Yazar "Kouhalvandi, Lida" seçeneğine göre listele

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  • Küçük Resim
    Öğe
    Optimizing indoor localization accuracy with neural network performance metrics and software-defined IEEE 802.11az Wi-Fi set-up
    (IEEE, 2023-10-28) Kouhalvandi, Lida; Aygün, Sercan; Matekovits, Ladislau; Miramirkhani, Farshad
    Accurately classifying regions based on Wi-Fi signals can be a difficult task, especially when considering different frequency values. In this study, we aimed to improve the accuracy of indoor localization by developing a novel approach that does not rely on pre-trained models. To achieve this, fingerprints from the IEEE 802.11az standard were randomly selected, and the data samples were trained using parameterized station characteristics and neural network hyperparameters. The impact of each parameter on the localization accuracy was measured, and performance monitoring metrics such as F1-Measure and confusion matrix-based metrics were evaluated. Furthermore, the Thompson sampling (TS) algorithm was employed to determine the optimal parameters, which helped to achieve the best possible accuracy. The proposed approach demonstrated improved accuracy in region localization compared to conventional heuristic approaches which typically yield an accuracy range of 65% to 77%. The proposed approach achieved up to 80% accuracy in region localization and could be a promising solution for indoor localization in various settings.
  • Küçük Resim
    Öğe
    A review of recent innovations in remote health monitoring
    (Multidisciplinary Digital Publishing Institute (MDPI), 2023-12) Dalloul, Ahmed Hany; Miramirkhani, Farshad; Kouhalvandi, Lida
    The development of remote health monitoring systems has focused on enhancing healthcare services’ efficiency and quality, particularly in chronic disease management and elderly care. These systems employ a range of sensors and wearable devices to track patients’ health status and offer real-time feedback to healthcare providers. This facilitates prompt interventions and reduces hospitalization rates. The aim of this study is to explore the latest developments in the realm of remote health monitoring systems. In this paper, we explore a wide range of domains, spanning antenna designs, small implantable antennas, on-body wearable solutions, and adaptable detection and imaging systems. Our research also delves into the methodological approaches used in monitoring systems, including the analysis of channel characteristics, advancements in wireless capsule endoscopy, and insightful investigations into sensing and imaging techniques. These advancements hold the potential to improve the accuracy and efficiency of monitoring, ultimately contributing to enhanced health outcomes for patients.