New platform for intelligent context-based distributed information fusion

Tesis por compendio de publicaciones[ES]Durante las últimas décadas, las redes de sensores se han vuelto cada vez más importantes y hoy en día están presentes en prácticamente todos los sectores de nuestra sociedad. Su gran capacidad para adquirir datos y actuar sobre el entorno, puede facilitar la construcción 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 Artículos”, de tal forma que las principales características de la arquitectura multi-agente distribuida propuesta para facilitar la interconexión de redes de sensores se presentan en tres artículos bien diferenciados. Se ha planteado una arquitectura modular y ligera para dispositivos limitados computacionalmente, diseñando un mecanismo de comunicación flexible que permite la interacción entre diferentes agentes embebidos, desplegados en dispositivos de tamaño reducido. Se propone un nuevo modelo de agente embebido, como mecanismo de extensión para la plataforma PANGEA. Además, se diseña un nuevo modelo de organización virtual de agentes especializada en la fusión de información. De esta forma, los agentes inteligentes tienen en cuenta las características de las organizaciones existentes en el entorno a la hora de proporcionar servicios. El modelo de fusión de información presenta una arquitectura claramente diferenciada en 4 niveles, siendo capaz de obtener la información proporcionada por las redes de sensores (capas inferiores) para ser integrada con organizaciones virtuales de agentes (capas superiores). El filtrado de señales, minería de datos, sistemas de razonamiento basados en casos y otras técnicas de Inteligencia Artificial han sido aplicadas para la consecución exitosa de esta investigación. Una de las principales innovaciones que pretendo con mi estudio, es investigar acerca de nuevos mecanismos que permitan la adición dinámica de redes de sensores combinando diferentes tecnologías con el propósito 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 autónoma la infraestructura subyacente constituida por el hardware y los diferentes sensores

The Role of the Internet of Things in Health Care: A Systematic and Comprehensive Study

The Internet of Things (IoT) is becoming an emerging trend and has significant potential to replace other technologies, where researchers consider it as the future of the internet. It has given tremendous support and become the building blocks in the development of important cyber-physical systems and it is being severed in a variety of application domains, including healthcare. A methodological evolution of the Internet of Things, enabled it to extend to the physical world beyond the electronic world by connecting miscellaneous devices through the internet, thus making everything is connected. In recent years it has gained higher attention for its potential to alleviate the strain on the healthcare sector caused by the rising and aging population along with the increase in chronic diseases and global pandemics. This paper surveys about various usages of IoT healthcare technologies and reviews the state of the art services and applications, recent trends in IoT based healthcare solutions, and various challenges posed including security and privacy issues, which researchers, service providers and end users need to pay higher attention. Further, this paper discusses how innovative IoT enabled technologies like cloud computing, fog computing, blockchain, and big data can be used to leverage modern healthcare facilities and mitigate the burden on healthcare resources

From Wearable Sensors to Smart Implants – Towards Pervasive and Personalised Healthcare

<p>Objective: This article discusses the evolution of pervasive healthcare from its inception for activity recognition using wearable sensors to the future of sensing implant deployment and data processing. Methods: We provide an overview of some of the past milestones and recent developments, categorised into different generations of pervasive sensing applications for health monitoring. This is followed by a review on recent technological advances that have allowed unobtrusive continuous sensing combined with diverse technologies to reshape the clinical workflow for both acute and chronic disease management. We discuss the opportunities of pervasive health monitoring through data linkages with other health informatics systems including the mining of health records, clinical trial databases, multi-omics data integration and social media. Conclusion: Technical advances have supported the evolution of the pervasive health paradigm towards preventative, predictive, personalised and participatory medicine. Significance: The sensing technologies discussed in this paper and their future evolution will play a key role in realising the goal of sustainable healthcare systems.</p> <p> </p

Exploring the Landscape of Ubiquitous In-home Health Monitoring: A Comprehensive Survey

Ubiquitous in-home health monitoring systems have become popular in recent years due to the rise of digital health technologies and the growing demand for remote health monitoring. These systems enable individuals to increase their independence by allowing them to monitor their health from the home and by allowing more control over their well-being. In this study, we perform a comprehensive survey on this topic by reviewing a large number of literature in the area. We investigate these systems from various aspects, namely sensing technologies, communication technologies, intelligent and computing systems, and application areas. Specifically, we provide an overview of in-home health monitoring systems and identify their main components. We then present each component and discuss its role within in-home health monitoring systems. In addition, we provide an overview of the practical use of ubiquitous technologies in the home for health monitoring. Finally, we identify the main challenges and limitations based on the existing literature and provide eight recommendations for potential future research directions toward the development of in-home health monitoring systems. We conclude that despite extensive research on various components needed for the development of effective in-home health monitoring systems, the development of effective in-home health monitoring systems still requires further investigation.Comment: 35 pages, 5 figure

Resource Management in a Peer to Peer Cloud Network for IoT

Software-Defined Internet of Things (SDIoT) is defined as merging heterogeneous objects in a form of interaction among physical and virtual entities. Large scale of data centers, heterogeneity issues and their interconnections have made the resource management a hard problem specially when there are different actors in cloud system with different needs. Resource management is a vital requirement to achieve robust networks specially with facing continuously increasing amount of heterogeneous resources and devices to the network. The goal of this paper is reviews to address IoT resource management issues in cloud computing services. We discuss the bottlenecks of cloud networks for IoT services such as mobility. We review Fog computing in IoT services to solve some of these issues. It provides a comprehensive literature review of around one hundred studies on resource management in Peer to Peer Cloud Networks and IoT. It is very important to find a robust design to efficiently manage and provision requests and available resources. We also reviewed different search methodologies to help clients find proper resources to answer their needs

Cloud-assisted body area networks: state-of-the-art and future challenges

Body area networks (BANs) are emerging as enabling technology for many human-centered application domains such as health-care, sport, fitness, wellness, ergonomics, emergency, safety, security, and sociality. A BAN, which basically consists of wireless wearable sensor nodes usually coordinated by a static or mobile device, is mainly exploited to monitor single assisted livings. Data generated by a BAN can be processed in real-time by the BAN coordinator and/or transmitted to a server-side for online/offline processing and long-term storing. A network of BANs worn by a community of people produces large amount of contextual data that require a scalable and efficient approach for elaboration and storage. Cloud computing can provide a flexible storage and processing infrastructure to perform both online and offline analysis of body sensor data streams. In this paper, we motivate the introduction of Cloud-assisted BANs along with the main challenges that need to be addressed for their development and management. The current state-of-the-art is overviewed and framed according to the main requirements for effective Cloud-assisted BAN architectures. Finally, relevant open research issues in terms of efficiency, scalability, security, interoperability, prototyping, dynamic deployment and management, are discussed

Advanced Internet of Things for Personalised Healthcare System: A Survey

As a new revolution of the Internet, Internet of Things (IoT) is rapidly gaining ground as a new research topic in many academic and industrial disciplines, especially in healthcare. Remarkably, due to the rapid proliferation of wearable devices and smartphone, the Internet of Things enabled technology is evolving healthcare from conventional hub based system to more personalised healthcare system (PHS). However, empowering the utility of advanced IoT technology in PHS is still significantly challenging in the area considering many issues, like shortage of cost-effective and accurate smart medical sensors, unstandardized IoT system architectures, heterogeneity of connected wearable devices, multi-dimensionality of data generated and high demand for interoperability. In an effect to understand advance of IoT technologies in PHS, this paper will give a systematic review on advanced IoT enabled PHS. It will review the current research of IoT enabled PHS, and key enabling technologies, major IoT enabled applications and successful case studies in healthcare, and finally point out future research trends and challenges

Smart Computing and Sensing Technologies for Animal Welfare: A Systematic Review

Animals play a profoundly important and intricate role in our lives today. Dogs have been human companions for thousands of years, but they now work closely with us to assist the disabled, and in combat and search and rescue situations. Farm animals are a critical part of the global food supply chain, and there is increasing consumer interest in organically fed and humanely raised livestock, and how it impacts our health and environmental footprint. Wild animals are threatened with extinction by human induced factors, and shrinking and compromised habitat. This review sets the goal to systematically survey the existing literature in smart computing and sensing technologies for domestic, farm and wild animal welfare. We use the notion of \emph{animal welfare} in broad terms, to review the technologies for assessing whether animals are healthy, free of pain and suffering, and also positively stimulated in their environment. Also the notion of \emph{smart computing and sensing} is used in broad terms, to refer to computing and sensing systems that are not isolated but interconnected with communication networks, and capable of remote data collection, processing, exchange and analysis. We review smart technologies for domestic animals, indoor and outdoor animal farming, as well as animals in the wild and zoos. The findings of this review are expected to motivate future research and contribute to data, information and communication management as well as policy for animal welfare

Design for energy-efficient and reliable fog-assisted healthcare IoT systems

Cardiovascular disease and diabetes are two of the most dangerous diseases as they are the leading causes of death in all ages. Unfortunately, they cannot be completely cured with the current knowledge and existing technologies. However, they can be effectively managed by applying methods of continuous health monitoring. Nonetheless, it is difficult to achieve a high quality of healthcare with the current health monitoring systems which often have several limitations such as non-mobility support, energy inefficiency, and an insufficiency of advanced services. Therefore, this thesis presents a Fog computing approach focusing on four main tracks, and proposes it as a solution to the existing limitations. In the first track, the main goal is to introduce Fog computing and Fog services into remote health monitoring systems in order to enhance the quality of healthcare. In the second track, a Fog approach providing mobility support in a real-time health monitoring IoT system is proposed. The handover mechanism run by Fog-assisted smart gateways helps to maintain the connection between sensor nodes and the gateways with a minimized latency. Results show that the handover latency of the proposed Fog approach is 10%-50% less than other state-of-the-art mobility support approaches. In the third track, the designs of four energy-efficient health monitoring IoT systems are discussed and developed. Each energy-efficient system and its sensor nodes are designed to serve a specific purpose such as glucose monitoring, ECG monitoring, or fall detection; with the exception of the fourth system which is an advanced and combined system for simultaneously monitoring many diseases such as diabetes and cardiovascular disease. Results show that these sensor nodes can continuously work, depending on the application, up to 70-155 hours when using a 1000 mAh lithium battery. The fourth track mentioned above, provides a Fog-assisted remote health monitoring IoT system for diabetic patients with cardiovascular disease. Via several proposed algorithms such as QT interval extraction, activity status categorization, and fall detection algorithms, the system can process data and detect abnormalities in real-time. Results show that the proposed system using Fog services is a promising approach for improving the treatment of diabetic patients with cardiovascular disease