NLOS Identification and Mitigation Using Low-Cost UWB Devices

[Abstract] Indoor location systems based on ultra-wideband (UWB) technology have become very popular in recent years following the introduction of a number of low-cost devices on the market capable of providing accurate distance measurements. Although promising, UWB devices also suffer from the classic problems found when working in indoor scenarios, especially when there is no a clear line-of-sight (LOS) between the emitter and the receiver, causing the estimation error to increase up to several meters. In this work, machine learning (ML) techniques are employed to analyze several sets of real UWB measurements, captured in different scenarios, to try to identify the measurements facing non-line-of-sight (NLOS) propagation condition. Additionally, an ulterior process is carried out to mitigate the deviation of these measurements from the actual distance value between the devices. The results show that ML techniques are suitable to identify NLOS propagation conditions and also to mitigate the error of the estimates when there is LOS between the emitter and the receiver.Xunta de Galicia; ED431C 2016-045Xunta de Galicia; ED431G/01Agencia Estatal de Investigación de España; TEC2016-75067-C4-1-

Environmental Cross-Validation of NLOS Machine Learning Classification/Mitigation with Low-Cost UWB Positioning Systems

[Abstract] Indoor positioning systems based on radio frequency inherently present multipath-related phenomena. This causes ranging systems such as ultra-wideband (UWB) to lose accuracy when detecting secondary propagation paths between two devices. If a positioning algorithm uses ranging measurements without considering these phenomena, it will face critical errors in estimating the position. This work analyzes the performance obtained in a localization system when combining location algorithms with machine learning techniques applied to a previous classification and mitigation of the propagation effects. For this purpose, real-world cross-scenarios are considered, where the data extracted from low-cost UWB devices for training the algorithms come from a scenario different from that considered for the test. The experimental results reveal that machine learning (ML) techniques are suitable for detecting non-line-of-sight (NLOS) ranging values in this situation.Xunta de Galicia; ED431C 2016-045Xunta de Galicia; ED431G/01Agencia Estatal de Investigación de España; TEC2016-75067-C4-1-

Improving semi-supervised learning for audio classification with FixMatch

Including unlabeled data in the training process of neural networks using Semi-Supervised Learning (SSL) has shown impressive results in the image domain, where state-of-the-art results were obtained with only a fraction of the labeled data. The commonality between recent SSL methods is that they strongly rely on the augmentation of unannotated data. This is vastly unexplored for audio data. In this work, SSL using the state-of-the-art FixMatch approach is evaluated on three audio classification tasks, including music, industrial sounds, and acoustic scenes. The performance of FixMatch is compared to Convolutional Neural Networks (CNN) trained from scratch, Transfer Learning, and SSL using the Mean Teacher approach. Additionally, a simple yet effective approach for selecting suitable augmentation methods for FixMatch is introduced. FixMatch with the proposed modifications always outperformed Mean Teacher and the CNNs trained from scratch. For the industrial sounds and music datasets, the CNN baseline performance using the full dataset was reached with less than 5% of the initial training data, demonstrating the potential of recent SSL methods for audio data. Transfer Learning outperformed FixMatch only for the most challenging dataset from acoustic scene classification, showing that there is still room for improvement

HRTFs Measurement Based on Periodic Sequences Robust towards Nonlinearities in Automotive Audio

The head related transfer functions (HRTFs) represent the acoustic path transfer functions between sound sources in 3D space and the listener’s ear. They are used to create immersive audio scenarios or to subjectively evaluate sound systems according to a human-centric point of view. Cars are nowadays the most popular audio listening environment and the use of HRTFs in automotive audio has recently attracted the attention of researchers. In this context, the paper proposes a measurement method for HRTFs based on perfect or orthogonal periodic sequences. The proposed measurement method ensures robustness towards the nonlinearities that may affect the measurement system. The experimental results considering both an emulated scenario and real measurements in a controlled environment illustrate the effectiveness of the approach and compare the proposed method with other popular approaches

Multi-Sensor Accurate Forklift Location and Tracking Simulation in Industrial Indoor Environments

[Abstract] Location and tracking needs are becoming more prominent in industrial environments nowadays. Process optimization, traceability or safety are some of the topics where a positioning system can operate to improve and increase the productivity of a factory or warehouse. Among the different options, solutions based on ultra-wideband (UWB) have emerged during recent years as a good choice to obtain highly accurate estimations in indoor scenarios. However, the typical harsh wireless channel conditions found inside industrial environments, together with interferences caused by workers and machinery, constitute a challenge for this kind of system. This paper describes a real industrial problem (location and tracking of forklift trucks) that requires precise internal positioning and presents a study on the feasibility of meeting this challenge using UWB technology. To this end, a simulator of this technology was created based on UWB measurements from a set of real sensors. This simulator was used together with a location algorithm and a physical model of the forklift to obtain estimations of position in different scenarios with different obstacles. Together with the simulated UWB sensor, an additional inertial sensor and optical sensor were modeled in order to test its effect on supporting the location based on UWB. All the software created for this work is published under an open-source license and is publicly available.Xunta de Galicia; ED431C 2016-045Xunta de Galicia; ED431G/01Agencia Estatal de Investigación de España; TEC2016-75067-C4-1-

Stress evaluation in simulated autonomous and manual driving through the analysis of skin potential response and electrocardiogram signals

The evaluation of car drivers\u2019 stress condition is gaining interest as research on Autonomous Driving Systems (ADS) progresses. The analysis of the stress response can be used to assess the acceptability of ADS and to compare the driving styles of different autonomous drive algorithms. In this contribution, we present a system based on the analysis of the Electrodermal Activity Skin Potential Response (SPR) signal, aimed to reveal the driver\u2019s stress induced by different driving situations. We reduce motion artifacts by processing two SPR signals, recorded from the hands of the subjects, and outputting a single clean SPR signal. Statistical features of signal blocks are sent to a Supervised Learning Algorithm, which classifies between stress and normal driving (non-stress) conditions. We present the results obtained from an experiment using a professional driving simulator, where a group of people is asked to undergo manual and autonomous driving on a highway, facing some unexpected events meant to generate stress. The results of our experiment show that the subjects generally appear more stressed during manual driving, indicating that the autonomous drive can possibly be well received by the public. During autonomous driving, however, significant peaks of the SPR signal are evident during unexpected events. By examining the electrocardiogram signal, the average heart rate is generally higher in the manual case compared to the autonomous case. This further supports our previous findings, even if it may be due, in part, to the physical activity involved in manual driving

Segmentation approaches for diabetic foot disorders

Thermography enables non-invasive, accessible, and easily repeated foot temperature measurements for diabetic patients, promoting early detection and regular monitoring protocols, that limit the incidence of disabling conditions associated with diabetic foot disorders. The establishment of this application into standard diabetic care protocols requires to overcome technical issues, particularly the foot sole segmentation. In this work we implemented and evaluated several segmentation approaches which include conventional and Deep Learning methods. Multimodal images, constituted by registered visual-light, infrared and depth images, were acquired for 37 healthy subjects. The segmentation methods explored were based on both visual-light as well as infrared images, and optimization was achieved using the spatial information provided by the depth images. Furthermore, a ground truth was established from the manual segmentation performed by two independent researchers. Overall, the performance level of all the implemented approaches was satisfactory. Although the best performance, in terms of spatial overlap, accuracy, and precision, was found for the Skin and U-Net approaches optimized by the spatial information. However, the robustness of the U-Net approach is preferred.This research was funded by the IACTEC Technological Training program, grant number TF INNOVA 2016–2021. This work was completed while Abián Hernández was beneficiary of a pre-doctoral grant given by the “Agencia Canaria de Investigacion, Innovacion y Sociedad de la Información (ACIISI)” of the “Consejería de Economía, Industria, Comercio y Conocimiento” of the “Gobierno de Canarias”, which is partly financed by the European Social Fund (FSE) (POC 2014–2020, Eje 3 Tema Prioritario 74 (85%))

SmartFog: Training the Fog for the energy-saving analytics of Smart-Meter data

In this paper, we characterize the main building blocks and numerically verify the classification accuracy and energy performance of SmartFog, a distributed and virtualized networked Fog technological platform for the support for Stacked Denoising Auto-Encoder (SDAE)-based anomaly detection in data flows generated by Smart-Meters (SMs). In SmartFog, the various layers of an SDAE are pretrained at different Fog nodes, in order to distribute the overall computational efforts and, then, save energy. For this purpose, a new Adaptive Elitist Genetic Algorithm (AEGA) is “ad hoc” designed to find the optimized allocation of the SDAE layers to the Fog nodes. Interestingly, the proposed AEGA implements a (novel) mechanism that adaptively tunes the exploration and exploitation capabilities of the AEGA, in order to quickly escape the attraction basins of local minima of the underlying energy objective function and, then, speed up the convergence towards global minima. As a matter of fact, the main distinguishing feature of the resulting SmartFog paradigm is that it accomplishes the joint integration on a distributed Fog computing platform of the anomaly detection functionality and the minimization of the resulting energy consumption. The reported numerical tests support the effectiveness of the designed technological platform and point out that the attained performance improvements over some state-of-the-art competing solutions are around 5%, 68% and 30% in terms of detection accuracy, execution time and energy consumption, respectively

Assessment and Real Time Implementation of Wireless Communications Systems and Applications in Transportation Systems

Programa Oficial de Doutoramento en Tecnoloxías da Información e das Comunicacións en Redes Móbiles. 5029V01[Resumo] Os sistemas de comunicación sen fíos de cuarta e quinta xeración (4G e 5G) utilizan unha capa física (PHY) baseada en modulacións multiportadora para a transmisión de datos cun gran ancho de banda. Este tipo de modulacións proporcionan unha alta eficiencia espectral á vez que permiten corrixir de forma sinxela os efectos da canle radio. Estes sistemas utilizan OFDMA como mecanismo para a repartición dos recursos radio dispoñibles entre os diferentes usuarios. Este repartimento realízase asignando un subconxunto de subportadoras a cada usuario nun instante de tempo determinado. Isto aporta unha gran flexibilidade ó sistema que lle permite adaptarse tanto ós requisitos de calidade de servizo dos usuarios como ó estado da canle radio. A capa de acceso ó medio (MAC) destes sistemas encárgase de configurar os diversos parámetros proporcionados pola capa física OFDMA, ademais de xestionar os diversos fluxos de información de cada usuario, transformando os paquetes de capas superiores en paquetes da capa física. Neste traballo estúdase o deseño e implementación das capas MAC e PHY de sistemas de comunicación 4G ademais da súa aplicabilidade en sistemas de transporte ferroviarios. Por unha parte, abórdase o deseño e implementación en tempo real do estándar WiMAX. Estúdanse os mecanismos necesarios para establecer comunicacións bidireccionais entre unha estación base e múltiples dispositivos móbiles. Ademais, estúdase como realizar esta implementación nunha arquitectura hardware baseada en DSPs e FPGAs, na que se implementan as capas MAC e PHY. Dado que esta arquitectura ten uns recursos computacionais limitados, tamén se estudan as necesidades de cada módulo do sistema para poder garantir o funcionamento en tempo real do sistema completo. Por outra parte, tamén se estuda a aplicabilidade dos sistemas 4G a sistemas de transporte públicos. Os sistemas de comunicacións e sinalización son unha parte vital para os sistemas de transporte ferroviario e metro. As comunicacións sen fíos utilizadas por estes sistemas deben ser robustas e proporcionar unha alta fiabilidade para permitir a supervisión, control e seguridade do tráfico ferroviario. Para levar a cabo esta avaliación de viabilidade realízanse simulacións de redes de comunicacións LTE en contornos de transporte ferroviarios, comprobando o cumprimento dos requisitos de fiabilidade e seguridade. Realízanse diferentes simulacións do sistema de comunicacións para poder ser avaliadas e seleccionar a configuración e arquitectura do sistema máis axeitada en función do escenario considerado. Tamén se efectúan simulacións de redes baseadas en Wi-Fi, dado que é a solución máis utilizada nos metros, para confrontar os resultados cos obtidos para LTE. Para que os resultados das simulacións sexan realistas débense empregar modelos de propagación radio axeitados. Nas simulacións utilízanse tanto modelos deterministas como modelos baseados nos resultados de campañas de medida realizadas nestes escenarios. Nas simulacións empréganse os diferentes fluxos de información destes escenarios para comprobar que se cumpren os requisitos de calidade de servicio (QoS). Por exemplo, os fluxos críticos para o control ferroviario, como European Train Control System (ETCS) ou Communication-Based Train Control (CBTC), necesitan unha alta fiabilidade e un retardo mínimo nas comunicacións para garantir o correcto funcionamento do sistema.[Resumen] Los sistemas de comunicación inalámbricos de cuarta y quinta generación (4G y 5G) utilizan una capa física (PHY) basada en modulaciones multiportadora para la transmisión de datos con un gran ancho de banda. Este tipo de modulaciones han demostrado tener una alta eficiencia espectral a la vez que permiten corregir de forma sencilla los efectos del canal radio. Estos sistemas utilizan OFDMA como mecanismo para el reparto de los recursos radio disponibles entre los diferentes usuarios. Este reparto se realiza asignando un subconjunto de subportadoras a cada usuario en un instante de tiempo determinado. Esto aporta una gran flexibilidad al sistema que le permite adaptarse tanto a los requisitos de calidad de servicio de los usuarios como al estado del canal radio. La capa de acceso al medio (MAC) de estos sistemas se encarga de configurar los diversos parámetros proporcionados por la capa física OFDMA, además de gestionar los diversos flujos de información de cada usuario, transformando los paquetes de capas superiores en paquetes de la capa física. En este trabajo se estudia el diseño e implementación de las capas MAC y PHY de sistemas de comunicación 4G además de su aplicabilidad en sistemas de transporte ferroviarios. Por una parte, se aborda el diseño e implementación en tiempo real del estándar WiMAX. Se estudian los mecanismos necesarios para establecer comunicaciones bidireccionales entre una estación base y múltiples dispositivos móviles. Además, se estudia cómo realizar esta implementación en una arquitectura hardware basada en DSPs y FPGAs, en la que se implementan las capas MAC y PHY. Dado que esta arquitectura tiene unos recursos computacionales limitados, también se estudian las necesidades de cada módulo del sistema para poder garantizar el funcionamiento en tiempo real del sistema completo. Por otra parte, también se estudia la aplicabilidad de los sistemas 4G a sistemas de transporte públicos. Los sistemas de comunicaciones y señalización son una parte vital para los sistemas de transporte ferroviario y metro. Las comunicaciones inalámbricas utilizadas por estos sistemas deben ser robustas y proporcionar una alta fiabilidad para permitir la supervisión, control y seguridad del tráfico ferroviario. Para llevar a cabo esta evaluación de viabilidad se realizan simulaciones de redes de comunicaciones LTE en entornos de transporte ferroviarios, comprobando si se cumplen los requisitos de fiabilidad y seguridad. Se realizan diferentes simulaciones del sistema de comunicaciones para poder ser evaluados y seleccionar la configuración y arquitectura del sistema más adecuada en función del escenario planteado. También se efectúan simulaciones de redes basadas en Wi-Fi, dado que es la solución más utilizada en los metros, para comparar los resultados con los obtenidos para LTE. Para que los resultados de las simulaciones sean realistas se deben utilizar modelos de propagación radio apropiados. En las simulaciones se utilizan tanto modelos deterministas como modelos basados en los resultados de campañas de medida realizadas en estos escenarios. En las simulaciones se utilizan los diferentes flujos de información de estos escenarios para comprobar que se cumplen sus requisitos de calidad de servicio. Por ejemplo, los flujos críticos para el control ferroviario, como European Train Control System (ETCS) o Communication-Based Train Control (CBTC), necesitan una alta fiabilidad y un retardo bajo en las comunicaciones para garantizar el correcto funcionamiento del sistema.[Abstract] The fourth and fifth generation wireless communication systems (4G and 5G) use a physical layer (PHY) based on multicarrier modulations for data transmission using high bandwidth. This type of modulations has shown to provide high spectral efficiency while allowing low complexity radio channel equalization. These systems use OFDMA as a mechanism for distributing the available radio resources among different users. This allocation is done by assigning a subset of subcarriers to each user in a given instant of time. This provides great flexibility to the system that allows it to adapt to both the quality of service requirements of users and the radio channel state. The media access layer (MAC) of these systems is in charge of configuring the multiple OFDMA PHY layer parameters, in addition to managing the data flows of each user, transforming the higher layer packets into PHY layer packets. This work studies the design and implementation of MAC and PHY layers of 4G communication systems as well as their applicability in rail transport systems. On the one hand, the design and implementation in real time of the WiMAX standard is addressed. The required mechanisms to establish bidirectional communications between a base station and several mobile devices are also evaluated. Moreover, a MAC layer and PHY layer implementation is presented, using a hardware architecture based in DSPs and FPGAs. Since this architecture has limited computational resources, the requirements of each processing block of the system are also studied in order to guarantee the real time operation of the complete system. On the other hand, the applicability of 4G systems to public transportation systems is also studied. Communications and signaling systems are a vital part of rail and metro transport systems. The wireless communications used by these systems must be robust and provide high reliability to enable the supervision, control and safety of rail traffic. To carry out this feasibility assessment, LTE communications network simulations are performed in rail transport environments to verify that reliability and safety requirements are met. Several simulations are carried out in order to evaluate the system performance and select the most appropriate system configuration in each case. Simulations of Wi-Fi based networks are also carried out, since it is the most used solution in subways, to compare the results with those obtained for LTE. To perform the simulations correctly, appropriate radio propagation models must be used. Both deterministic models and models based on the results of measurement campaigns in these scenarios are used in the simulations. The simulations use the different information flows present in the railway transportation systems to verify that its quality of service requirements are met. For example, critical flows for railway control, such as the European Train Control System (ETCS) or Communication-Based Train Control (CBTC), require high reliability and low delay communications to ensure the proper functioning of the system

A new generalized projection and its application to acceleration of audio declipping

In convex optimization, it is often inevitable to work with projectors onto convex sets composed with a linear operator. Such a need arises from both the theory and applications, with signal processing being a prominent and broad field where convex optimization has been used recently. In this article, a novel projector is presented, which generalizes previous results in that it admits to work with a broader family of linear transforms when compared with the state of the art but, on the other hand, it is limited to box-type convex sets in the transformed domain. The new projector is described by an explicit formula, which makes it simple to implement and requires a low computational cost. The projector is interpreted within the framework of the so-called proximal splitting theory. The convenience of the new projector is demonstrated on an example from signal processing, where it was possible to speed up the convergence of a signal declipping algorithm by a factor of more than two