Proceedings of the 4th Workshop on Interacting with Smart Objects 2015

These are the Proceedings of the 4th IUI Workshop on Interacting with Smart Objects. Objects that we use in our everyday life are expanding their restricted interaction capabilities and provide functionalities that go far beyond their original functionality. They feature computing capabilities and are thus able to capture information, process and store it and interact with their environments, turning them into smart objects

Context Aware Middleware Architectures: Survey and Challenges

Abstract: Context aware applications, which can adapt their behaviors to changing environments, are attracting more and more attention. To simplify the complexity of developing applications, context aware middleware, which introduces context awareness into the traditional middleware, is highlighted to provide a homogeneous interface involving generic context management solutions. This paper provides a survey of state-of-the-art context aware middleware architectures proposed during the period from 2009 through 2015. First, a preliminary background, such as the principles of context, context awareness, context modelling, and context reasoning, is provided for a comprehensive understanding of context aware middleware. On this basis, an overview of eleven carefully selected middleware architectures is presented and their main features explained. Then, thorough comparisons and analysis of the presented middleware architectures are performed based on technical parameters including architectural style, context abstraction, context reasoning, scalability, fault tolerance, interoperability, service discovery, storage, security & privacy, context awareness level, and cloud-based big data analytics. The analysis shows that there is actually no context aware middleware architecture that complies with all requirements. Finally, challenges are pointed out as open issues for future work

Internet of Things Architectures, Technologies, Applications, Challenges, and Future Directions for Enhanced Living Environments and Healthcare Systems: A Review

Internet of Things (IoT) is an evolution of the Internet and has been gaining increased attention from researchers in both academic and industrial environments. Successive technological enhancements make the development of intelligent systems with a high capacity for communication and data collection possible, providing several opportunities for numerous IoT applications, particularly healthcare systems. Despite all the advantages, there are still several open issues that represent the main challenges for IoT, e.g., accessibility, portability, interoperability, information security, and privacy. IoT provides important characteristics to healthcare systems, such as availability, mobility, and scalability, that o er an architectural basis for numerous high technological healthcare applications, such as real-time patient monitoring, environmental and indoor quality monitoring, and ubiquitous and pervasive information access that benefits health professionals and patients. The constant scientific innovations make it possible to develop IoT devices through countless services for sensing, data fusing, and logging capabilities that lead to several advancements for enhanced living environments (ELEs). This paper reviews the current state of the art on IoT architectures for ELEs and healthcare systems, with a focus on the technologies, applications, challenges, opportunities, open-source platforms, and operating systems. Furthermore, this document synthesizes the existing body of knowledge and identifies common threads and gaps that open up new significant and challenging future research directions.info:eu-repo/semantics/publishedVersio

Internet of Things Architectures for Enhanced Living Environments

Ambient Assisted Living (AAL) is an emerging multidisciplinary research area that aims to create an ecosystem of different types of sensors, computers, mobile devices, wireless networks, and software applications for enhanced living environments and occupational health. There are several challenges in the development and implementation of an effective AAL system, such as system architecture, human-computer interaction, ergonomics, usability, and accessibility. There are also social and ethical challenges, such as acceptance by seniors and the privacy and confidentiality that must be a requirement of AAL devices. It is also essential to ensure that technology does not replace human care and is used as a relevant complement. The Internet of Things (IoT) is a paradigm where objects are connected to the Internet and support sensing capabilities. IoT devices should be ubiquitous, recognize the context, and support intelligence capabilities closely related to AAL. Technological advances allow defining new advanced tools and platforms for real-time health monitoring and decision making in the treatment of various diseases. IoT is a suitable approach to building healthcare systems, and it provides a suitable platform for ubiquitous health services, using, for example, portable sensors to carry data to servers and smartphones for communication. Despite the potential of the IoT paradigm and technologies for healthcare systems, several challenges to be overcome still exist. The direction and impact of IoT in the economy are not clearly defined, and there are barriers to the immediate and ubiquitous adoption of IoT products, services, and solutions. Several sources of pollutants have a high impact on indoor living environments. Consequently, indoor air quality is recognized as a fundamental variable to be controlled for enhanced health and well-being. It is critical to note that typically most people occupy more than 90% of their time inside buildings, and poor indoor air quality negatively affects performance and productivity. Research initiatives are required to address air quality issues to adopt legislation and real-time inspection mechanisms to improve public health, not only to monitor public places, schools, and hospitals but also to increase the rigor of building rules. Therefore, it is necessary to use real-time monitoring systems for correct analysis of indoor air quality to ensure a healthy environment in at least public spaces. In most cases, simple interventions provided by homeowners can produce substantial positive impacts on indoor air quality, such as avoiding indoor smoking and the correct use of natural ventilation. An indoor air quality monitoring system helps the detection and improvement of air quality conditions. Local and distributed assessment of chemical concentrations is significant for safety (e.g., detection of gas leaks and monitoring of pollutants) as well as to control heating, ventilation, and HVAC systems to improve energy efficiency. Real-time indoor air quality monitoring provides reliable data for the correct control of building automation systems and should be assumed as a decision support platform on planning interventions for enhanced living environments. However, the monitoring systems currently available are expensive and only allow the collection of random samples that are not provided with time information. Most solutions on the market only allow data consulting limited to device memory and require procedures for downloading and manipulating data with specific software. In this way, the development of innovative environmental monitoring systems based on ubiquitous technologies that allow real-time analysis becomes essential. This thesis resulted in the design and development of IoT architectures using modular and scalable structures for air quality monitoring based on data collected from cost-effective sensors for enhanced living environments. The proposed architectures address several concepts, including acquisition, processing, storage, analysis, and visualization of data. These systems incorporate an alert management Framework that notifies the user in real-time in poor indoor air quality scenarios. The software Framework supports multiple alert methods, such as push notifications, SMS, and e-mail. The real-time notification system offers several advantages when the goal is to achieve effective changes for enhanced living environments. On the one hand, notification messages promote behavioral changes. These alerts allow the building manager to identify air quality problems and plan interventions to avoid unhealthy air quality scenarios. The proposed architectures incorporate mobile computing technologies such as mobile applications that provide ubiquitous air quality data consulting methods s. Also, the data is stored and can be shared with medical teams to support the diagnosis. The state-of-the-art analysis has resulted in a review article on technologies, applications, challenges, opportunities, open-source IoT platforms, and operating systems. This review was significant to define the IoT-based Framework for indoor air quality supervision. The research leads to the development and design of cost-effective solutions based on open-source technologies that support Wi-Fi communication and incorporate several advantages such as modularity, scalability, and easy installation. The results obtained are auspicious, representing a significant contribution to enhanced living environments and occupational health. Particulate matter (PM) is a complex mixture of solid and liquid particles of organic and inorganic substances suspended in the air. Moreover, it is considered the pollutant that affects more people. The most damaging particles to health are ≤PM10 (diameter 10 microns or less), which can penetrate and lodge deep within the lungs, contributing to the risk of developing cardiovascular and respiratory diseases as well as lung cancer. Taking into account the adverse health effects of PM exposure, an IoT architecture for automatic PM monitoring was proposed. The proposed architecture is a PM real-time monitoring system and a decision-making tool. The solution consists of a hardware prototype for data acquisition and a Web Framework developed in .NET for data consulting. This system is based on open-source and technologies, with several advantages compared to existing systems, such as modularity, scalability, low-cost and easy installation. The data is stored in a database developed in SQL SERVER using .NET Web services. The results show the ability of the system to analyze the indoor air quality in real-time and the potential of the Web Framework for the planning of interventions to ensure safe, healthy, and comfortable conditions. Associations of high concentrations of carbon dioxide (CO2) with low productivity at work and increased health problems are well documented. There is also a clear correlation between high levels of CO2 and high concentrations of pollutants in indoor air. There are sufficient reasons to monitor CO2 and provide real-time notifications to improve occupational health and provide a safe and healthy indoor living environment. Taking into account the significant influence of CO2 for enhanced living environments, a real-time IoT architecture for CO2 monitoring was proposed. CO2 was selected because it is easy to measure and is produced in quantity (by people and combustion equipment). It can be used as an indicator of other pollutants and, therefore, of air quality in general. The solution consists of a hardware prototype for data acquisition environment, a Web software, and a smartphone application for data consulting. The proposed architecture is based on open-source technologies, and the data is stored in a SQL SERVER database. The mobile Framework allows the user not only to consult the latest data collected but also to receive real-time notifications in poor indoor air quality scenarios, and to configure the alerts threshold levels. The results show that the mobile application not only provides easy access to real-time air quality data, but also allows the user to maintain parameter history and provide a history of changes. Consequently, this system allows the user to analyze in a precise and detailed manner the behavior of air quality. Finally, an air quality monitoring solution was implemented, consisting of a hardware prototype that incorporates only the MICS-6814 sensor as the detection unit. This system monitors various air quality parameters such as NH3 (ammonia), CO (carbon monoxide), NO2 (nitrogen dioxide), C3H8 (propane), C4H10 (butane), CH4 (methane), H2 (hydrogen) and C2H5OH (ethanol). The monitoring of the concentrations of these pollutants is essential to provide enhanced living environments. This solution is based on Cloud, and the collected data is sent to the ThingSpeak platform. The proposed Framework combines sensitivity, flexibility, and measurement accuracy in real-time, allowing a significant evolution of current air quality controls. The results show that this system provides easy, intuitive, and fast access to air quality data as well as relevant notifications in poor air quality situations to provide real-time intervention and improve occupational health. These data can be accessed by physicians to support diagnoses and correlate the symptoms and health problems of patients with the environment in which they live. As future work, the results reported in this thesis can be considered as a starting point for the development of a secure system sharing data with health professionals in order to serve as decision support in diagnosis.Ambient Assisted Living (AAL) é uma área de investigação multidisciplinar emergente que visa a construção de um ecossistema de diferentes tipos de sensores, microcontroladores, dispositivos móveis, redes sem fios e aplicações de software para melhorar os ambientes de vida e a saúde ocupacional. Existem muitos desafios no desenvolvimento e na implementação de um sistema AAL, como a arquitetura do sistema, interação humano-computador, ergonomia, usabilidade e acessibilidade. Existem também problemas sociais e éticos, como a aceitação por parte dos utilizadores mais vulneráveis e a privacidade e confidencialidade, que devem ser uma exigência de todos os dispositivos AAL. De facto, também é essencial assegurar que a tecnologia não substitua o cuidado humano e seja usada como um complemento essencial. A Internet das Coisas (IoT) é um paradigma em que os objetos estão conectados à Internet e suportam recursos sensoriais. Tendencialmente, os dispositivos IoT devem ser omnipresentes, reconhecer o contexto e ativar os recursos de inteligência ambiente intimamente relacionados ao AAL. Os avanços tecnológicos permitem definir novas ferramentas avançadas e plataformas para monitorização de saúde em tempo real e tomada de decisão no tratamento de várias doenças. A IoT é uma abordagem adequada para construir sistemas de saúde sendo que oferece uma plataforma para serviços de saúde ubíquos, usando, por exemplo, sensores portáteis para recolha e transmissão de dados e smartphones para comunicação. Apesar do potencial do paradigma e tecnologias IoT para o desenvolvimento de sistemas de saúde, muitos desafios continuam ainda por ser resolvidos. A direção e o impacto das soluções IoT na economia não está claramente definido existindo, portanto, barreiras à adoção imediata de produtos, serviços e soluções de IoT. Os ambientes de vida são caracterizados por diversas fontes de poluentes. Consequentemente, a qualidade do ar interior é reconhecida como uma variável fundamental a ser controlada de forma a melhorar a saúde e o bem-estar. É importante referir que tipicamente a maioria das pessoas ocupam mais de 90% do seu tempo no interior de edifícios e que a má qualidade do ar interior afeta negativamente o desempenho e produtividade. É necessário que as equipas de investigação continuem a abordar os problemas de qualidade do ar visando a adoção de legislação e mecanismos de inspeção que atuem em tempo real para a melhoraria da saúde e qualidade de vida, tanto em locais públicos como escolas e hospitais e residências particulares de forma a aumentar o rigor das regras de construção de edifícios. Para tal, é necessário utilizar mecanismos de monitorização em tempo real de forma a possibilitar a análise correta da qualidade do ambiente interior para garantir ambientes de vida saudáveis. Na maioria dos casos, intervenções simples que podem ser executadas pelos proprietários ou ocupantes da residência podem produzir impactos positivos substanciais na qualidade do ar interior, como evitar fumar em ambientes fechados e o uso correto de ventilação natural. Um sistema de monitorização e avaliação da qualidade do ar interior ajuda na deteção e na melhoria das condições ambiente. A avaliação local e distribuída das concentrações químicas é significativa para a segurança (por exemplo, deteção de fugas de gás e supervisão dos poluentes) bem como para controlar o aquecimento, ventilação, e sistemas de ar condicionado (HVAC) visando a melhoria da eficiência energética. A monitorização em tempo real da qualidade do ar interior fornece dados fiáveis para o correto controlo de sistemas de automação de edifícios e deve ser assumida com uma plataforma de apoio à decisão no que se refere ao planeamento de intervenções para ambientes de vida melhorados. No entanto, os sistemas de monitorização atualmente disponíveis são de alto custo e apenas permitem a recolha de amostras aleatórias que não são providas de informação temporal. A maioria das soluções disponíveis no mercado permite apenas a acesso ao histórico de dados que é limitado à memória do dispositivo e exige procedimentos de download e manipulação de dados com software proprietário. Desta forma, o desenvolvimento de sistemas inovadores de monitorização ambiente baseados em tecnologias ubíquas e computação móvel que permitam a análise em tempo real torna-se essencial. A Tese resultou na definição e no desenvolvimento de arquiteturas para monitorização da qualidade do ar baseadas em IoT. Os métodos propostos são de baixo custo e recorrem a estruturas modulares e escaláveis para proporcionar ambientes de vida melhorados. As arquiteturas propostas abordam vários conceitos, incluindo aquisição, processamento, armazenamento, análise e visualização de dados. Os métodos propostos incorporam Frameworks de gestão de alertas que notificam o utilizador em tempo real e de forma ubíqua quando a qualidade do ar interior é deficiente. A estrutura de software suporta vários métodos de notificação, como notificações remotas para smartphone, SMS (Short Message Service) e email. O método usado para o envio de notificações em tempo real oferece várias vantagens quando o objetivo é alcançar mudanças efetivas para ambientes de vida melhorados. Por um lado, as mensagens de notificação promovem mudanças de comportamento. De facto, estes alertas permitem que o gestor do edifício e os ocupantes reconheçam padrões da qualidade do ar e permitem também um correto planeamento de intervenções de forma evitar situações em que a qualidade do ar é deficiente. Por outro lado, o sistema proposto incorpora tecnologias de computação móvel, como aplicações móveis, que fornecem acesso omnipresente aos dados de qualidade do ar e, consequentemente, fornecem soluções completas para análise de dados. Além disso, os dados são armazenados e podem ser partilhados com equipas médicas para ajudar no diagnóstico. A análise do estado da arte resultou na elaboração de um artigo de revisão sobre as tecnologias, aplicações, desafios, plataformas e sistemas operativos que envolvem a criação de arquiteturas IoT. Esta revisão foi um trabalho fundamental na definição das arquiteturas propostas baseado em IoT para a supervisão da qualidade do ar interior. Esta pesquisa conduz a um desenvolvimento de arquiteturas IoT de baixo custo com base em tecnologias de código aberto que operam como um sistema Wi-Fi e suportam várias vantagens, como modularidade, escalabilidade e facilidade de instalação. Os resultados obtidos são muito promissores, representando uma contribuição significativa para ambientes de vida melhorados e saúde ocupacional. O material particulado (PM) é uma mistura complexa de partículas sólidas e líquidas de substâncias orgânicas e inorgânicas suspensas no ar e é considerado o poluente que afeta mais pessoas. As partículas mais prejudiciais à saúde são as ≤PM10 (diâmetro de 10 micrómetros ou menos), que podem penetrar e fixarem-se dentro dos pulmões, contribuindo para o risco de desenvolver doenças cardiovasculares e respiratórias, bem como de cancro do pulmão. Tendo em consideração os efeitos negativos para a saúde da exposição ao PM foi desenvolvido numa primeira fase uma arquitetura IoT para monitorização automática dos níveis de PM. Esta arquitetura é um sistema que permite monitorização de PM em tempo real e uma ferramenta de apoio à tomada de decisão. A solução é composta por um protótipo de hardware para aquisição de dados e um portal Web desenvolvido em .NET para consulta de dados. Este sistema é baseado em tecnologias de código aberto com várias vantagens em comparação aos sistemas existentes, como modularidade, escalabilidade, baixo custo e fácil instalação. Os dados são armazenados numa base de dados desenvolvida em SQL SERVER e são enviados com recurso a serviços Web. Os resultados mostram a capacidade do sistema de analisar em tempo real a qualidade do ar interior e o potencial da Framework Web para o planeamento de intervenções com o objetivo de garantir condições seguras, saudáveis e confortáveis. Associações de altas concentrações de dióxido de carbono (CO2) com défice de produtividade no trabalho e aumento de problemas de saúde encontram-se bem documentadas. Existe também uma correlação evidente entre altos níveis de CO2 e altas concentrações de poluentes no ar interior. Tendo em conta a influência significativa do CO2 para a construção de ambientes de vida melhorados desenvolveu-se uma solução de monitorização em tempo real de CO2 com base na arquitetura de IoT. A arquitetura proposta permite também o envio de notificações em tempo real para melhorar a saúde ocupacional e proporcionar um ambiente de vida interior seguro e saudável. O CO2 foi selecionado, pois é fácil de medir e é produzido em quantidade (por pessoas e equipamentos de combustão). Assim, pode ser usado como um indicador de outros poluentes e, portanto, da qualidade do ar em geral. O método proposto é composto por um protótipo de hardware para aquisição de dados, um software Web e uma aplicação smartphone para consulta de dados. Esta arquitetura é baseada em tecnologias de código aberto e os dados recolhidos são armazenados numa base de dados SQL SERVER. A Framework móvel permite não só consultar em tempo real os últimos dados recolhidos, receber notificações com o objetivo de avisar o utilizador quando a qualidade do ar está deficiente, mas também para configurar alertas. Os resultados mostram que a Framework móvel fornece não apenas acesso fácil aos dados da qualidade do ar em tempo real, mas também permite ao utilizador manter o histórico de parâmetros. Assim este sistema permite ao utilizador analisar de maneira precisa e detalhada o comportamento da qualidade do ar interior. Por último, é proposta uma arquitetura para monitorização de vários parâmetros da qualidade do ar, como NH3 (amoníaco), CO (monóxido de carbono), NO2 (dióxido de azoto), C3H8 (propano), C4H10 (butano), CH4 (metano), H2 (hidrogénio) e C2H5OH (etanol). Esta arquitetura é composta por um protótipo de hardware que incorpora unicamente o sensor MICS-6814 como unidade de deteção. O controlo das concentrações destes poluentes é extremamente relevante para proporcionar ambientes de vida melhorados. Esta solução tem base na Cloud sendo que os dados recolhidos são enviados para a plataforma ThingSpeak. Esta Framework combina sensibilidade, flexibilidade e precisão de medição em tempo real, permitindo uma evolução significativa dos atuais sistemas de monitorização da qualidade do ar. Os resultados mostram que este sistema fornece acesso fácil, intuitivo e rápido aos dados de qualidade do ar bem como notificações essenciais em situações de qualidade do ar deficiente de forma a planear intervenções em tempo útil e melhorar a saúde ocupacional. Esses dados podem ser acedidos pelos médicos para apoiar diagnósticos e correlacionar os sintomas e problemas de saúde dos pacientes com o ambiente em que estes vivem. Como trabalho futuro, os resultados reportados nesta Tese podem ser considerados um ponto de partida para o desenvolvimento de um sistema seguro para partilha de dados com profissionais de saúde de forma a servir de suporte à decisão no diagnóstico

A Proof-of-Concept IoT System for Remote Healthcare Based on Interoperability Standards

[EN] The Internet of Things paradigm in healthcare has boosted the design of new solutions for the promotion of healthy lifestyles and the remote care. Thanks to the effort of academia and industry, there is a wide variety of platforms, systems and commercial products enabling the real-time information exchange of environmental data and people's health status. However, one of the problems of these type of prototypes and solutions is the lack of interoperability and the compromised scalability in large scenarios, which limits its potential to be deployed in real cases of application. In this paper, we propose a health monitoring system based on the integration of rapid prototyping hardware and interoperable software to build system capable of transmitting biomedical data to healthcare professionals. The proposed system involves Internet of Things technologies and interoperablility standards for health information exchange such as the Fast Healthcare Interoperability Resources and a reference framework architecture for Ambient Assisted Living UniversAAL.This research received no external funding. The APC was funded by Research group Information and Communication Technologies against Climate Change (!CTCC) of the Universitat Politecnica de Valencia, Spain.Lemus Zúñiga, LG.; Félix, JM.; Fides Valero, Á.; Benlloch-Dualde, J.; Martinez-Millana, A. (2022). A Proof-of-Concept IoT System for Remote Healthcare Based on Interoperability Standards. Sensors. 22(4):1-17. https://doi.org/10.3390/s2204164611722

Web services approach for ambient assisted living in mobile environments

Web services appeared as a promising technology for Web environments independent of technologies, services, and applications. First, a performance comparison study between the two most used Web service architectures, SOAP and REST, is presented, considering messages exchange between clients and a server. Based on this study, the REST architecture was chosen to deploy the system because it gets better results compared to SOAP architecture. Currently, there are some issues related with this approach that should be studied. For instance, if massive quantities of data are sent to databases it can influence significantly the performance of the whole system. The Advanced Message Queuing Protocol (AMPQ) appears as a promising solution to address this problem. Then, in order to evaluate the performance of this approach, this work presents a performance evaluation and a comparison study of RESTful Web services and the AMQP Protocol considering exchanging messages between clients and a server. The study is based on the averaged exchanged messages for a certain period of time. It was observed and concluded that, for large quantities of messages exchange, the best results comes from the Advanced Message Queuing Protocol. Message Queuing Telemetry Transport (MQTT) was addressed in this work because it is a similar protocol to AMQP but it can be used by mobile devices with a processing capacity smallest unlike the AMQP that needs greater processing capacity. These studies are performed in the context of Ambient Assisted Living environments, since the work was applied to this topic in order to experiment the effectiveness and evaluate the performance of these protocols in this scenario

Enhanced Living Environments

This open access book was prepared as a Final Publication of the COST Action IC1303 “Algorithms, Architectures and Platforms for Enhanced Living Environments (AAPELE)”. The concept of Enhanced Living Environments (ELE) refers to the area of Ambient Assisted Living (AAL) that is more related with Information and Communication Technologies (ICT). Effective ELE solutions require appropriate ICT algorithms, architectures, platforms, and systems, having in view the advance of science and technology in this area and the development of new and innovative solutions that can provide improvements in the quality of life for people in their homes and can reduce the financial burden on the budgets of the healthcare providers. The aim of this book is to become a state-of-the-art reference, discussing progress made, as well as prompting future directions on theories, practices, standards, and strategies related to the ELE area. The book contains 12 chapters and can serve as a valuable reference for undergraduate students, post-graduate students, educators, faculty members, researchers, engineers, medical doctors, healthcare organizations, insurance companies, and research strategists working in this area

Personalized data analytics for internet-of-things-based health monitoring

The Internet-of-Things (IoT) has great potential to fundamentally alter the delivery of modern healthcare, enabling healthcare solutions outside the limits of conventional clinical settings. It can offer ubiquitous monitoring to at-risk population groups and allow diagnostic care, preventive care, and early intervention in everyday life. These services can have profound impacts on many aspects of health and well-being. However, this field is still at an infancy stage, and the use of IoT-based systems in real-world healthcare applications introduces new challenges. Healthcare applications necessitate satisfactory quality attributes such as reliability and accuracy due to their mission-critical nature, while at the same time, IoT-based systems mostly operate over constrained shared sensing, communication, and computing resources. There is a need to investigate this synergy between the IoT technologies and healthcare applications from a user-centered perspective. Such a study should examine the role and requirements of IoT-based systems in real-world health monitoring applications. Moreover, conventional computing architecture and data analytic approaches introduced for IoT systems are insufficient when used to target health and well-being purposes, as they are unable to overcome the limitations of IoT systems while fulfilling the needs of healthcare applications. This thesis aims to address these issues by proposing an intelligent use of data and computing resources in IoT-based systems, which can lead to a high-level performance and satisfy the stringent requirements. For this purpose, this thesis first delves into the state-of-the-art IoT-enabled healthcare systems proposed for in-home and in-hospital monitoring. The findings are analyzed and categorized into different domains from a user-centered perspective. The selection of home-based applications is focused on the monitoring of the elderly who require more remote care and support compared to other groups of people. In contrast, the hospital-based applications include the role of existing IoT in patient monitoring and hospital management systems. Then, the objectives and requirements of each domain are investigated and discussed. This thesis proposes personalized data analytic approaches to fulfill the requirements and meet the objectives of IoT-based healthcare systems. In this regard, a new computing architecture is introduced, using computing resources in different layers of IoT to provide a high level of availability and accuracy for healthcare services. This architecture allows the hierarchical partitioning of machine learning algorithms in these systems and enables an adaptive system behavior with respect to the user's condition. In addition, personalized data fusion and modeling techniques are presented, exploiting multivariate and longitudinal data in IoT systems to improve the quality attributes of healthcare applications. First, a real-time missing data resilient decision-making technique is proposed for health monitoring systems. The technique tailors various data resources in IoT systems to accurately estimate health decisions despite missing data in the monitoring. Second, a personalized model is presented, enabling variations and event detection in long-term monitoring systems. The model evaluates the sleep quality of users according to their own historical data. Finally, the performance of the computing architecture and the techniques are evaluated in this thesis using two case studies. The first case study consists of real-time arrhythmia detection in electrocardiography signals collected from patients suffering from cardiovascular diseases. The second case study is continuous maternal health monitoring during pregnancy and postpartum. It includes a real human subject trial carried out with twenty pregnant women for seven months

HABITAT: An IoT Solution for Independent Elderly

In this work, a flexible and extensive digital platform for Smart Homes is presented, exploiting the most advanced technologies of the Internet of Things, such as Radio Frequency Identification, wearable electronics, Wireless Sensor Networks, and Artificial Intelligence. Thus, the main novelty of the paper is the system-level description of the platform flexibility allowing the interoperability of different smart devices. This research was developed within the framework of the operative project HABITAT (Home Assistance Based on the Internet of Things for the Autonomy of Everybody), aiming at developing smart devices to support elderly people both in their own houses and in retirement homes, and embedding them in everyday life objects, thus reducing the expenses for healthcare due to the lower need for personal assistance, and providing a better life quality to the elderly users