Listar por autoría "4ca1e4d2-a2cd-4b9c-b3d9-922246fb6c75"

Mostrando ítems 1-13 de 13

    • openAccess   A Survey on Wearable Technology: History, State-of-the-Art and Current Challenges 

      Ometov, Aleksandr; Shubina, Viktoriia; Klus, Lucie; Skibińska, Justyna; Saafi, Salwa; Pascacio, Pavel; Flueratoru, Laura; Quezada Gaibor, Darwin; Chukhno, Nadezhda; Chukhno, Olga; Ali, Asad; Channa, Asma; Svertoka, Ekaterina; QAIM, WALEED BIN; Casanova-Marqués, Raúl; Holcer, Sylvia; Torres-Sospedra, Joaquín; Casteleyn, Sven; Ruggeri, Giuseppe; ARANITI, Giuseppe; Burget, Radim; Hosek, Jiri Elsevier (2021-04-08)
      Technology is continually undergoing a constituent development caused by the appearance of billions new interconnected “things” and their entrenchment in our daily lives. One of the underlying versatile technologies, namely ...

    • openAccess   Cloud Platforms for Context-Adaptive Positioning and Localisation in GNSS-Denied Scenarios—A Systematic Review 

      Quezada Gaibor, Darwin; Torres-Sospedra, Joaquín; Nurmi, Jari; Koucheryavy, Yevgeni; Huerta, Joaquin MDPI (2021-12-24)
      Cloud Computing and Cloud Platforms have become an essential resource for businesses, due to their advanced capabilities, performance, and functionalities. Data redundancy, scalability, and security, are among the key ...

    • 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   Discovering location based services: A unified approach for heterogeneous indoor localization systems 

      Furfari, Francesco; Crivello, Antonino; Baronti, Paolo; Barsocchi, Paolo; GIROLAMI, MICHELE; Palumbo, Filippo; Quezada Gaibor, Darwin; Mendoza-Silva, Germán Martín; Torres-Sospedra, Joaquín Elsevier B.V. (2021-03-01)
      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 ...

    • 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   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 ...

    • closedAccess   Lightweight Hybrid CNN-ELM Model for Multi-building and Multi-floor Classification 

      Quezada Gaibor, Darwin; Torres-Sospedra, Joaquín; Nurmi, Jari; Koucheryavy, Yevgeni; Huerta, Joaquin IEEE (2022)
      Machine learning models have become an essential tool in current indoor positioning solutions, given their high capabilities to extract meaningful information from the environment. Convolutional neural networks (CNNs) ...

    • openAccess   Lightweight Wi-Fi Fingerprinting with a Novel RSS Clustering Algorithm 

      Quezada Gaibor, Darwin; Torres-Sospedra, Joaquín; Nurmi, Jari; Koucheryavy, Yevgeni; Huerta, Joaquin IEEE (2021-11-29)
      Nowadays, several indoor positioning solutions sup-port Wi-Fi and use this technology to estimate the user position. It is characterized by its low cost, availability in indoor and outdoor environments, and a wide variety ...

    • openAccess   New Cluster Selection and Fine-grained Search for k-Means Clustering and Wi-Fi Fingerprinting 

      Torres-Sospedra, Joaquín; Quezada Gaibor, Darwin; Mendoza-Silva, Germán Martín; Nurmi, Jari; Koucheryavy, Yevgeni; Huerta, Joaquin IEEE (2020-06-02)
      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 ...

    • openAccess   Off-Line Evaluation of Indoor Positioning Systems in Different Scenarios: The Experiences From IPIN 2020 Competition 

      Potortì, Francesco; Torres-Sospedra, Joaquín; Quezada Gaibor, Darwin; Jimenez Ruiz, Antonio Ramon; Seco, Fernando; Perez-Navarro, Antoni; ortiz, miguel; Zhu, Ni; Renaudin, Valerie; Ichikari, Ryosuke Institute of Electrical and Electronics Engineers (2022-03)
      Every 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 ...

    • 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 ...