Mantenimiento área industrial

The increasing adoption of location-based services drives the pervasive adoption of localization systems available anywhere. Environments equipped with multiple indoor localization systems (ILSs) require managing the transition from one ILS to another in order to continue localizing the user’s device even when moving indoor or outdoor. In this article, we focus on the handoff procedure,… Continuar leyendo Integrating Indoor Localization Systems Through a Handoff Protocol

Visual–inertial odometry (VIO), the fusion of visual and inertial sensor data, has been shown to be functional for navigation in global-navigation-satellite-system-denied environments. Recently, dense-optical-flow-based end-to-end trained deep learning VIO models have gained superior performance in outdoor navigation. In this article, we introduced a novel visual–inertial sensor fusion approach based on vision transformer architecture with a… Continuar leyendo A Novel Cross-Attention-Based Pedestrian Visual–Inertial Odometry With Analyses Demonstrating Challenges in Dense Optical Flow

Radio-frequency technologies have been largely explored to deliver reliable indoor localization systems. However, at the current stage, none of the proposed technologies represent a de-facto standard. Although RSS-based (received signal strength) techniques have been extensively studied, they suffer of a number of side-effects mainly caused by the complexity of radio propagation in indoor environments. A… Continuar leyendo An Experimental Evaluation Based on Direction Finding Specification for Indoor Localization and Proximity Detection

Social interaction behaviors change as a result of both physical and psychiatric problems, and it is important to identify subtle changes in group activity engagements for monitoring the mental health of patients in clinics. This work proposes a system to identify when and where group formations occur in an approximately 1700 $ text{m}^{2}$ therapeutic built environment… Continuar leyendo Indoor Group Identification and Localization Using Privacy-Preserving Edge Computing Distributed Camera Network

The 3-D nature of modern smart applications has imposed significant 3-D positioning accuracy requirements, especially in indoor environments. However, a major limitation of most existing indoor localization systems is their focus on estimating positions mainly in the horizontal plane, overlooking the crucial vertical dimension. This neglect presents considerable challenges in accurately determining the 3-D position… Continuar leyendo Radar-Based Millimeter-Wave Sensing for Accurate 3-D Indoor Positioning: Potentials and Challenges

The power over Ethernet (PoE)-enabled visible light positioning (VLP) networks as a promising technology can significantly enhance accuracy and cost-effectiveness of indoor positioning. However, both the limited bandwidth of the light-emitting diode (LED) and the low sampling rate of the receiver have a negative impact on the positioning performance. Moreover, time synchronization requirements between transmitters… Continuar leyendo PoE-Enabled Visible Light Positioning Network With Low Bandwidth Requirement and High Precision Pulse Reconstruction

This article presents UnSpoof, an ultrawideband localization system that can detect and localize distance-spoofing tags with a few collaborative passively receiving anchors. We propose novel formulations that enable passively receiving anchors to deduce their time-of-flight (ToF) and time-difference-of-arrival (TDoA) just by overhearing standard two-way ranging messages between the tag and one active anchor. Our ToF… Continuar leyendo Spoofing Evident and Spoofing Deterrent Localization Using Ultrawideband (UWB) Active–Passive Ranging

To enhance the utilization of concentrated solar power (CSP), and reduce the wind abandonment rate of wind power (WP) and the carbon emissions from the traditional coal-fired unit (CFU), this study introduces oxygen-enriched combustion capture technology to retrofit the conventional CFU, and configures CSP with heat recovery unit (HRU) for participation in heating, along with… Continuar leyendo Optimal Capacity Configuration of a Low-Carbon Energy System Considering Carbon Capture Technology and Hydrogen-Diversified Utilization Under Multiple Operational Scenarios

The limited size of existing datasets and signal variability have hindered EEG-based emotion recognition. In this paper, we present a solution that simultaneously addresses both problems. Generative Adversarial Networks (GANs) have recently shown notable data augmentation (DA) success. Therefore, we leverage a GAN-based DA technique to enhance the robustness of our proposed emotion recognition model… Continuar leyendo A Graph Neural Network for EEG-Based Emotion Recognition With Contrastive Learning and Generative Adversarial Neural Network Data Augmentation

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