9 research outputs found

    Event-driven Middleware for Body and Ambient Sensor Applications

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    Continuing development of on-body and ambient sensors has led to a vast increase in sensor-based assistance and monitoring solutions. A growing range of modular sensors, and the necessity of running multiple applications on the sensor information, has led to an equally extensive increase in efforts for system development. In this work, we present an event-driven middleware for on-body and ambient sensor networks allowing multiple applications to define information types of their interest in a publish/subscribe manner. Incoming sensor data is hereby transformed into the required data representation which lifts the burden of adapting the application with respect to the connected sensors off the developer's shoulders. Furthermore, an unsupervised on-the-fly reloading of transformation rules from a remote server allows the system's adaptation to future applications and sensors at run-time as well as reducing the number of connected sensors. Open communication channels distribute sensor information to all interested applications. In addition to that, application-specific event channels are introduced that provide tailor-made information retrieval as well as control over the dissemination of critical information. The system is evaluated based on an Android implementation with transformation rules implemented as OSGi bundles that are retrieved from a remote web server. Evaluation shows a low impact of running the middleware and the transformation rules on a phone and highlights the reduced energy consumption by having fewer sensors serving multiple applications. It also points out the behavior and limits of the open and application-specific event channels with respect to CPU utilization, delivery ratio, and memory usage. In addition to the middleware approach, four (preventive) health care applications are presented. They take advantage of the mediation between sensors and applications and highlight the system's capabilities. By connecting body sensors for monitoring physical and physiological parameters as well as ambient sensors for retrieving information about user presence and interactions with the environment, full-fledged health monitoring examples for monitoring a user throughout the day are presented. Vital parameters are gathered from commercially available biosensors and the mediator device running both the middleware and the application is an off-the-shelf smart phone. For gaining information about a user's physical activity, custom-built body and ambient sensors are presented and deployed

    Towards the internet of smart clothing: a review on IoT wearables and garments for creating intelligent connected e-textiles

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    [Abstract] Technology has become ubiquitous, it is all around us and is becoming part of us. Togetherwith the rise of the Internet of Things (IoT) paradigm and enabling technologies (e.g., Augmented Reality (AR), Cyber-Physical Systems, Artificial Intelligence (AI), blockchain or edge computing), smart wearables and IoT-based garments can potentially have a lot of influence by harmonizing functionality and the delight created by fashion. Thus, smart clothes look for a balance among fashion, engineering, interaction, user experience, cybersecurity, design and science to reinvent technologies that can anticipate needs and desires. Nowadays, the rapid convergence of textile and electronics is enabling the seamless and massive integration of sensors into textiles and the development of conductive yarn. The potential of smart fabrics, which can communicate with smartphones to process biometric information such as heart rate, temperature, breathing, stress, movement, acceleration, or even hormone levels, promises a new era for retail. This article reviews the main requirements for developing smart IoT-enabled garments and shows smart clothing potential impact on business models in the medium-term. Specifically, a global IoT architecture is proposed, the main types and components of smart IoT wearables and garments are presented, their main requirements are analyzed and some of the most recent smart clothing applications are studied. In this way, this article reviews the past and present of smart garments in order to provide guidelines for the future developers of a network where garments will be connected like other IoT objects: the Internet of Smart Clothing.Xunta de Galicia; ED431C 2016-045Xunta de Galicia; ED341D R2016/012Xunta de Galicia; ED431G/01Agencia Estatal de Investigación de España; TEC2013-47141-C4-1-RAgencia Estatal de Investigación de España; TEC2016-75067-C4-1-RAgencia Estatal de Investigación de España; TEC2015-69648-RED

    Telemedicine

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    Telemedicine is a rapidly evolving field as new technologies are implemented for example for the development of wireless sensors, quality data transmission. Using the Internet applications such as counseling, clinical consultation support and home care monitoring and management are more and more realized, which improves access to high level medical care in underserved areas. The 23 chapters of this book present manifold examples of telemedicine treating both theoretical and practical foundations and application scenarios

    Smart Clothing Framework for Health Monitoring Applications

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    Wearable technologies are making a significant impact on people’s way of living thanks to the advancements in mobile communication, internet of things (IoT), big data and artificial intelligence. Conventional wearable technologies present many challenges for the continuous monitoring of human health conditions due to their lack of flexibility and bulkiness in size. Recent development in e-textiles and the smart integration of miniature electronic devices into textiles have led to the emergence of smart clothing systems for remote health monitoring. A novel comprehensive framework of smart clothing systems for health monitoring is proposed in this paper. This framework provides design specifications, suitable sensors and textile materials for smart clothing (e.g., leggings) development. In addition, the proposed framework identifies techniques for empowering the seamless integration of sensors into textiles and suggests a development strategy for health diagnosis and prognosis through data collection, data processing and decision making. The conceptual technical specification of smart clothing is also formulated and presented. The detailed development of this framework is presented in this paper with selected examples. The key challenges in popularizing smart clothing and opportunities of future development in diverse application areas such as healthcare, sports and athletics and fashion are discussed

    Distributed Online Machine Learning for Mobile Care Systems

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    Appendix D: Wavecomm Tech Docs removed for copyright reasonsTelecare and especially Mobile Care Systems are getting more and more popular. They have two major benefits: first, they drastically improve the living standards and even health outcomes for patients. In addition, they allow significant cost savings for adult care by reducing the needs for medical staff. A common drawback of current Mobile Care Systems is that they are rather stationary in most cases and firmly installed in patients’ houses or flats, which makes them stay very near to or even in their homes. There is also an upcoming second category of Mobile Care Systems which are portable without restricting the moving space of the patients, but with the major drawback that they have either very limited computational abilities and only a rather low classification quality or, which is most frequently, they only have a very short runtime on battery and therefore indirectly restrict the freedom of moving of the patients once again. These drawbacks are inherently caused by the restricted computational resources and mainly the limitations of battery based power supply of mobile computer systems. This research investigates the application of novel Artificial Intelligence (AI) and Machine Learning (ML) techniques to improve the operation of 2 Mobile Care Systems. As a result, based on the Evolving Connectionist Systems (ECoS) paradigm, an innovative approach for a highly efficient and self-optimising distributed online machine learning algorithm called MECoS - Moving ECoS - is presented. It balances the conflicting needs of providing a highly responsive complex and distributed online learning classification algorithm by requiring only limited resources in the form of computational power and energy. This approach overcomes the drawbacks of current mobile systems and combines them with the advantages of powerful stationary approaches. The research concludes that the practical application of the presented MECoS algorithm offers substantial improvements to the problems as highlighted within this thesis

    Cenários comunicacionais baseados em IOT para a promoção do bem-estar físico, psicológico e social dos séniores

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    The main objective of this research is to design and validate IoT based social hybrid scenario model that has the potential to promote psychological and physical wellbeing among older adults. The main reason to design and validate the model is age growth, older adults face psychological, physical and social well-being problems that increase mild cognitive impairment and frailty among older adults. Thus, to overcome older adults' problems, the study proposes and validates an IoT-based social hybrid scenario model. The model's features contain passive communication in which Drs, caregivers, and family members can monitor older adults' physical data from long distances. The model's features also contained intentional communication in which Older adults can interact online by text, audio, video calls, sharing images, and online activities such as painting, exercises and cooking. Moreover, older adults can do outdoor activities by inviting peers, friends or family members; the activities can be location-based IoT games, city tours, groups gardening and dinners. The outcomes of model validation will indicate how IoT characteristics can promote physical, psychological and social well-being and provide an opportunity for older adults to spend their life independently. The research that embodies this thesis includes 411 senior Portuguese Universities which are located mainland and on the island of Portugal. Using descriptive research methodology, where quantitative results are analysed, the results indicated a holistic scenario of passive and intentional communication in the context of well-being promotion among olderadults. from here, the social hybrid scenario is outlined, a hybrid model that offers passive and intentional communication between olderadults, family and medical doctors in the context of well-being promotion. The design and characteristics of the model are based on the existing knowledg, and needs of older adults, family members and also medical doctors. Such as model is a compound of passive and intentional characteristics that helps to reduce problem-related mental and physical health. The Passive and intentional communication characteristics are capable to create an environment for older adultsto take care of their psychological and physical health without any intervention and also increase their social physical and online activities, these activities help to promote the well-being of olderadults andd improve the daily lifestyle.O principal objetivo desta pesquisa é projetar e validar um modelo de cenário híbrido social baseado em IoT que tenha o potencial de promover o bem-estar psicológico e físico entre os idosos. A principal razão para projetar e validar o modelo é o crescimento da idade, os idosos enfrentam problemas psicológicos, físicos e de bem-estar social que aumentam o comprometimento cognitivo leve e a fragilidade entre os idosos. Assim, para superar os problemas dos idosos, o estudo propõe e valida um modelo de cenário híbrido social baseado em IoT. Os recursos do modelo contêm comunicação passiva na qual médicos, cuidadores e familiares podem monitorar os dados físicos dos idosos a longas distâncias. As características do modelo também contemplam comunicação intencional em que os idosos podem interagir online por meio de texto, áudio, videochamadas, compartilhamento de imagens e atividades online como pintura, exercícios e culinária. Além disso, os idosos podem fazer atividades ao ar livre convidando colegas, amigos ou familiares; as atividades podem ser jogos de IoT baseados em localização, passeios pela cidade, jardinagem em grupo e jantares. Os resultados da validação do modelo indicam como as características da IoT podem promover o bem-estar físico, psicológico e social e fornecer uma oportunidade para os idosos passarem sua vida de forma independente. A investigação que dá corpo a esta tese inclui 411 universidades portuguesas seniores localizadas no continente e na ilha de Portugal. Utilizando metodologia de pesquisa descritiva, onde são analisados resultados quantitativos, os resultados indicaram um cenário holístico de comunicação passiva e intencional no contexto da promoção do bem-estar entre idosos. a partir daqui, delineia-se o cenário social híbrido, um modelo híbrido que oferece comunicação passiva e intencional entre idosos, médicos de família e médicos no contexto da promoção do bem-estar. O desenho e as características do modelo baseiam-se no conhecimento existente e nas necessidades dos idosos, familiares e também médicos. Tal modelo é um composto de características passivas e intencionais que ajuda a reduzir os problemas relacionados com a saúde mental e física. As características de comunicação passiva e intencional são capazes de criar um ambiente para que os idosos cuidem de sua saúde psicológica e física e também aumentem suas atividades sociais físicas e online, essas atividades ajudam a promover o bem-estar dos idosos e melhorar o estilo de vida diário.Programa Doutoral em Informação e Comunicação em Plataformas Digitai

    Preface

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    Technical Verification of Integrating Wearable Sensors into BSN-Based Telemedical Monitoring System

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    Ultra-Low-Power Uwb Impulse Radio Design: Architecture, Circuits, And Applications

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    Recent advances in home healthcare, environmental sensing, and low power computing have created a need for wireless communication at very low power for low data rate applications. Due to higher energy/bit requirements at lower data -rate, achieving power levels low enough to enable long battery lifetime (~10 years) or power-harvesting supplies have not been possible with traditional approaches. Dutycycled radios have often been proposed in literature as a solution for such applications due to their ability to shut off the static power consumption at low data rates. While earlier radio nodes for such systems have been proposed based on a type of sleepwake scheduling, such implementations are still power hungry due to large synchronization uncertainty (~1[MICRO SIGN]s). In this dissertation, we utilize impulsive signaling and a pulse-coupled oscillator (PCO) based synchronization scheme to facilitate a globally synchronized wireless network. We have modeled this network over a widely varying parameter space and found that it is capable of reducing system cost as well as providing scalability in wireless sensor networks. Based on this scheme, we implemented an FCC compliant, 3-5GHz, timemultiplexed, dual-band UWB impulse radio transceiver, measured to consume only 20[MICRO SIGN]W when the nodes are synchronized for peer-peer communication. At the system level the design was measured to consume 86[MICRO SIGN]W of power, while facilitating multi- hop communication. Simple pulse-shaping circuitry ensures spectral efficiency, FCC compliance and ~30dB band-isolation. Similarly, the band-switchable, ~2ns turn-on receiver implements a non-coherent pulse detection scheme that facilitates low power consumption with -87dBm sensitivity at 100Kbps. Once synchronized the nodes exchange information while duty-cycling, and can use any type of high level network protocols utilized in packet based communication. For robust network performance, a localized synchronization detection scheme based on relative timing and statistics of the PCO firing and the timing pulses ("sync") is reported. No active hand-shaking is required for nodes to detect synchronization. A self-reinforcement scheme also helps maintain synchronization even in the presence of miss-detections. Finally we discuss unique ways to exploit properties of pulse coupled oscillator networks to realize novel low power event communication, prioritization, localization and immediate neighborhood validation for low power wireless sensor applications
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