المؤلفون: Sansano Sansano, Emilio

المساهمون: University/Department: Universitat Jaume I. Escola de Doctorat

مرشدي الرسالة: Montoliu Colás, Raúl, Belmonte Fernández, Óscar

المصدر: TDX (Tesis Doctorals en Xarxa)

مصطلحات موضوعية: Machine learning, Deep learning, Indoor localization, Human activity recognition, Convolutional Neural Network, LSTM, Tecnologies de la informació i les comunicacions (TIC)

الوصف: This thesis approaches the study of several machine learning techniques to improve the performance of indoor positioning systems, with a special focus on wearable and low-cost devices. It also presents some tools designed to facilitate the research in this field through the development of a software framework for indoor positioning-related research, and the creation of a web platform committed to becoming a collaborative repository of data. The framework has been developed as an open-source package for the R language platform. This allows other users to collaborate in the development of future functionality.

الوصف (مترجم): Esta tesis aborda el estudio de una serie de técnicas basadas en el aprendizaje automático (machine learning), con la intención de mejorar el rendimiento de los sistemas de posicionamiento en interiores, haciendo especial hincapié en el uso de dispositivos portátiles de bajo coste. Tambien se presentan dos herramientas destinadas a facilitar la investigación en este campo, mediante el desarrollo de un paquete de software para el estudio en el campo del posicionamiento en interiores, y mediante la creación de una plataforma web pensada para servir como un repositorio colaborativo de datos. El paquete de software ha sido desarrollado como software abierto usando el lenguaje R, con el objeto de permitir a otros usuarios colaborar en el desarrollo de futuras funcionalidades.
Programa de Doctorat en Informàtica

وصف الملف: application/pdf

الوصول الحر: http://hdl.handle.net/10803/670346Test

المؤلفون: Gaviña Rueda, Javier, Montoliu Colás, Raul, Sansano-Sansano, Emilio, Martínez García, Marina, Lluva-Plaza, Sergio, Jiménez Martín, Ana, Villadangos, Jose M., García Domínguez, Juan Jesús

مصطلحات موضوعية: Association rules, Decision trees, Indoor localisation, People Monitoring, Sensor networks

الوصف: Monitoring the activities and routines of the elderly requires continuous work and effort on the part of the care staff. It is vital to follow up on each user since abnormal behaviour could reveal the presence of a medical condition and, in these cases, early intervention is of utmost importance. In this paper, we deploy a room-level symbolic location system based on Bluetooth Low Energy (BLE) technology and present the results obtained from applying several methods capable of determining daily and weekly habits, non-invasive, using association rules and decision trees.

وصف الملف: application/pdf

العلاقة: CEUR Workshop Proceedings, Volume 3581 (2023). 13th International Conference on Indoor Positioning and Indoor Navigation. Work in Progress Papers, IPIN-WiP, Nuremberg 25-28 September 2023.; https://ceur-ws.org/Vol-3581Test/; Rueda, J. G., Colás, R. M., Sansano-Sansano, E., Martínez-García, M., Plaza, S. L., Martín, A. J., . & Domínguez, J. J. G. . "Automatic And Non-Invasive Analysis Of Behavioural Routines Using BLE Technology". In CEUR Workshop Proceedings, Volume 3581 (2023). 13th International Conference on Indoor Positioning and Indoor Navigation. Work in Progress Papers, IPIN-WiP, Nuremberg 25-28 September 2023. Code 195084; http://hdl.handle.net/10234/207239Test

الإتاحة: http://hdl.handle.net/10234/207239Test

المؤلفون: Antsfeld, Leonid, Chidlovskii, Boris, Sansano-Sansano, Emilio

مصطلحات موضوعية: Computer Science - Machine Learning, Computer Science - Networking and Internet Architecture, Computer Science - Robotics, H.4

الوصف: We address the indoor localization problem, where the goal is to predict user's trajectory from the data collected by their smartphone, using inertial sensors such as accelerometer, gyroscope and magnetometer, as well as other environment and network sensors such as barometer and WiFi. Our system implements a deep learning based pedestrian dead reckoning (deep PDR) model that provides a high-rate estimation of the relative position of the user. Using Kalman Filter, we correct the PDR's drift using WiFi that provides a prediction of the user's absolute position each time a WiFi scan is received. Finally, we adjust Kalman Filter results with a map-free projection method that takes into account the physical constraints of the environment (corridors, doors, etc.) and projects the prediction on the possible walkable paths. We test our pipeline on IPIN'19 Indoor Localization challenge dataset and demonstrate that it improves the winner's results by 20\% using the challenge evaluation protocol.

الوصول الحر: http://arxiv.org/abs/2011.10799Test

المؤلفون: Perez-Navarro, Antoni, Montoliu, Raul, Sansano-Sansano, Emilio, Martinez-Garcia, Marina, Femenia, Ruben, Torres-Sospedra, Joaquín

مصطلحات موضوعية: Error propagation, Fingerprinting methods, Indoor positioning, Ciências Naturais::Ciências da Computação e da Informação

الوصف: Indoor Positioning Systems usually consider the average positioning error over a set of evaluation samples, or a quartile of that value, as the global error. However, they do not provide a metric for the uncertainty for each individual position estimation. In this paper, we apply the error propagation theory to the kNN algorithm in Wi-Fi fingerprint-based indoor positioning. Our proposed method does not only retrieve the position estimate but also describes how the uncertainties of the RSSI measurements propagate through the calculations. We have validated our proposed method with two open-access datasets. ; This work was supported in part by projects Grant PID2021-1226420B-C44 funded AEI/10.13039/501100011033/FEDER,UE, Grant PID2021-1226420B-C42 funded AEI/10.13039/501100011033/FEDER,UE, Grant TED2021-199866B–I00 funded AEI/10.13039/501100011033/ European Union NextGenerationEU/PRTR , UJI-A2022-12, CYTED Network “GeoLibero” and H2020-MSCA-IF 101023072.

وصف الملف: application/pdf

العلاقة: info:eu-repo/grantAgreement/EC/H2020/101023072/EU; https://ieeexplore.ieee.org/document/10161717Test; A. Pérez-Navarro, R. Montoliu, E. Sansano-Sansano, M. Martínez-Garcia, R. Femenía and J. Torres-Sospedra, "Accuracy of a Single Position Estimate for kNN-Based Fingerprinting Indoor Positioning Applying Error Propagation Theory," in IEEE Sensors Journal, vol. 23, no. 16, pp. 18765-18775, 15 Aug.15, 2023, doi:10.1109/JSEN.2023.3287856.; https://hdl.handle.net/1822/86277Test

الإتاحة: https://doi.org/10.1109/JSEN.2023.3287856Test
https://hdl.handle.net/1822/86277Test

المؤلفون: Cardo Miota, Javier, Beltran, Hector, Pérez, Emilio, Sansano-Sansano, Emilio

مصطلحات موضوعية: ancillary services, electricity price forecasting, statistical analysis, machine learning

الوصف: As a consequence of the continuous growth being experienced by renewable energy systems, the role of the different ancillary services is becoming essential for the reliable operation of the electric system. This paper develops a methodology for estimating the secondary reserve marginal band price in the Iberian electricity market using four forecasting techniques: two classical models (ARIMAX and SARIMAX) and two machine learning models (Random Forest and Support Vector Regression). The methodology involves a Pearson correlation analysis and a Sequential Forward Selection algorithm to select the relevant model inputs and exogenous variables. A statistical data analysis is conducted to examine the temporal characteristics of the target variable and a data-preprocessing is performed for the proper implementation of the models. A grid search and a sequential division cross-validation are applied to determine the optimal parameters of the models. The performance is evaluated using three statistical metrics. The results show that the Random Forest model outperforms the other models, achieving the lowest MAE (2.40 e/MW) and RMSE (3.40 e/MW) values.

العلاقة: ECON 2023-49th Annual Conference of the IEEE Industrial Electronics Society. IEEE, 2023. p. 1-6.; https://ieeexplore.ieee.org/abstract/document/10311889Test; CARDO-MIOTA, J., et al. Secondary Reserve Marginal Band Price Prediction with Classical and Machine Learning Based Techniques. In: IECON 2023-49th Annual Conference of the IEEE Industrial Electronics Society. IEEE, 2023. p. 1-6.; http://hdl.handle.net/10234/207248Test

الإتاحة: http://hdl.handle.net/10234/207248Test

المؤلفون: Aranda Polo, Fernando Jesús, Álvarez, Fernando J., Parralejo Rodríguez, Felipe, Sansano-Sansano, Emilio, Montoliu Colás, Raul

مصطلحات موضوعية: bluetooth low energy, gait speed, health monitoring

الوصف: Ponencia presentada en: 22nd IEEE International Conference on Industrial Technology (ICIT), del 10 al 12 de marzo de 2021 ; Gait speed (GS) is a crucial parameter in the evolution and diagnosis of degenerative illnesses. Nowadays, it is measured in clinical environments where it is impossible to keep track of all patients due to the lack of resources. The development of GS measurement systems for in-home environments could solve this problem, but current methods present, at least, one of these problems: they require expensive hardware, are intrusive for the patient, or are imprecise. A novel method to measure GS in these scenarios using Bluetooth Low Energy and smart wearable devices is proposed in this work. The proposed system is inexpensive, non-intrusive, and its precision is comparable to the current state of the art methods. This system could be commercialized as part of an in-home health monitoring system.

وصف الملف: application/pdf

العلاقة: IEEE, 2021. p. 671-676; ARANDA, Fernando J., et al. A novel method for in-home gait speed estimation in health monitoring using bluetooth low energy. In: 2021 22nd IEEE International Conference on Industrial Technology (ICIT). IEEE, 2021. p. 671-676.; http://hdl.handle.net/10234/198764Test; https://doi.org/10.1109/ICIT46573.2021.9453578Test

الإتاحة: https://doi.org/10.1109/ICIT46573.2021.9453578Test
http://hdl.handle.net/10234/198764Test

المؤلفون: Martínez Garcia, marina, Sansano-Sansano, Emilio, Castillo Hornero, Andrea, Femenia, Ruben, Roomp, Kristof, Oliver, Nuria

مصطلحات موضوعية: Population screening, Public health

الوصف: Since March of 2020, billions of people worldwide have been asked to limit their social contacts in an effort to contain the spread of the SARS-CoV-2 virus. However, little research has been carried out to date on the impact of such social distancing measures on the social isolation levels of the population. In this paper, we study the impact of the pandemic on the social isolation of the Spanish population, by means of 32,359 answers to a citizen survey collected over a period of 7 months. We uncover (1) a significant increase in the prevalence of social isolation in the population, reaching almost 26%; (2) gender and age differences, with the largest prevalence of isolation among middle-aged individuals; (3) a strong relationship between economic impact and social isolation; and (4) differences in social isolation, depending on the number of COVID-19 protection measures and on the perception of coronavirus infection risk by our participants. Our research sheds quantitative light on the sociological impact of the pandemic, and enables us to identify key factors in the interplay between the deployment of non-pharmaceutical interventions to contain the spread of an infectious disease and a population’s levels of social isolation.

وصف الملف: application/pdf

العلاقة: Scientific Reports, vol. 12, núm. 1 (2022); https://www.nature.com/articles/s41598-022-16628-y#citeasTest; MARTÍNEZ-GARCIA, Marina, et al. Social isolation during the COVID-19 pandemic in Spain: a population study. Scientific Reports, 2022, vol. 12, núm. 1, p. 1-15.; http://hdl.handle.net/10234/199774Test; https://doi.org/10.1038/s41598-022-16628-yTest

الإتاحة: https://doi.org/10.1038/s41598-022-16628-yTest
http://hdl.handle.net/10234/199774Test

المؤلفون: Potortì, Francesco, Park, Sangjoon, Crivello, Antonino, Palumbo, Filippo, GIROLAMI, MICHELE, Barsocchi, Paolo, Lee, Soyeon, Torres-Sospedra, Joaquín, Jimenez Ruiz, Antonio Ramon, Perez-Navarro, Antoni, Mendoza-Silva, Germán Martín, Seco, Fernando, ortiz, miguel, PERUL, Johan, Renaudin, Valerie, Kang, Hyunwoong, Park, Soyoung, Lee, Jae Hong, Park, Chan Gook, Ha, Jisu, Han, JaeSeung, Park, Changjun, Kim, Keunhye, Lee, Yonghyun, Gye, Seunghun, lee, keumryeol, Kim, Eunjee, Choi, Jeongsik, choi, Yang-Seok, Talwar, Shilpa, Cho, Seong Yun, Ben-Moshe, Boaz, Scherbakov, Alex, Antsfeld, Leonid, Sansano-Sansano, Emilio, Chidlovskii, Boris, Kronenwett, Nikolai, Prophet, Silvia, Landay, Yael, Marbel, Revital, Zheng, Lingxiang, Peng, Ao, Lin, Zhichao, Wu, Bang, Ma, Chengqi, Poslad, Stefan, Selviah, David, Wu, Wei, Ma, Zixiang, Zhang, Wenchao, Wei, Dongyan, Yuan, Hong, Jiang, Jun-Bang, Huang, Shao-Yung, Liu, Jing-Wen, Su, Kuan-Wu, Leu, Jenq-Shiou, Nishiguchi, Kazuki, BOUSSELHAM, Walid, Uchiyama, Hideaki, Thomas, Diego, Shimada, Atsushi, Taniguchi, Rin-ichiro, Cortés Puschel, Vicente, Lungenstrass, Tomás, Ashraf, Imran, Lee, Chanseok, Ali, Muhammad Usman, Im, Yeongjun, Kim, Gunzung, Eom, Jeongsook, Hur, Soojung, Park, Yongwan, Opiela, Miroslav, Moreira, Adriano, Nicolau, Maria João, Pendão, Cristiano, Silva, Ivo, Meneses, Filipe, Costa, António, Trogh, Jens, Plets, David, Chien, Ying-Ren, Chang, Tzu-Yu, Fang, Shih-Hau, Tsao, Yu

مصطلحات موضوعية: indoor localisation, indoor navigation, competition, benchmarking, smartphone-based positioning, foot-mounted pedestrian dead reckoning, Wi-Fi fingerprinting, magnetic field, camera-based positioning, inertial-based positioning, sensor fusion, Kalman filter, particle filter, stakeholders, atmospheric measurements, particle measurements, real-time systems, wireless fidelity, sensor systems

الوصف: IPIN 2019 Competition, sixth in a series of IPIN competitions, was held at the CNR Research Area of Pisa (IT), integrated into the program of the IPIN 2019 Conference. It included two on-site real-time Tracks and three off-site Tracks. The four Tracks presented in this paper were set in the same environment, made of two buildings close together for a total usable area of 1000 m 2 outdoors and and 6000 m 2 indoors over three floors, with a total path length exceeding 500 m. IPIN competitions, based on the EvAAL framework, have aimed at comparing the accuracy performance of personal positioning systems in fair and realistic conditions: past editions of the competition were carried in big conference settings, university campuses and a shopping mall. Positioning accuracy is computed while the person carrying the system under test walks at normal walking speed, uses lifts and goes up and down stairs or briefly stops at given points. Results presented here are a showcase of state-of-the-art systems tested side by side in real-world settings as part of the on-site real-time competition Tracks. Results for off-site Tracks allow a detailed and reproducible comparison of the most recent positioning and tracking algorithms in the same environment as the on-site Tracks.

وصف الملف: application/pdf

العلاقة: Development of human enhancement fire helmet and fire suppression support system; Basic Science Research Program; ICT Research and Development Program of MSIP/IITP (Development of Precise Positioning Technology for the Enhancement of Pedestrian Position/Spatial Cognition and Sports Competition Analysis); MICROCEBUS; REPNIN PLUS; TECHNOFUSION(III)CM; Development of wireless communication tracking-based location information system in disaster scene for fire-fighters and person who requested rescue; Strategic Priority Research Program; IEEE Access, Vol. 8 (2020); F. Potortì et al., "The IPIN 2019 Indoor Localisation Competition—Description and Results," in IEEE Access, vol. 8, pp. 206674-206718, 2020, doi:10.1109/ACCESS.2020.3037221.; http://hdl.handle.net/10234/200929Test

الإتاحة: https://doi.org/10.1109/ACCESS.2020.3037221Test
http://hdl.handle.net/10234/200929Test

المؤلفون: Sansano-Sansano, Emilio, Montoliu Colás, Raul, Belmonte-Fernández, Óscar, Aranda Polo, Fernando Jesús, Alvarez, Fernando J.

مصطلحات موضوعية: ambient assisted living, bluetooth low energy, gait speed

الوصف: In the near future, as a consequence of the increasing percentage of elder people with respect to the total population, developed countries will face significant stress on their healthcare systems. The onset of some diseases associated with aging, such as dementia or cognitive decline, has been associated with a number of factors that can be detected in advance, thus offering the possibility of an early intervention to delay their onset. Specifically, several studies have shown a correlation between slower gait speed and serious cognitive diseases such as Alzheimer’s disease. In this work we present a method, based on Bluetooth Low Energy (BLE), capable of detecting the user’s walking speed in a continuous and non-invasive way, providing a useful tool for the monitoring and early detection of this type of diseases. The proposed method estimates the gait speed with an average error of less than 10 cm/s, and is capable of providing continuous non-invasive monitoring of the gait speed of users while they conduct their usual life routines, without any additional requirements other than wearing a smartwatch or an activity band with inertial sensors and BLE capabilities.

وصف الملف: application/pdf

العلاقة: IEEE Sensors Journal. Volume: 22, Issue: 8, 15 April 2022; https://github.com/esansano/gait-speed-monitoringTest; https://ieeexplore.ieee.org/document/9729223Test; E. Sansano-Sansano, R. Montoliu, Ó. Belmonte-Fernández, F. J. Aranda and F. J. Álvarez, "Continuous Non-Invasive Assessment of Gait Speed Through Bluetooth Low Energy," in IEEE Sensors Journal, vol. 22, no. 8, pp. 8183-8195, 15 April15, 2022, doi:10.1109/JSEN.2022.3157137.; http://hdl.handle.net/10234/200539Test; https://doi.org/10.1109/JSEN.2022.3157137Test

الإتاحة: https://doi.org/10.1109/JSEN.2022.3157137Test
http://hdl.handle.net/10234/200539Test

المؤلفون: Montoliu Colás, Raul, Sansano-Sansano, Emilio, Gascó, Arturo, Belmonte-Fernández, Óscar, Caballer Miedes, Antonio

مصطلحات موضوعية: WiFi fingerprinting, people monitoring, real case

الوصف: Ponència presentada a 10th International Conference on Indoor Positioning and Indoor Navigation IPIN 2019 celebrada a Pisa, Itàlia, del 30 de setembre al 3 d'octubre de 2019 ; This paper presents our experience on a real case of applying a Wi-Fi fingerprinting-based indoor localization system for monitoring elder people in their own homes. The presented system is part of a broad project called Senior Monitoring where the main aim is to monitor elders to study behavioural patterns as a tool for early detection of some cognitive decay diseases. Since the system is used by real users, there are many situations that cannot be controlled by system developers and can be a source of errors. This paper presents some of the problems arisen when real non-expert users use localization systems, and discuss some strategies to deal with such situations.

وصف الملف: application/pdf

العلاقة: CEUR Workshop Proceedings, vol. 2498; UJI-B2017-45; RTI2018- 095168-B-C53; http://ceur-ws.org/Vol-2498Test/; MONTOLIU, R. et al. Senior monitoring: a real case of applying a WiFi fingerprinting-based indoor positioning method for people monitoring. En IPIN (Short Papers/Work-in-Progress Papers), 2019. p. 95-102.; http://hdl.handle.net/10234/190025Test

الإتاحة: http://hdl.handle.net/10234/190025Test