Linking recorded data with emotive and adaptive computing in an eHealth environment

Telecare, and particularly lifestyle monitoring, currently relies on the ability to detect and respond to changes in individual behaviour using data derived from sensors around the home. This means that a significant aspect of behaviour, that of an individuals emotional state, is not accounted for in reaching a conclusion as to the form of response required. The linked concepts of emotive and adaptive computing offer an opportunity to include information about emotional state and the paper considers how current developments in this area have the potential to be integrated within telecare and other areas of eHealth. In doing so, it looks at the development of and current state of the art of both emotive and adaptive computing, including its conceptual background, and places them into an overall eHealth context for application and development

Architecture for orchestration of M2M services

The past few years, miniaturization has allowed usto imbue computers into everyday devices. This in turn hasenabled these devices to communicate with each other, and in doing so, allows us to collect a wealth of information, moreaccurately and with greater availability than ever before. Thisphenomenon is known as the Internet of Things. It allows smart environments to truly behave in an intelligent manner by using information collected from the devices mentioned above. However, it’s necessary to model how the gathered data will influence the behavior of a smart environment. This open problem can be approached as a machine to machine (M2M) orchestration.In this paper we present a new architecture for M2Morchestration. This new architecture will be based around aplatform that creates orchestration processes through a graphical interface. Through this interface a business process execution language (BPEL) service will be made and deployed on an enterprise service bus (ESB). Alongside this, we are also developing a collection of services that will be used for the purposes of implementing a smart environment

An Ecological Approach to Smart Homes for Health Care Services: Conceptual Framework of a Smart Servicescape Wheel

Background: Smart homes are considered effective solutions for home health care for the elderly, as smart home technologies can reduce care costs and improve elderly residents' independence. To develop a greater understanding of smart homes for health care services (SHHSs), this study accentuated the necessity of ecological approaches with an emphasis on environmental constraints. This study was based on 2 rationales: (1) users are inclined to perceive the service quality and service experience from environments (ie, servicescape) owing to the intangibility of health care and the pervasiveness of smart home technologies, and (2) both service domains are complex adaptive systems in which diversified and undefined service experiences-not only a few intended service flows-can be generated by complex combinations of servicescape elements. Objective: This study proposed the conceptual framework of a Smart Servicescape Wheel (SSW) as an ecological approach delineating the extensive spectrum of environmental constraints in SHHSs. Methods: The SSW framework was established based on a literature review. Results: Generally divided by perceptible and imperceptible servicescapes, the SSW consists of the perceptible Physical scape (ie, hardware components, environmental cues, and human states) and Social scape (ie, service relationships and social relationships) as well as the imperceptible Datascape (ie, computing intelligence, databases, and communication networks). Following the ecological approach, each category of the SSW is subdivided and defined at the level of components or functions. Conclusions: The SSW's strengths lie in the various application opportunities for SHHSs. In terms of service planning and development, the SSW can be utilized to (1) establish the requirements for SHHS development, (2) associate with work domain analysis by defining component layers, and (3) understand the real contexts of SHHSs for the enhanced prediction of diverse service experiences. Regarding service management, it can be applied to develop measurement items for the operation and evaluation of SHHSs.This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea under grant NRF-2017S1A5A8019275. This fund has no specific role or influence in the research process

A Rule-based Service Customization Strategy for Smart Home Context-aware Automation

The continuous technical progress of the smartphone built-in modules and embedded sensing techniques has created chances for context-aware automation and decision support in home environments. Studies in this area mainly focus on feasibility demonstrations of the emerging techniques and system architecture design that are applicable to the different use cases. It lacks service customization strategies tailoring the computing service to proactively satisfy users’ expectations. This investigation aims to chart the challenges to take advantage of the dynamic varying context information, and provide solutions to customize the computing service to the contextual situations. This work presents a rule-based service customization strategy which employs a semantic distance-based rule matching method for context-aware service decision making and a Rough Set Theory-based rule generation method to supervise the service customization. The simulation study reveals the trend of the algorithms in time complexity with the number of rules and context items. A prototype smart home system is implemented based on smartphones and commercially available low-cost sensors and embedded electronics. Results demonstrate the feasibility of the proposed strategy in handling the heterogeneous context for decision making and dealing with history context to discover the underlying rules. It shows great potential in employing the proposed strategy for context-aware automation and decision support in smart home applications

Central monitoring system for ambient assisted living

Smart homes for aged care enable the elderly to stay in their own homes longer. By means of various types of ambient and wearable sensors information is gathered on people living in smart homes for aged care. This information is then processed to determine the activities of daily living (ADL) and provide vital information to carers. Many examples of smart homes for aged care can be found in literature, however, little or no evidence can be found with respect to interoperability of various sensors and devices along with associated functions. One key element with respect to interoperability is the central monitoring system in a smart home. This thesis analyses and presents key functions and requirements of a central monitoring system. The outcomes of this thesis may benefit developers of smart homes for aged care

Internet of things (IoT) based adaptive energy management system for smart homes

PhD ThesisInternet of things enhances the flexibility of measurements under different environments, the development of advanced wireless sensors and communication networks on the smart grid infrastructure would be essential for energy efficiency systems. It makes deployment of a smart home concept easy and realistic. The smart home concept allows residents to control, monitor and manage their energy consumption with minimal wastage. The scheduling of energy usage enables forecasting techniques to be essential for smart homes. This thesis presents a self-learning home management system based on machine learning techniques and energy management system for smart homes. Home energy management system, demand side management system, supply side management system, and power notification system are the major components of the proposed self-learning home management system. The proposed system has various functions including price forecasting, price clustering, power forecasting alert, power consumption alert, and smart energy theft system to enhance the capabilities of the self-learning home management system. These functions were developed and implemented through the use of computational and machine learning technologies. In order to validate the proposed system, real-time power consumption data were collected from a Singapore smart home and a realistic experimental case study was carried out. The case study had proven that the developed system performing well and increased energy awareness to the residents. This proposed system also showcases its customizable ability according to different types of environments as compared to traditional smart home models. Forecasting systems for the electricity market generation have become one of the foremost research topics in the power industry. It is essential to have a forecasting system that can accurately predict electricity generation for planning and operation in the electricity market. This thesis also proposed a novel system called multi prediction system and it is developed based on long short term memory and gated recurrent unit models. This proposed system is able to predict the electricity market generation with high accuracy. Multi Prediction System is based on four stages which include a data collecting and pre-processing module, a multi-input feature model, multi forecast model and mean absolute percentage error. The data collecting and pre-processing module preprocess the real-time data using a window method. Multi-input feature model uses single input feeding method, double input feeding method and multiple feeding method for features input to the multi forecast model. Multi forecast model integrates long short term memory and gated recurrent unit variations such as regression model, regression with time steps model, memory between batches model and stacked model to predict the future generation of electricity. The mean absolute percentage error calculation was utilized to evaluate the accuracy of the prediction. The proposed system achieved high accuracy results to demonstrate its performance

Smart kitchen for Ambient Assisted Living

El envejecimiento de la población es una realidad en todos los países desarrollados. Las predicciones de crecimiento de esta población son alarmantes, planteando un reto para los servicios sociales y sanitarios. Las personas ancianas padecen diversas discapacidades que se van acentuando con la edad, siendo más propensas a sufrir accidentes domésticos, presentando problemas para realizar tareas cotidianas, etc. Esta situación conlleva a una pérdida paulatina de capacidades que en muchas ocasiones acaba con la vida autónoma de la persona. En este contexto, las Tecnologías de la Información y Comunicación (TIC) aplicadas al entorno doméstico pueden jugar un papel importante, permitiendo que las personas ancianas vivan más tiempo, de forma independiente en su propio hogar, presentando, por tanto, una alternativa a la hospitalización o institucionalización de las mismas. Este trabajo da un paso más en este sentido, presentando el diseño y desarrollo de un Ambiente Inteligente en la cocina, que ayuda a las personas ancianas y/o con discapacidad a desempeñar sus actividades de la vida diaria de una forma más fácil y sencilla. Esta tesis realiza sus principales aportaciones en dos campos: El metodológico y el tecnológico. Por un lado se presenta una metodología sistemática para extraer necesidades de colectivos específicos a fin de mejorar la información disponible por el equipo de diseño del producto, servicio o sistema. Esta metodología se basa en el estudio de la interacción Hombre-Máquina en base a los paradigmas y modelos existentes y el modelado y descripción de las capacidades del usuario en la misma utilizado el lenguaje estandarizado propuesto en la Clasificación Internacional del Funcionamiento, de la Discapacidad y de la Salud (CIF). Adicionalmente, se plantea el problema de la evaluación tecnológica, diseñando la metodología de evaluación de la tecnología con la finalidad de conocer su accesibilidad, funcionalidad y usabilidad del sistema desarrollado y aplicándola a 61 usuarios y 31 profesionales de la gerontología. Desde un punto de vista técnico, se afronta el diseño de un ambiente asistido inteligente (Ambient Assisted Living, AAL) en la cocina, planteando y definiendo la arquitectura del sistema. Esta arquitectura, basada en OSGi (Open Services Gateway initiative), oferta un sistema modular, con altas capacidades de interoperabilidad y escalabilidad. Además, se diseña e implementa una red de sensores distribuida en el entorno con el fin de obtener la mayor información posible del contexto, presentando distintos algoritmos para obtener información de alto nivel: detección de caídas o localización. Todos los dispositivos presentes en el entorno han sido modelados utilizando la taxonomía propuesta en OSGi4AmI, extendiendo la misma a los electrodomésticos más habituales de la cocina. Finalmente, se presenta el diseño e implementación de la inteligencia del sistema, que en función de la información procedente del contexto y de las capacidades del usuario da soporte a las principales actividades de la vida diaria (AVD) en la cocina

Adaptation de services dans un espace intelligent sensible au contexte

Grâce à l’apparition des paradigmes de l’intelligence ambiante, on assiste à l’émergence de nouveaux systèmes intelligents ambiants visant à créer et gérer des environnements intelligents d’une façon intuitive et transparente. Ces environnements sont des espaces intelligents caractérisés notamment par l’ouverture, l’hétérogénéité, l’incertitude et la dynamique des entités qui les constituent. Ces caractéristiques soulèvent ainsi des defies scientifiques considérables pour la conception et la mise en place d’un système intelligent adéquat. Ces défis sont principalement au nombre de trois : l’abstraction et la gestion du contexte, la sensibilité au contexte et l’auto-adaptation face aux changements imprévisibles qui peuvent se produire dans un environnement ambiant. Dans cette thèse, nous avons proposé une architecture d’un système intelligent capable d’adapter les services selon les besoins des utilisateurs en tenant compte, d’une part, du contexte environnemental et de ses différents équipements et d’autre part, des besoins variables exprimés par les utilisateurs. Ce système est construit suivant un modèle sensible au contexte, adaptatif et réactif aux évènements. Il se repose sur des entités modulaires de faible couplage et de forte cohésion lui permettant d’être flexible et efficace. Ce système integer également un module d’adaptation de services afin de repérer le contexte et de l’ajuster dynamiquement suivant les attentes des utilisateurs. Cette adaptation est réalisée via deux algorithmes : le premier est un algorithme par renforcement (Q-learning), le deuxième est un algorithme supervisé (CBR). L’hybridation de ces deux algorithmes permet surmonter les inconvénients de Q-learning pour aboutir à une nouvelle approche capable de gérer le contexte, sélectionner et adapter le service

Application coordination in pervasive systems

Our future environment will be managed by a multitude of different pervasive systems. A pervasive system consists of users and devices which cooperate to provide functionality to the users. The provision of functionality is realized by pervasive applications. A major characteristic of pervasive applications is their context-interactivity. On one hand, pervasive applications are context-aware and can adapt themselves to changing context. This ability enables them to provide their functionality in different configurations. On the other hand, pervasive applications have the ability to influence and change the context themselves. A context change can be caused implicitly as a side effect of employed resources or explicitly through the use of actuators. Due to the context-interactivity, problems are likely to occur when two or more applications are executed in the same physical space. Since applications share a common context and interact with it, they can have a direct impact on each other. The described problem is defined as an interference in this thesis. An interference is an application-produced context that impairs the functionality provision of another application. To manage interferences in pervasive systems, a coordination framework is presented. The framework detects interferences using a context model and information about how applications interact with the shared context. The resolution of an interference is achieved through a coordinated application adaptation. The idea is based on the assumption that an alternative application configuration may yield a different context interaction. Thus, the framework determines a configuration for each application such that the context interactions do not interfere. Once a configuration is found for each application, the framework instructs applications to instantiate the selected configuration, resolving the interference. The framework is unique due to three design decisions. At first, the framework is realized as a cross-system coordination layer in order to allow an integration of arbitrary systems. Secondly, the integration of applications can be achieved through the extension of existing systems while preserving their system characteristics. Thirdly, the framework supports a generic interface to integrate arbitrary resolution strategies in order to allow the customization of the framework to the needs of different pervasive systems. The thesis introduces the theoretical concepts of the framework, presents a prototypical implementation and evaluates the prototype and its implemented concepts through extensive measurements