Listar INIT_Congressos i Informes por autoría "b1cc9f02-8702-4800-83bb-c805cea706c8"

Mostrando ítems 1-7 de 7

    • closedAccess   Data Cleansing for Indoor Positioning Wi-Fi Fingerprinting Datasets 

      Quezada Gaibor, Darwin; Klus, Lucie; Torres-Sospedra, Joaquín; Lohan, Elena Simona; Nurmi, Jari; Granell, Carlos; Huerta, Joaquin IEEE (2022)
      Wearable and IoT devices requiring positioning and localisation services grow in number exponentially every year. This rapid growth also produces millions of data entries that need to be pre-processed prior to being ...

    • openAccess   Improving DBSCAN for Indoor Positioning Using Wi-Fi Radio Maps in Wearable and IoT Devices 

      Quezada Gaibor, Darwin; Klus, Lucie; Torres-Sospedra, Joaquín; Lohan, Elena Simona; Nurmi, Jari; Huerta, Joaquin IEEE (2020-10-05)
      IoT devices and wearables may rely on Wi-Fi finger-printing to estimate the position indoors. The limited resources of these devices make it necessary to provide adequate methods to reduce the operational computational ...

    • openAccess   Lossy Compression Methods for Performance-Restricted Wearable Devices 

      Klus, Lucie; Lohan, Elena Simona; Granell, Carlos; Nurmi, Jari CEUR Workshop Proceedings (2020)
      With the increasing popularity, diversity, and utilization of wearable devices, the data transfer-andstorage efficiency becomes increasingly important. This paper evaluates a set of compression techniques regarding their ...

    • 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 ...

    • 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   Towards Ubiquitous Indoor Positioning: Comparing Systems across Heterogeneous Datasets 

      Torres-Sospedra, Joaquín; Silva, Ivo; Klus, Lucie; Quezada Gaibor, Darwin; Crivello, Antonino; Barsocchi, Paolo; Pendão, Cristiano; Lohan, Elena Simona; Nurmi, Jari; Moreira, Adriano IEEE (2021-11-29)
      The evaluation of Indoor Positioning Systems (IPSs) mostly relies on local deployments in the researchers’ or partners’ facilities. The complexity of preparing comprehensive experiments, collecting data, and considering ...

    • 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 ...