2024
Novak, Robert; Delgado, Marcos; García-Sipols, Ana Elizabeth; Trilles-Oliver, Sergio; de Blas, Clara Simón; Gallego, Micael; Rodríguez-Sánchez, Maria Cristina
A Real-Time Framework for Enhancing Emergency Response Effectiveness in Firefighting Contexts Proceedings Article
In: Seminario Anual de Automática, Electrónica Industrial e Instrumentación, pp. 1-7, Granada, 2024.
Abstract | BibTeX | Tags: machine learning, Real time analysis, Smart Cities
@inproceedings{Novak2024a,
title = {A Real-Time Framework for Enhancing Emergency Response Effectiveness in Firefighting Contexts},
author = {Robert Novak and Marcos Delgado and Ana Elizabeth García-Sipols and Sergio Trilles-Oliver and Clara Simón de Blas and Micael Gallego and Maria Cristina Rodríguez-Sánchez},
year = {2024},
date = {2024-07-03},
urldate = {2024-07-03},
booktitle = {Seminario Anual de Automática, Electrónica Industrial e Instrumentación},
pages = {1-7},
address = {Granada},
abstract = {This study presents a real-time framework designed to enhance emergency response effectiveness, initially applied in firefighting contexts but potentially generalizable to other emergency scenarios. Integrating advanced sensors with a comprehensive mathematical framework significantly enhances immediate situational awareness and substantially improves operational decision-making. Deployed and tested at Fire Station 9 in Chamartín, the system utilizes strategically placed sensors with variable transmission rates to simulate diverse emergency scenarios. The core achievement of this research is the demonstration of the framework’s capacity to provide real-time predictions, enabling emergency responders to act swiftly and accurately in dynamic situations. The results highlight the significant potential of real-time data analytics in revolutionizing emergency response strategies, offering a path towards safer and more efficient firefighting operations.},
keywords = {machine learning, Real time analysis, Smart Cities},
pubstate = {published},
tppubtype = {inproceedings}
}
2017
Trilles-Oliver, Sergio; Belmonte-Fernández, Óscar; Schade, Sven; Huerta-Guijarro, Joaquín
A domain-independent methodology to analyze IoT data streams in real-time. A proof of concept implementation for anomaly detection from environmental data Journal Article
In: International Journal of Digital Earth, vol. 10, no. 1, pp. 103-120, 2017, ISSN: 1753-8947.
Abstract | BibTeX | Tags: environmental monitoring, Internet of things, Real time analysis, real-time sensor streams
@article{TrillesOliver16,
title = {A domain-independent methodology to analyze IoT data streams in real-time. A proof of concept implementation for anomaly detection from environmental data},
author = { Sergio Trilles-Oliver and Óscar Belmonte-Fernández and Sven Schade and Joaquín Huerta-Guijarro},
issn = {1753-8947},
year = {2017},
date = {2017-01-01},
journal = {International Journal of Digital Earth},
volume = {10},
number = {1},
pages = {103-120},
abstract = {Pushed by the Internet of Things (IoT) paradigm modern sensor networks monitor a wide range of phenomena, in areas such as environmental monitoring, health care, industrial processes, and smart cities. These networks provide a continuous pulse of the almost infinite activities that are happening in the physical space and are thus, key enablers for a Digital Earth Nervous System. Nevertheless, the rapid processing of these sensor data streams still continues to challenge traditional data handling solutions and new approaches are being requested. We propose a generic answer to this challenge, which has the potential to support any form of distributed real-time analysis. This neutral methodology follows a brokering approach to work with different kinds of data sources and uses web-based standards to achieve interoperability. As a proof of concept, we implemented the methodology to detect anomalies in real-time and applied it to the area of environmental monitoring. The developed system is capable of detecting anomalies, generating notifications, and displaying the recent situation to the user.},
keywords = {environmental monitoring, Internet of things, Real time analysis, real-time sensor streams},
pubstate = {published},
tppubtype = {article}
}
2016
Nittel, Silvia; Bodum, Lars; Clarke, Keith; Gould, Michael; Raposo, Paulo; Sharma, Jayant; Vasardi, Maria
Emerging Technological Trends likely to Affect GIScience in the Next 20 Years Book Chapter
In: Onsrund, H.; Kunh, Werner (Ed.): Advancing Geographic Information Science: the past and next twenty years, Chapter 3, pp. 45, GSDI association press, 2016, ISBN: 978-0985244446.
Abstract | BibTeX | Tags: geoprivacy, geovisual analytics, GIScience, Real time analysis, user interfaces
@inbook{Nittel2015,
title = {Emerging Technological Trends likely to Affect GIScience in the Next 20 Years},
author = {Silvia Nittel and Lars Bodum and Keith Clarke and Michael Gould and Paulo Raposo and Jayant Sharma and Maria Vasardi},
editor = {H. Onsrund and Werner Kunh},
isbn = {978-0985244446},
year = {2016},
date = {2016-01-01},
booktitle = {Advancing Geographic Information Science: the past and next twenty years},
pages = {45},
publisher = {GSDI association press},
chapter = {3},
abstract = {In this article, the members of the “Emerging Technological Trends likely to Affect GIScience in the Next 20 Years” panel, which was part of the International Early- Career Scholars Summer Institutes in Geographic Information Vespucci Institute in Bar Harbor, Maine in 2015, summarize their findings about major technological developments that potentially will required novel research in GIScience. Keywords:},
keywords = {geoprivacy, geovisual analytics, GIScience, Real time analysis, user interfaces},
pubstate = {published},
tppubtype = {inbook}
}
2015
Trilles-Oliver, Sergio
Aproximación al tratamiento completo del ciclo de vida sobre datos provenientes de sensores mediante estándares GIS PhD Thesis
Universitat Jaume I, 2015.
Abstract | BibTeX | Tags: Geographic Information Systems (GIS), Internet of things, Interoperability, Real time analysis, Sensors, Standards
@phdthesis{TrillesOliver2015,
title = {Aproximación al tratamiento completo del ciclo de vida sobre datos provenientes de sensores mediante estándares GIS},
author = {Sergio Trilles-Oliver},
year = {2015},
date = {2015-01-01},
school = {Universitat Jaume I},
abstract = {El aumento de la necesidad por conocer cu´ al es el estado de cualquier entorno, ya sea por motivos medioambientales, econ´omicos, como sociales, ha propiciado el crecimiento del uso de nodos de sensorizaci ´on capaces de cuantificar y cualificar cualquier tipo de fen´omeno observable. Esta necesidad, combinada con la disminuci ´on de los precios y tama˜no de los componentes, ha favorecido el despliegue de dichos nodos con la finalidad de interconectarse entre ellos formando una red que proporciona los datos de sensorizaci ´on. Mayoritariamente, las redes de sensores disponibles actualmente ofrecen sus observaciones mediante protocolos y formatos propietarios. Esta situaci ´on, muestra la carencia de un est´andar com´un para que facilite la gesti ´on de los datos generados por los sensores de una forma interoperable. Adem´as, dichos protocolos y formatos, tampoco favorecen el consumo de este tipo de contenido en entornos donde los recursos computacionales son m´as reducidos, como pueden ser tel ´ efonos m´ oviles. La tendencia actual es utilizar los protocolos de Internet para la comunicaci´on entre los nodos de sensorizaci ´on. Dichos protocolos, permiten el uso de los sensores como una parte de Internet, donde el enfoque es llamado el Internet de la Cosas. Esto propicia un escenario id ´oneo para el control de los sensores y favorece el acceso a ellos, aunque actualmente tampoco existe un est´andar capaz de ofrecer dicho enfoque de una forma universal. El uso de los protocolos de Internet ha favorecido el uso de sensores ofreciendo nuevos usos donde antes no era posible. Prueba de ello son las ciudades inteligentes, en las cuales la implantaci´on de sensores en sus alrededores, se ha hecho con la finalidad de conocer y controlar lo que est ´a sucediendo en ella. De esta forma, cada d´?a hay un mayor despliegue de redes de sensores midiendo gran cantidad de fen´omenos diferentes. Estas redes proporcionan grandes vol ´umenes de datos en m´ ultiples formatos, resoluciones y escalas con una alta tasa de generaci ´on que no es posible analizar con las tecnolog´?as actuales, por lo que es necesario ofrecer m´etodos de an´ alisis adaptados a estas caracter´?sticas. Adem´as, tambi´en se necesita ofrecer dichos an´ alisis mediante procesamientos que garanticen su reusabilidad e interoperabilidad. Esto puede lograrse mediante los procesamientos que siguen est´andares, ya que establecen una interfaz predefinida para su ejecuci ´on. Enmarcados en este escenario, se presenta la actual tesis. En ella, se utiliza como hilo conductor el ciclo de vida de cualquier contenido geoespacial, que coincide con el ciclo de los datos proporcionados por sensores. Para ello, se presentan cuatro etapas que son: adquisici ´on, publicaci ´on, acceso y an´ alisis. Para cada una de ellas se detallan los problemas existentes y se proponen diferentes soluciones. Para la etapa de adquisici ´on se presenta una plataforma de sensorizaci ´on, basada en software y hardware libre, energ´eticamente aut´onoma e integrada en el Internet de las Cosas. En la etapa de publicaci ´on se dise ˜na un procesamiento est´andar para la publicaci ´on automatizada de contenido geoespacial en los diferentes servicios est ´andares del ´ambito geoespacial. Adem´as, en la etapa de acceso proponen diferentes formas de acceder a datos de sensores dependiendo del caso de uso en particular. Las interfaces propuestas se basan en seguir los paradigmas del Internet de las Cosas a trav´es del uso de est´andares geoespaciales mejorando la interoperabilidad, adem´as de ofrecer un acceso ligero para dispositivos con restricciones limitadas o de ser capaces de servir grandes cantidades de observaciones. En la ´ultima etapa, el an´ alisis, se aportan dos metodolog´?as diferentes. La primera de ellas permite el an´ alisis en tiempo real sobre grandes cantidades de datos y, la segunda, ofrece aplicar cualquier tipo de modelo utilizando un procesamiento est ´andar. Finalmente se proponen diferentes casos de uso donde son aplicadas todas las aportaciones que se describen.},
keywords = {Geographic Information Systems (GIS), Internet of things, Interoperability, Real time analysis, Sensors, Standards},
pubstate = {published},
tppubtype = {phdthesis}
}
Trilles-Oliver, Sergio; Schade, Sven; Belmonte-Fernández, Óscar; Huerta-Guijarro, Joaquín
Real-Time Anomaly Detection from Environmental Data Streams Book Section
In: Baçao, Fernando; Santos, Maribel Yasmina; Painho, Marci (Ed.): AGILE 2015: Geographic information science as an enabler of smarter cities and communities, pp. 125–144, Springer International Publishing, Heidelberg, 2015, ISBN: 978-3-319-16786-2.
Abstract | Links | BibTeX | Tags: Big data, Real time analysis, Sensors
@incollection{TrillesOliver2015b,
title = {Real-Time Anomaly Detection from Environmental Data Streams},
author = {Sergio Trilles-Oliver and Sven Schade and Óscar Belmonte-Fernández and Joaquín Huerta-Guijarro},
editor = {Baçao, Fernando and Santos, Maribel Yasmina and Painho, Marci},
url = {http://link.springer.com/10.1007/978-3-319-16787-9_8},
doi = {10.1007/978-3-319-16787-9_8},
isbn = {978-3-319-16786-2},
year = {2015},
date = {2015-01-01},
booktitle = {AGILE 2015: Geographic information science as an enabler of smarter cities and communities},
pages = {125--144},
publisher = {Springer International Publishing},
address = {Heidelberg},
abstract = {Modern sensor networks monitor a wide range of phenomena. They are applied in environmental monitoring, health care, optimization of industrial processes, social media, smart city solutions, and many other domains. All in all, they provide a continuously pulse of the almost infinite activities that are happening in the physical space—and in cyber space. The handling of the massive amounts of generated measurements poses a series of (Big Data) challenges. Our work addresses one of these challenges: the detection of anomalies in real-time. In this paper, we propose a generic solution to this problem, and introduce a system that is capable of detecting anomalies, generating notifications, and displaying the recent situation to the user. We apply CUSUM a statistical control algorithm and adopt it so that it can be used inside the Storm framework—a robust and scalable real-time processing framework. We present a proof of concept implementation from the area of environmental monitoring.},
keywords = {Big data, Real time analysis, Sensors},
pubstate = {published},
tppubtype = {incollection}
}