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Using heterogeneous wireless sensor networks in a telemonitoring system for healthcare
Abstract—Ambient intelligence has acquired great importance in recent years and requires the development of new innovative solutions. This paper presents a distributed telemonitoring system, aimed at improving healthcare and assistance to dependent people at their homes. The system implements a service-oriented architecture based platform, which allows heterogeneous wireless sensor networks to communicate in a distributed way independent of time and location restrictions. This approach provides the system with a higher ability to recover from errors and a better flexibility to change their behavior at execution time. Preliminary results are presented in this paper. Index Terms—Ambient intelligence (AmI), healthcare, servicesoriented architectures (SOAs), wireless sensors networks (WSNs)
New platform for intelligent context-based distributed information fusion
Tesis por compendio de publicaciones[ES]Durante las Ăşltimas dĂ©cadas, las redes de sensores se han vuelto cada vez más importantes y hoy en dĂa están presentes en prácticamente todos los sectores de nuestra sociedad. Su gran capacidad para adquirir datos y actuar sobre el entorno, puede facilitar la construcciĂłn de sistemas sensibles al contexto, que permitan un análisis detallado y flexible de los procesos que ocurren y los servicios que se pueden proporcionar a los usuarios.
Esta tesis doctoral se presenta en el formato de “Compendio de ArtĂculos”, de tal forma que las principales caracterĂsticas de la arquitectura multi-agente distribuida propuesta para facilitar la interconexiĂłn de redes de sensores se presentan en tres artĂculos bien diferenciados. Se ha planteado una arquitectura modular y ligera para dispositivos limitados computacionalmente, diseñando un mecanismo de comunicaciĂłn flexible que permite la interacciĂłn entre diferentes agentes embebidos, desplegados en dispositivos de tamaño reducido. Se propone un nuevo modelo de agente embebido, como mecanismo de extensiĂłn para la plataforma PANGEA. Además, se diseña un nuevo modelo de organizaciĂłn virtual de agentes especializada en la fusiĂłn de informaciĂłn. De
esta forma, los agentes inteligentes tienen en cuenta las caracterĂsticas de las organizaciones existentes en el entorno a la hora de proporcionar servicios. El modelo de fusiĂłn de informaciĂłn presenta una arquitectura claramente diferenciada en 4 niveles, siendo capaz de obtener la informaciĂłn proporcionada por las redes de sensores (capas inferiores) para ser integrada con organizaciones virtuales de agentes (capas superiores). El filtrado de señales, minerĂa de datos, sistemas de razonamiento basados en casos y otras tĂ©cnicas de Inteligencia Artificial han sido aplicadas para la consecuciĂłn exitosa de esta investigaciĂłn.
Una de las principales innovaciones que pretendo con mi estudio, es investigar acerca de nuevos mecanismos que permitan la adiciĂłn dinámica de redes de sensores combinando diferentes tecnologĂas con el propĂłsito final de exponer un conjunto de servicios de usuario de forma distribuida. En este sentido, se propondrá una arquitectura multiagente basada en organizaciones virtuales que gestione de forma autĂłnoma la infraestructura subyacente constituida por el hardware y los diferentes sensores
Chapter A Fuzzy Logic Approach for Remote Healthcare Monitoring by Learning and Recognizing Human Activities of Daily Living
Systems analysis & desig
Distributed Computing and Monitoring Technologies for Older Patients
This book summarizes various approaches for the automatic detection of health threats to older patients at home living alone. The text begins by briefly describing those who would most benefit from healthcare supervision. The book then summarizes possible scenarios for monitoring an older patient at home, deriving the common functional requirements for monitoring technology. Next, the work identifies the state of the art of technological monitoring approaches that are practically applicable to geriatric patients. A survey is presented on a range of such interdisciplinary fields as smart homes, telemonitoring, ambient intelligence, ambient assisted living, gerontechnology, and aging-in-place technology. The book discusses relevant experimental studies, highlighting the application of sensor fusion, signal processing and machine learning techniques. Finally, the text discusses future challenges, offering a number of suggestions for further research directions
A Fuzzy Logic Approach for Remote Healthcare Monitoring by Learning and Recognizing Human Activities of Daily Living
Systems analysis & desig
Performance assessment of a closed-loop system for diabetes management
Telemedicine systems can play an important
role in the management of diabetes, a chronic condition that
is increasing worldwide. Evaluations on the consistency of
information across these systems and on their performance
in a real situation are still missing. This paper presents a
remote monitoring system for diabetes management based
on physiological sensors, mobile technologies and patient/
doctor applications over a service-oriented architecture that
has been evaluated in an international trial (83,905 operation
records). The proposed system integrates three types of
running environments and data engines in a single serviceoriented
architecture. This feature is used to assess key
performance indicators comparing them with other type
of architectures. Data sustainability across the applications
has been evaluated showing better outcomes for full integrated
sensors. At the same time, runtime performance of
clients has been assessed spotting no differences regarding
the operative environmentThe authors wish to acknowledge the consortium of the METABO project (funded by the European Commission, Grant nr. 216270) for their commitment during concept development and trial execution.MartĂnez Millana, A.; Fico, G.; Fernández Llatas, C.; Traver Salcedo, V. (2015). Performance assessment of a closed-loop system for diabetes management. Medical and Biological Engineering and Computing. 53(12):1295-1303. doi:10.1007/s11517-015-1245-3S129513035312Bellazzi R, Larizza C, Montani A et al (2002) A telemedicine support dor diabetes management: the T-IDDM project. Comput Methods Programs Biomed 69:147–161Boloor K, Chirkova R, Salo T, Viniotis Y (2011) Analysis of response time percentile service level agreements in soa-based applications. 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