The aim of the thesis is to design a web services architecture that shall support the automatic determination of a personalised sensor-system, which is embedded in smart garments, and which shall be used in self-care in order to allow a profane user to record himself a personal electrocardiogram (ECG), at anytime and anywhere. The main challenge consists in the intelligent and dynamic orchestration of context-aware business services that supply the user with an optimal personalised solution, while mastering the system's complexity: context dependent user and system interactions, knowledge extraction from subject-specific vital signs, services reconfiguration automation. The solution to this challenge is to create an Ambient Intelligence which goes beyond Ubiquitous Computing and is capable to replace an expert by proposing an Intelligent Assistance to any citizen. We propose a methodology expressed in terms of Data and Model driven Service Oriented Architecture (DM-SOA), which provides a framework for the production of context-aware intelligent business services. This architecture supports the automation of sophisticated and personalised expert activities, which apply professional knowledge to process an individual case. The proposed solution is based on a new dynamic business process modelling approach and in its implementation via automatically reconfigurable services. It consists in setting-up an intelligent environment based on a business process ontology of context-aware concepts and on related context handling rules for services orchestration. A core-ontology has been designed to support the automation of expert activities related to decision-making. The soundness of the method and of the underlying decision-making techniques has been demonstrated in the cardiology domain for selecting the most adequate subject-specific sensor-system, characterised by its ability to yield for an ECG signal of similar diagnostic content than a standard 12-lead ECG. We propose the design of a new three modalities sensor-system prototype as a response to the need of sensor-systems used on demand in self-care situations and ensuring diagnostic quality signals recordings. This prototype has been tested on a set of healthy volunteers presenting various characteristics in age, sex and morphology. In this context, Ambient Intelligence is demonstrated as an ensemble of professional quality services ready to use by profane users. These services are accessible pervasively, trough the objects people work with / wear on / use each day, and provide an appropriate guidance to the non-competent users. Such an Ambient Intelligence approach strongly supports the vision of an Information Society which corresponds to the long-term goal of the EU Information Society Technologies Research Programme that aims to ease knowledge access. The future healthcare will benefit from this approach and will significantly improve patient care.

Leveraging our experience with the traditional approach to ambient assisted living (AAL) which relies on a large spread of heterogeneous technologies in deployments, this thesis studies the possibility of a more "stripped down" and complementary approach, where only a reduced hardware subset is deployed, probing a transfer of complexity towards the software side, and enhancing the large scale deployability of the solution. Focused on the reasoning aspects in AAL systems, this work has allowed the finding of a suitable semantic inference engine for the peculiar use in these systems, responding to a need in this scientific community. Considering the coarse granularity of situational data available, dedicated rule-sets with adapted inference strategies are proposed, implemented, and validated using this engine. A novel semantic reasoning mechanism is proposed based on a cognitively inspired reasoning architecture. Finally, the whole reasoning system is integrated in a fully featured context-aware service framework, powering its context awareness by performing live event processing through complex ontological manipulation. the overall system is validated through in-situ deployments in a nursing home as well as private homes over a few months period, which itself is noticeable in a mainly laboratory-bound research domain

This thesis takes place in the field of Ambient Intelligence (AmI). AmI Systems are interactive systems composed of many heterogeneous components. From a hardware perspective these components can be divided into two main classes: sensors, using which the system observes its surroundings, and actuators, through which the system acts upon its surroundings in order to execute specific tasks.From a functional point of view, the goal of AmI Systems is to activate some actuators, based on data provided by some sensors. However, sensors and actuators may suffer failures. Our motivation in this thesis is to equip ambient systems with self fault detection capabilities. One of the particularities of AmI systems is that instances of physical resources (mainly sensors and actuators) are not necessarily known at design time; instead they are dynamically discovered at run-time. In consequence, one could not apply classical control theory to pre-determine closed control loops using the available sensors. We propose an approach in which the fault detection and diagnosis in AmI systems is dynamically done at run-time, while decoupling actuators and sensors at design time. We introduce a Fault Detection and Diagnosis framework modeling the generic characteristics of actuators and sensors, and the physical effects that are expected on the physical environment when a given action is performed by the system's actuators. These effects are then used at run-time to link actuators (that produce them) with the corresponding sensors (that detect them). Most importantly the mathematical model describing each effect allows the calculation of the expected readings of sensors. Comparing the predicted values with the actual values provided by sensors allows us to achieve fault-detection.

Almost 20 years ago, Marc Weiser envisioned the prospect of computer in 21st century, and proposed the pioneering notion of ubiquitous computing. One of Weiser's primary ideas has recently evolved to a more general paradigm known as context awareness, becoming a central research theme in many other ubiquitous computing programs. From Active Badge considered as the first context-aware application, there are numerous attempts to build effective context-aware systems. However, how to acquire context, how to process context and how to create context-aware applications is still faced with enormous challenges in the both of research and practice. This dissertation investigates deeply some chosen key issues in context awareness and develops a context-aware middleware. The main research contributions are presented in three categories: a spatialtemporal context represent model, a context-aware middleware and an intelligence context inference engine. The spatial-temporal context representation model is proposed to organize context and relations for context-aware system. Ontology-based method is adopted to construct our model, supporting both knowledge sharing and reuse as well as logic inference. This model adopts two-layer hierarchy structure for different situation. The higher layer comes up with the generic common context, while the lower layer focuses on various specific situations. Differing from existing models, besides taking locational factors into account, it supports different historical context service depending on different context resource. These context histories may be used to predict and infer the context. A context-aware middleware is designed as a platform associated with context retrieval and context processing. It is organized in two layers: the low layer provides a solution to integrate sensors and actuators with a standardized data representation; the high layer: versatile context interpreter focuses on context processing, which is made up of four parts: Context Aggregator, Inference Engine, Context Knowledge Base, and Query Engine in charge of context inferences, expressive query, and persistent storage. This middleware provides an environment for rapid prototyping of context aware services in ambient intelligent. The intelligent inference engine is the central and intellectual component of context-aware middleware. We review all the methods on activity context recognition published in three premier conferences in past decade and conclude that activity context recognition is divided into three facets: basic activity inference, dynamic activity analysis and future activity recommendation. Then we propose an intelligent inference engine based on our context-aware middleware. Beside satisfying requirements of checking the context consistency, our inference engine integrates the three most popular methods on activity context recognition: Rules, Decision Tree, and Hide Markov Model. It provides a solution for all facets of activity context recognition based on our context-aware middleware. The individuals' information collecting from their social networks under permission are leveraged to train intelligent inference engine. We finally use two scenarios (applications) to explain the generic process to develop application via our middleware, and compare and analyze the main aspects of our middleware with other five representative context-aware applications. Our middleware profits good features from existing context-aware systems and improve intelligence via supporting activity context recognition. It provides an efficient platform for a rapid developing of new context-aware applications in ambient intelligence.

The future Internet will need to cater for an increasing number of powerful devices and entire groups of networks to roam in heterogeneous access networks. The current approach towards meeting such requirements, which is to retrofit mobility solutions to different layers of the protocol stack, has given rise to an increasingly fragmented network control layer. Furthermore, retrofitting solutions in an ad-hoc manner to the protocol stack does not provide consistent support from the network to different applications. This lack of a common control layer for facilitating roaming in heterogeneous networking environments represents a crucial challenge both technically and from a user perspective. To this end, a novel mobility architecture forms the basis and the first part of this dissertation. The work on investigating current network mobility solutions and improving these solutions if deemed necessary, in order to reuse within the novel mobility architecture constitutes the second part of this dissertation. The IETF standard protocol for network mobility was implemented and its performance was analysed on a real networking environment. This enabled to identify problems in the standard which affect the handover and routing performance. To address the identified routing and protocol header overheads of the standard network mobility protocol a novel optimal routing framework, OptiNets was proposed. To address the handover latency issues, optimizations to IPv6 network attachment were incorporated and also an access technology independent multiple interface Make-Before-Break handover mechanism was proposed. The viability of the OptiNets framework and the handover optimizations were demonstrated by analysis and by implementation. A more general external factor that affects the performance of mobile networks which is bandwidth scarcity of Wireless Wide Area Networks was addressed, by proposing a bandwidth fuelling architecture for on-board mobile networks. The feasibility of the bandwidth fuelling architecture was analysed by implementing a prototype and evaluating its performance.

This thesis investigates the design of sociable technologies and is divided into three main parts described below. In the first part, we introduce sociable technologies. We review our the definition of technology and propose categories of technologies according to the motivation underlying their design: improvement of control, improvement of communication or improvement of cooperation. Sociable technologies are then presented as an extension of techniques to improve cooperation. The design of sociable technologies are then discussed leading to the observation that acquisition of social common sense is a key challenge for designing sociable technologies. Finally, polite technologies are presented as an approach for acquiring social common sense. In the second part, we focus on the premises for the design of sociable technologies. A key aspect of social common sense is the ability to act appropriately in social situations. Associating appropriate behaviour with social situations is presented as a key method for implementing polite technologies. Reinforcement learning is proposed as a method for learning such associations and variation of this algorithm are experimentally evaluated. Learning the association between situation and behaviour relies on the strong assumption that mutual understanding of social situations can be achieved between technologies and people during interaction. We argue that in order to design sociable technologies, we must change the model of communication used by our technologies. We propose to replace the well-known code model of communication, with the ostensive-inferential model proposed by Sperber and Wilson. Hypotheses raised by this approach are evaluated in an experiment conducted in a smart environment, where, subjects by group of two or three are asked to collaborate with a smart environment in order to teach it how to behave in an automated meeting. A novel experimental methodology is presented: The Sorceress of Oz. The results collected from this experiment validate our hypothesis and provide insightful information for the design. We conclude by presenting, what we believe are, the premises for the design of sociable technologies. The final part of the thesis concerns an infrastructure for the design of sociable technologies. This infrastructure provides the support for three fundamental components. First, it provides the support for an inferential model of context. This inferential model of context is presented; a software architecture is proposed and evaluated in an experiment conducted in a smart-environment. Second, it provides the support for reasoning by analogy and introduces the concept of eigensituations. The advantage of this representation are discussed and evaluated in an experiment. Finally, it provides the support for ostensive-inferential communication and introduces the concept of ostensive interface. / This thesis investigates the design of sociable technologies and is divided into three main parts described below. In the first part, we introduce sociable technologies. We review our the definition of technology and propose categories of technologies according to the motivation underlying their design: improvement of control, improvement of communication or improvement of cooperation. Sociable technologies are then presented as an extension of techniques to improve cooperation. The design of sociable technologies are then discussed leading to the observation that acquisition of social common sense is a key challenge for designing sociable technologies. Finally, polite technologies are presented as an approach for acquiring social common sense. In the second part, we focus on the premises for the design of sociable technologies. A key aspect of social common sense is the ability to act appropriately in social situations. Associating appropriate behaviour with social situations is presented as a key method for implementing polite technologies. Reinforcement learning is proposed as a method for learning such associations and variation of this algorithm are experimentally evaluated. Learning the association between situation and behaviour relies on the strong assumption that mutual understanding of social situations can be achieved between technologies and people during interaction. We argue that in order to design sociable technologies, we must change the model of communication used by our technologies. We propose to replace the well-known code model of communication, with the ostensive-inferential model proposed by Sperber and Wilson. Hypotheses raised by this approach are evaluated in an experiment conducted in a smart environment, where, subjects by group of two or three are asked to collaborate with a smart environment in order to teach it how to behave in an automated meeting. A novel experimental methodology is presented: The Sorceress of Oz. The results collected from this experiment validate our hypothesis and provide insightful information for the design. We conclude by presenting, what we believe are, the premises for the design of sociable technologies. The final part of the thesis concerns an infrastructure for the design of sociable technologies. This infrastructure provides the support for three fundamental components. First, it provides the support for an inferential model of context. This inferential model of context is presented; a software architecture is proposed and evaluated in an experiment conducted in a smart-environment. Second, it provides the support for reasoning by analogy and introduces the concept of eigensituations. The advantage of this representation are discussed and evaluated in an experiment. Finally, it provides the support for ostensive-inferential communication and introduces the concept of ostensive interface.

Dans cette thèse, nous proposons un cadre générique pour la modélisation et la gestion du contexte dans le cadre des systèmes intelligents ambiants et robotiques. Les connaissances contextuelles considérées sont de plusieurs types et issues de perceptions multimodales : connaissances spatiales et/ou temporelles, changement d’états et de propriétés d’entités, énoncés en langage naturel. Pour ce faire, nous avons proposé une extension du langage NKRL (Narrative Knowledge Representation and Reasoning) pour parvenir à une représentation unifiée des connaissances contextuelles qu’elles soient spatiales, temporelles ou spatio-temporelles et effectuer les raisonnements associés. Nous avons exploité l’expressivité des ontologies n-aires sur lesquelles repose le langage NKRL pour pallier aux problèmes rencontrés dans les approches de représentation des connaissances spatiales et dynamiques à base d’ontologies binaires, communément utilisées en intelligence ambiante et en robotique. Il en résulte une modélisation plus riche, plus fine et plus cohérente du contexte permettant une meilleure adaptation des services d’assistance à l’utilisateur dans le cadre des systèmes intelligents ambiants et robotiques. La première contribution concerne la modélisation des connaissances spatiales et/ou temporelles et des changements de contexte, et les inférences spatiales, temporelles ou spatio-temporelles. La deuxième contribution concerne, quant à elle, le développement d’une méthodologie permettant d’effectuer un traitement syntaxique et une annotation sémantique pour extraire, à partir d’un énoncé en langage naturel, des connaissances contextuelles spatiales ou temporelles en NKRL. Ces contributions ont été validées et évaluées en termes de performances (temps de traitement, taux d’erreurs, et taux de satisfaction des usagers) dans le cadre de scénarios mettant en œuvre différentes formes de services : assistance au bien-être, assistance de type aide sociale, assistance à la préparation d’un repas / In this thesis, we propose a generic framework for modeling and managing the context in ambient and robotic intelligent systems. The contextual knowledge considered is of several types and derived from multimodal perceptions : spatial and / or temporal knowledge, change of states and properties of entities, statements in natural language. To do this, we proposed an extension of the Narrative Knowledge Representation and Reasoning (NKRL) language to reach a unified representation of contextual knowledge whether spatial, temporal or spatio-temporal and perform the associated reasoning. We have exploited the expressiveness of the n-ary ontologies on which the NKRL language is based to bearing on the problems encountered in the spatial and dynamic knowledge representation approaches based on binary ontologies, commonly used in ambient intelligence and robotics. The result is a richer, finer and more coherent modeling of the context allowing a better adaptation of user assistance services in the context of ambient and robotic intelligent systems. The first contribution concerns the modeling of spatial and / or temporal knowledge and contextual changes, and spatial, temporal or spatial-temporal inferences. The second contribution concerns the development of a methodology allowing to carry out a syntactic treatment and a semantic annotation to extract, from a statement in natural language, spatial or temporal contextual knowledge in NKRL. These contributions have been validated and evaluated in terms of performance (processing time, error rate, and user satisfaction rate) in scenarios involving different forms of services: wellbeing assistance, social assistance, assistance with the preparation of a meal

La gestion de l'acheminement de messages d'e-santé en environnement ubiquitaire soulève plusieurs défis majeurs liés à la diversité et à la spécificité des cas d'usage et des acteurs, à l'évolutivité des contextes médical, social, logistique, environnemental...Nous proposons une méthode originale d'orchestration autonome et auto-adaptative de services visant à optimiser le flux des messages et à personnaliser la qualité de transmission, en les adressant aux destinataires les plus appropriés dans les délais requis. Notre solution est une architecture générique dirigée par des modèles du domaine d'information considéré et des données contextuelles, basés sur l'identification des besoins et des contraintes soulevées par notre problématique.Notre approche consiste en la composition de services de fusion et de gestion dynamique en temps réel d'informations hétérogènes provenant des écosystèmes source, cible et message, pilotés par des méthodes d'intelligence artificielle pour l'aide à la prise de décision de routage. Le but est de garantir une communication fiable, personnalisable et sensible à l'évolution du contexte, quel que soit le scénario et le type de message (alarme, technique, etc.). Notre architecture, applicable à divers domaines, a été consolidée par une modélisation des processus métiers (BPM) explicitant le fonctionnement des services qui la composent.Le cadriciel proposé est basé sur des ontologies et est compatible avec le standard HL7 V3. L'auto-adaptation du processus décisionnel d'acheminement est assurée par un réseau bayésien dynamique et la supervision du statut des messages par une modélisation mathématique utilisant des réseaux de Petri temporels / Routing policy management of eHealth messages in ubiquitous environment leads to address several key issues, such as taking into account the diversity and specificity of the different use cases and actors, as well as the dynamicity of the medical, social, logistic and environmental contexts.We propose an original, autonomous and adaptive service orchestration methodology aiming at optimizing message flow and personalizing transmission quality by timely sending the messages to the appropriate recipients. Our solution consists in a generic, model-driven architecture where domain information and context models were designed according to user needs and requirements. Our approach consists in composing, in real time, services for dynamic fusion and management of heterogeneous information from source, target and message ecosystems, driven by artificial intelligence methods for routing decision support. The aim is to ensure reliable, personalized and dynamic context-aware communication, whatever the scenario and the message type (alarm, technical, etc.). Our architecture is applicable to various domains, and has been strengthened by business process modeling (BPM) to make explicit the services operation.The proposed framework is based on ontologies and is compatible with the HL7 V3 standard. Self-adaptation of the routing decision process is performed by means of a dynamic Bayesian network and the messages status supervision is based on timed Petri nets

La creatividad es una habilidad de especial interés para el desarrollo humano dado que es una de las dimensiones que permite al individuo y en última instancia a la sociedad enfrentarse a nuevos problemas y retos de forma satisfactoria. Además de entender la creatividad como una serie de factores relativos al individuo creativo, debe tenerse en cuenta que el grado de motivación intrínseca, el entorno y otros factores sociales pueden tener un efecto relevante sobre el desarrollo de esta importante habilidad, por lo que resulta de interés explorarla en el contexto de utilización de tecnologías de la información. En particular, dado que los procesos comunicativos, el intercambio de ideas y la interacción colaborativa entre individuos son un pilar fundamental en los procesos creativos, y también que en gran medida todas ellas son características mayormente facilitadas por las mesas interactivas, una de las principales contribuciones de esta tesis consiste precisamente en la exploración de la idoneidad de las superficies interactivas en tareas creativas colaborativas de construcción en estudiantes adolescentes. Partiendo del estudio realizado, que aporta evidencia empírica acerca de la adecuación de las superficies interactivas como tecnología de potencial para el fomento de la creatividad, esta tesis presenta AGORAS: un middleware para la construcción de ecosistemas de juegos 2D para mesas interactivas, y cuya idea final es entender actividades de aprendizaje más enriquecedoras como aquellas que permiten la propia creación de juegos y su posterior consumo. En el contexto de esta tesis también se ha desarrollado un toolkit básico para construcción de interfaces de usuario para superficies interactivas, se ha desarrollado un modelo de ecosistema basado en entidades que son simulables de acuerdo a leyes físicas; y se ha dotado al modelo de aproximación basada en reglas de comportamiento enriquecidas con expresiones dataflows y de su correspondiente editor para superficies. / Catalá Bolós, A. (2012). AGORAS: Augmented Generation of Reactive Ambients on Surfaces. Towards educational places for action, discussion and reflection to support creative learning on interactive surfaces [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/16695 / Palancia

Los sistemas multi-agente (SMA) son sistemas distribuidos donde entidades autónomas llamadas agentes, ya sean humanos o software, persiguen sus propios objetivos. El paradigma de SMA ha sido propuesto como la aproximación de modelo apropiada para aplicaciones como el comercio electrónico, los sistemas multi-robot, aplicaciones de seguridad, etc. En la comunidad de SMA, la visión de sistemas multi-agente abiertos, donde agentes heterogéneos pueden entrar y salir del sistema dinámicamente, ha cobrado fuerza como paradigma de modelado debido a su relación conceptual con tecnologías como la Web, la computación grid, y las organizaciones virtuales. Debido a la heterogeneidad de los agentes, y al hecho de dirigirse por sus propios objetivos, el conflicto es un fenómeno candidato a aparecer en los sistemas multi-agente. En los últimos años, el término tecnologías del acuerdo ha sido usado para referirse a todos aquellos mecanismos que, directa o indirectamente, promueven la resolución de conflictos en sistemas computacionales como los sistemas multi-agente. Entre las tecnologías del acuerdo, la negociación automática ha sido propuesta como uno de los mecanismos clave en la resolución de conflictos debido a su uso análogo en la resolución de conflictos entre humanos. La negociación automática consiste en el intercambio automático de propuestas llevado a cabo por agentes software en nombre de sus usuarios. El objetivo final es conseguir un acuerdo con todas las partes involucradas. Pese a haber sido estudiada por la Inteligencia Artificial durante años, distintos problemas todavía no han sido resueltos por la comunidad científica todavía. El principal objetivo de esta tesis es proponer modelos de negociación para escenarios complejos donde la complejidad deriva de (1) las limitaciones computacionales o (ii) la necesidad de representar las preferencias de múltiples individuos. En la primera parte de esta tesis proponemos un modelo de negociación bilateral para el problema de / Sánchez Anguix, V. (2013). Complex negotiations in multi-agent systems [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/21570 / Palancia