for Fingerprint-Based Positioning 

      Torres-Sospedra, Joaquín; Quezada Gaibor, Darwin; Nurmi, Jari; Koucheryavy, Yevgeni; Lohan, Elena Simona; Huerta, Joaquin IEEE (2023)
      Abstract: Indoor positioning based on IEEE 802.11 wireless LAN (Wi-Fi) fingerprinting needs a reference data set, also known as a radio map, in order to match the incoming fingerprint in the operational phase with the ...

    • closedAccess   Towards Accelerated Localization Performance Across Indoor Positioning Datasets 

      Klus, Lucie; Quezada Gaibor, Darwin; Torres-Sospedra, Joaquín; Lohan, Elena Simona; Granell, Carlos; Nurmi, Jari IEEE (2022)
      The localization speed and accuracy in the indoor scenario can greatly impact the Quality of Experience of the user. While many individual machine learning models can achieve comparable positioning performance, their ...

    • openAccess   Transfer Learning for Convolutional Indoor Positioning Systems 

      Klus, Roman; Klus, Lucie; Talvitie, Jukka; Pihlajasalo, Jaakko; Torres-Sospedra, Joaquín; Valkama, Mikko IEEE (2021-11-29)
      Fingerprinting is a widely used technique in indoor positioning, mainly due to its simplicity. Usually, this technique is used with the deterministic k - Nearest Neighbors (k-NN) algorithm. Utilizing a neural network model ...

    • openAccess   TUJI1 Dataset: Multi-device dataset for indoor localization with high measurement density 

      Klus, Lucie; Klus, Roman; Lohan, Elena Simona; Nurmi, Jari; Granell, Carlos; Valkama, Mikko; Talvitie, Jukka; Casteleyn, Sven; Torres-Sospedra, Joaquín Elsevier (2024-03-22)
      Positioning in indoor scenarios using signals of opportunity is an effective solution enabling accurate and reliable performance in Global Navigation Satellite System (GNSS)-obscured scenarios. Despite the availability of ...