Abstract In this work, statistical machine learning and pattern recognition methods were developed and applied to sensor-based human context recognition. More precisely, we concentrated on an effective discriminative learning framework, where input-output mapping is learned directly from a labeled dataset. Non-parametric discriminative classification and regression models based on kernel methods were applied. They include support vector machines (SVM) and Gaussian processes (GP), which play a central role in modern statistical machine learning. Based on these established models, we propose various extensions for handling structured data that usually arise from real-life applications, for example, in a field of context-aware computing. We applied both SVM and GP techniques to handle data with multiple classes in a structured multi-sensor domain. Moreover, a framework for combining data from several sources in this setting was developed using multiple classifiers and fusion rules, where kernel methods are used as base classifiers. We developed two novel methods for handling sequential input and output data. For sequential time-series data, a novel kernel based on graphical presentation, called a weighted walk-based graph kernel (WWGK), is introduced. For sequential output labels, discriminative temporal smoothing (DTS) is proposed. Again, the proposed algorithms are modular, so different kernel classifiers can be used as base models. Finally, we propose a group of techniques based on Gaussian process regression (GPR) and particle filtering (PF) to learn to track multiple targets. We applied the proposed methodology to three different human-motion-based context recognition applications: person identification, person tracking, and activity recognition, where floor (pressure-sensitive and binary switch) and wearable acceleration sensors are used to measure human motion and gait during walking and other activities. Furthermore, we extracted a useful set of specific high-level features from raw sensor measurements based on time, frequency, and spatial domains for each application. As a result, we developed practical extensions to kernel-based discriminative learning to handle many kinds of structured data applied to human context recognition. / Tiivistelmä Tässä työssä kehitettiin ja sovellettiin tilastollisen koneoppimisen ja hahmontunnistuksen menetelmiä anturipohjaiseen ihmiseen liittyvän tilannetiedon tunnistamiseen. Esitetyt menetelmät kuuluvat erottelevan oppimisen viitekehykseen, jossa ennustemalli sisääntulomuuttujien ja vastemuuttujan välille voidaan oppia suoraan tunnetuilla vastemuuttujilla nimetystä aineistosta. Parametrittomien erottelevien mallien oppimiseen käytettiin ydinmenetelmiä kuten tukivektorikoneita (SVM) ja Gaussin prosesseja (GP), joita voidaan pitää yhtenä modernin tilastollisen koneoppimisen tärkeimmistä menetelmistä. Työssä kehitettiin näihin menetelmiin liittyviä laajennuksia, joiden avulla rakenteellista aineistoa voidaan mallittaa paremmin reaalimaailman sovelluksissa, esimerkiksi tilannetietoisen laskennan sovellusalueella. Tutkimuksessa sovellettiin SVM- ja GP-menetelmiä moniluokkaisiin luokitteluongelmiin rakenteellisen monianturitiedon mallituksessa. Useiden tietolähteiden käsittelyyn esitetään menettely, joka yhdistää useat opetetut luokittelijat päätöstason säännöillä lopulliseksi malliksi. Tämän lisäksi aikasarjatiedon käsittelyyn kehitettiin uusi graafiesitykseen perustuva ydinfunktio sekä menettely sekventiaalisten luokkavastemuuttujien käsittelyyn. Nämä voidaan liittää modulaarisesti ydinmenetelmiin perustuviin erotteleviin luokittelijoihin. Lopuksi esitetään tekniikoita usean liikkuvan kohteen seuraamiseen. Menetelmät perustuvat anturitiedosta oppivaan GP-regressiomalliin ja partikkelisuodattimeen. Työssä esitettyjä menetelmiä sovellettiin kolmessa ihmisen liikkeisiin liittyvässä tilannetiedon tunnistussovelluksessa: henkilön biometrinen tunnistaminen, henkilöiden seuraaminen sekä aktiviteettien tunnistaminen. Näissä sovelluksissa henkilön asentoa, liikkeitä ja astuntaa kävelyn ja muiden aktiviteettien aikana mitattiin kahdella erilaisella paineherkällä lattia-anturilla sekä puettavilla kiihtyvyysantureilla. Tunnistusmenetelmien laajennuksien lisäksi jokaisessa sovelluksessa kehitettiin menetelmiä signaalin segmentointiin ja kuvaavien piirteiden irroittamiseen matalantason anturitiedosta. Tutkimuksen tuloksena saatiin parannuksia erottelevien mallien oppimiseen rakenteellisesta anturitiedosta sekä erityisesti uusia menettelyjä tilannetiedon tunnistamiseen.

Diversos pesquisadores vêm investigando métodos e técnicas para tornar possível às pessoas anotarem vídeos de modo transparente. A anotação pode ser realizada com a fala, com o uso de tinta digital ou algum outro meio que possa ser capturado enquanto a pessoa assiste ao vídeo. Tais anotações podem ser compartilhadas com outras pessoas, que podem estar assistindo ao mesmo vídeo em um mesmo instante ou em momentos diferentes, sendo interessante ainda que as anotações possam ser realizadas por várias pessoas de modo colaborativo. O paradigma Watch-and-Comment (WaC) propõe a captura transparente de anotações multimodais de usuários enquanto os mesmos assistem e comentam um vídeo. Como resultado desse processo, é gerado um vídeo digital interativo integrando o conteúdo original às anotações realizadas. Esta dissertação tem por objetivo explorar conceitos de computação ubíqua, redes sociais, redes peer-to-peer e TV interativa na proposta de um modelo arquitetural de ciência de informações de contexto para aplicações definidas segundo o paradigma WaC. O modelo explora a integração de um serviço ao paradigma, que auxilie ou forneça alternativas para que aplicações, do momento da captura ao acesso das anotações, utilizem informações de contexto do usuário, do vídeo e das anotações. O modelo também auxilia no estudo de colaboração entre usuários que realizam anotações em vídeos. Outra contribuição da dissertação é a prototipação de aplicações para avaliar e refinar o modelo proposto. São apresentadas extensões para a aplicação WaCTool, considerando o uso de redes sociais e de alternativas para a anotação em vídeos / Researchers have been investigating methods and techniques to allow people to annotate videos ubiquitously. Annotations can be made using voice, digital ink or some other media that can be captured while a person watches a video. These annotations can be shared with other people, who can be watching a video on the same time or at a different one. Also, these annotations can be made by many people collaboratively. The Watch-and-Comment (WaC) paradigm aims at capturing multimodal annotations in an ubiquitous way, while users watch and comment some video. As a result, an interactive digital video is generated combining the original content and the annotations. The work reported on this thesis explores concepts such as ubiquitous computing, social networks, peer-to-peer networks and interactive digital TV, to propose an architectural context-aware model to the applications defined by WaC paradigm. The model proposes the integration of a new service to the paradigm, supporting applications on the annotation process by offering capture alternatives and using context information from user, video and annotations. Also, the model provides a study in collaborative annotation process. Another contribution of this thesis is the prototypes built to evaluate and upgrade the proposed model. The prototypes are extensions from WaCTool, considering the use of social networks and alternatives to annotate in videos

PhD (Business Information Systems) / Department of Business Information Systems / Collaborative Decision Making (CDM) is a never-ending challenge in complex-problem situations where multiple actors are involved. Complex-problem situations involve problems that are ill-defined, ill-structured and wicked such as terrorism. Problems of this nature usually warrant a collaborative effort between actors (organizations) with multiple skill-sets and expertise that at times might be at variance with each other. In order to address this gap, three sub-objectives were postulated from the main research objective, “To determine how optimal/effective CDM can be realized amongst counter-terrorism organizations through context-aware technologies.” Using the theory of synergetics and following deductive thematic analysis, the socio-technical nature of the terrorism problem was depicted by postulating a Digital Terrorism Ecology that consists of Open Digital Infrastructure (ODI), Digital Information Ecosystem (DIE), Digital Terrorism Enactment (DTE), Digital Capability and Digital Enslavement. Based on institutional theory and using PLS-SEM technique, Group/departmental relationships, Organizational co-operation, Organizational form, Technical infrastructure and interoperability, Information and knowledge sharing were identified as the factors influencing attainment of Optimal/effective CDM amongst counter-terrorism organizations. In order to explicate the role of context-aware technologies in enhancing CDM amongst counter-terrorism organizations, a context-aware CDM framework was developed following Design Science Research (DSR) methodology. In this study it was evident from the findings that attainment of OCDM in counter-terrorism contexts is challenging even though it is essential. Among the factors considered as possible influencers of attainment of OCDM, Organizational form (OF) was found to influence Organizational cooperation (OC) and Technical infrastructure and inter-operability (TI). Group/departmental relationships (GDR) were found to influence OF and OC. TI was found to influence OC and GDR and further, Information and knowledge sharing (IKS) was found to influence Optimal/effective CDM (OCDM). Of the three pillars of institutional theory, the regulative pillar offered more insights on issues related to rules, discourse and practice and hence the challenges of OCDM attainment. Practically, this study aims to re-orient the thinking of counter-terrorism organizations by presenting the socio-technical nature of the terrorism problem as well as explicating the role of digital technologies in terrorism. / NRF

This paper aimed to discover how player satisfaction is affected by context-aware elements based on physical, real-world factors in an action role-playing game. The possibility of utilizing player modelling to counteract the reduction in player empowerment in a game heavily influenced by external factors was also explored. This was accomplished by creating an ARPG heavily integrated with various weather, and daytime, context data obtained from web-based APIs. Followed by conducting qualitative tests with help of eleven participants during a time period of a week. The evaluated results were presented in a manner of relevance for both context-driven applications as a whole, and for further exploration within game developments utilization of state of the art technology.

Kontextmedvetenhet kan användas i turistguide applikationer för att bidra användare med information och tjänster. Majoriteten av turistguide applikationer utvecklas vanligtvis för utbildnings eller historiska ändamål. Den här studien presenterar en konceptvalidering av den opublicerade ljuvandrings applikationen "SoundTracker", i syfte att förbättra den. Den nya "SoundTracker" prototypen inriktar sig inte på utbildnings eller historiska ändamål, utan den är inriktad på inspelning, uppspelning, och delning av personliga ljudvandringar med vänner och familj. Konceptvalideringen är begränsad av de definierade forskningsfrågorna i den här uppsatsen. Det handlar i korta drag om en förbättring av noggranheten på de inlästa GPS koordinaterna från en användares position, för att förse användaren med en trevlig användarupplevelse. Dessutom är grafiska användargränssnittet av den originala prototypen förbättrat, och testat genom webb enkäter. Vad gäller delnings funktionaliteten, en test applikation är skapad för att hitta essentiella aspekter som behöver tas hänsyn till i den nya "SoundTracker" prototypen när en användare vill dela ett ljudspår med vänner och familj. Test applikationen testas baserat på samlade svar genom en semi strukturerad interview på människor i åldersgruppen 20-30 år.De erhållna resultaten indikerar på att genom användning av Kalman filter, förbättras noggrannheten på användarens position, vilket resulterar i en ljudvandring med mindre avvikelser jämfört med en GPS-sensor. Vad gäller det förbättrade grafiska användargränssnittet, det var enklare för användarna att förstå den förbättrade prototypen såväl som navigera igenom den, än fallet med den originala prototypen. Användarna finner det även intressant när en delningsfunktion implementeras med designen som diskuteras i det här arbetet. / Context-awareness can be used in tour guide applications in order to provide users with information and services. The majority of tour guide applications are usually developed for educational or historical review purposes. This paper presents a proof-of-concept of the unpublished audio tour guide application, “SoundTracker”, with the aim of improving it. The new “SoundTracker” prototype does not aim for educational or historical review purposes, instead it is aimed for recording, listening and sharing personal audio tour guides with friends and family. The proof-of-concept is limited by the defined research questions found in this paper. In summary, the accuracy of the read-in GPS coordinates of a user’s position is enhanced with Kalman filter, to give an enjoyable user experience. Additionally, the graphical user interface of the original prototype is improved and tested through web-surveys. As for the sharing functionality, a test application is created in order to find what necessary aspects need to be considered in the new "SoundTracker" prototype when a user wants to share a sound-walk with friends and family. The test application is tested based on responses obtained through a semi-structured interview from people in the age of 20-30 years.The obtained results indicate that, with use of Kalman filter, the location accuracy of the user is enhanced, which results in a sound-walk with less deviations compared to location accuracy of only GPS-sensor. Regarding the improved graphical user interface, users found the new "SoundTracker" prototype easier to understand, as well as to navigate through it, than the case in the original prototype. Users also find it interesting when a sharing function is implemented with the design that is discussed in this work.

Le monde de la TV est en cours de transformation de la télévision analogique à la télévision numérique, qui est capable de diffuser du contenu de haute qualité, offrir aux consommateurs davantage de choix, et rendre l'expérience de visualisation plus interactive. IPTV (Internet Protocol TV) présente une révolution dans la télévision numérique dans lequel les services de télévision numérique sont fournis aux utilisateurs en utilisant le protocole Internet (IP) au dessus d’une connexion haut débit. Les progrès de la technologie IPTV permettra donc un nouveau modèle de fourniture de services. Les fonctions offertes aux utilisateurs leur permettent de plus en plus d’autonomie et de plus en plus de choix. Il en est notamment ainsi de services de type ‘nTS’ (pour ‘network Time Shifting’ en anglais) qui permettent à un utilisateur de visionner un programme de télévision en décalage par rapport à sa programmation de diffusion, ou encore des services de type ‘nPVR’ (pour ‘network Personal Video Recorder’ en anglais) qui permettent d’enregistrer au niveau du réseau un contenu numérique pour un utilisateur. D'autre part, l'architecture IMS proposée dans NGN fournit une architecture commune pour les services IPTV. Malgré les progrès rapides de la technologie de télévision interactive (comprenant notamment les technologies IPTV et NGN), la personnalisation de services IPTV en est encore à ses débuts. De nos jours, la personnalisation des services IPTV se limite principalement à la recommandation de contenus et à la publicité ciblée. Ces services ne sont donc pas complètement centrés sur l’utilisateur, alors que choisir manuellement les canaux de diffusion et les publicités désirées peut représenter une gêne pour l’utilisateur. L’adaptation des contenus numériques en fonction de la capacité des réseaux et des dispositifs utilisés n’est pas encore prise en compte dans les implémentations actuelles. Avec le développement des technologies numériques, les utilisateurs sont amenés à regarder la télévision non seulement sur des postes de télévision, mais également sur des smart phones, des tablettes digitales, ou encore des PCs. En conséquence, personnaliser les contenus IPTV en fonction de l’appareil utilisé pour regarder la télévision, en fonction des capacités du réseau et du contexte de l’utilisateur représente un défi important. Cette thèse présente des solutions visant à améliorer la personnalisation de services IPTV à partir de trois aspects: 1) Nouvelle identification et authentification pour services IPTV. 2) Nouvelle architecture IPTV intégrée et comportant un système de sensibilité au contexte pour le service de personnalisation. 3) Nouveau service de recommandation de contenu en fonction des préférences de l’utilisateur et aussi des informations contextes / Internet Protocol TV (IPTV) delivers television content to users over IP-based network. Different from the traditional TV services, IPTV platforms provide users with large amount of multimedia contents with interactive and personalized services, including the targeted advertisement, on-demand content, personal video recorder, and so on. IPTV is promising since it allows to satisfy users experience and presents advanced entertainment services. On the other hand, the Next Generation Network (NGN) approach in allowing services convergence (through for instance coupling IPTV with the IP Multimedia Subsystem (IMS) architecture or NGN Non-IMS architecture) enhances users’ experience and allows for more services personalization. Although the rapid advancement in interactive TV technology (including IPTV and NGN technologies), services personalization is still in its infancy, lacking the real distinguish of each user in a unique manner, the consideration of the context of the user (who is this user, what is his preferences, his regional area, location, ..) and his environment (characteristics of the users’ devices ‘screen types, size, supported resolution, ‘‘ and networks available network types to be used by the user, available bandwidth, ..’) as well as the context of the service itself (content type and description, available format ‘HD/SD’, available language, ..) in order to provide the adequate personalized content for each user. This advanced IPTV services allows services providers to promote new services and open new business opportunities and allows network operators to make better utilization of network resources through adapting the delivered content according to the available bandwidth and to better meet the QoE (Quality of Experience) of clients. This thesis focuses on enhanced personalization for IPTV services following a user-centric context-aware approach through providing solutions for: i) Users’ identification during IPTV service access through a unique and fine-grained manner (different from the identification of the subscription which is the usual current case) based on employing a personal identifier for each user which is a part of the user context information. ii) Context-Aware IPTV service through proposing a context-aware system on top of the IPTV architecture for gathering in a dynamic and real-time manner the different context information related to the user, devices, network and service. The context information is gathered throughout the whole IPTV delivery chain considering the user domain, network provider domain, and service/content provider domain. The proposed context-aware system allows monitoring user’s environment (devices and networks status), interpreting user’s requirements and making the user’s interaction with the TV system dynamic and transparent. iii) Personalized recommendation and selection of IPTV content based on the different context information gathered and the personalization decision taken by the context-aware system (different from the current recommendation approach mainly based on matching content to users’ preferences) which in turn highly improves the users’ Quality of Experience (QoE) and enriching the offers of IPTV services

Les applications contextuelles doivent gérer un flux contenu de contexte selon une logique approprié. Les travaux de recherche en contextualisation se limitent à proposer des plateformes de développement proposant des mécanismes d’adaptation prédéfinie. Cette thèse se propose d’étende l’état de l’art en proposant des nouveaux concepts formant la fondation pour la création d’application contextuelles en adoptant des principes de l’ingénierie logicielle et une décomposition fonctionnelle. Aussi, cela permet l’intégration de comportements contextualisés à des applications non initialement conçus pour cela. La thèse propose une autre manière centrée-contexte permettant de séparer la représentation du contexte de son interprétation, offrant encore plus de flexibilité à la gestion de contexte. Les propositions sont analysées aux lumières d’étude de cas et de simulations. Le résultat de la thèse est l’introduction de nouvelle approche de création d’applications contextuelles qui met en avant le développeur mais aussi l’utilisateur / Context-aware applications must manage a continuous stream of context according to dedicated business logic. Research was limited on proposing frameworks and platforms that have predefined behavior toward applications. This thesis attempts to extend background works by proposing new concepts serving as foundation for a flexible approach for building context-aware applications. The thesis examines the state of the art of context-aware computing, then adopts well-established software design principles and a functional decomposition for designing a reference model for context management enabling seamless integration of context-awareness into applications. Also, the thesis studies the use of context in common applications and proposes a context-centric modeling approach which allows the creation of a graph-based representation where entities are connected to each other through links representing context. Furthermore, the context graph decouples the presentation and the semantics of context, leaving each application to manage the appropriate semantic for their context data. Case studies are conducted for the evaluation of the proposed system in terms of its support for the creation of applications enhanced with context-awareness. A simulation study is performed to analyze the performance properties of the proposed system. The result of this thesis is the introduction of a novel approach for supporting the creation of context-aware applications that supports the integration of context-awareness to existing applications. It empowers developers as well as users to participate in the creation process, thereby reducing usability issues

[pt] A disseminação atual da IoT aumenta a implantação de soluções de processamento de fluxo de dados para monitorar e controlar elementos do mundo real. Uma dessas soluções é o Processamento de Eventos Complexos (CEP). Inicialmente, um único computador ou cluster concentraria toda a execução do CEP. No entanto, a execução centralizada do CEP não é ideal para lidar com o alto volume, velocidade e volatilidade dos fluxos de dados dos sensores IoT. Em vez disso, as aplicações CEP devem criar e decentralizar o processamento de eventos CEP, de preferência tendo agentes CEP na nuvem e em dispositivos na borda. Além disso, tão importante quanto a descentralização, é decidir como o processamento será dividido entre esses dispositivos. Dito isso, estar ciente do contexto atual de cada dispositivo, por exemplo, sua localização e sensores disponíveis, pode ajudar a coletar e (parcialmente) processar os dados em dispositivos próximos ao local onde os dados foram produzidos. Este trabalho apresenta uma plataforma de CEP distribuído com ciência de contexto chamada Global CEP Manager (GCM). GCM é um serviço do middleware ContextNet que oferece suporte à implantação e ao rearranjo dinâmico de consultas CEP baseados em contexto para motores CEP em execução na nuvem, em dispositivos na borda estacionários e M-Hubs, que são dispositivos na borda móveis do ContextNet. O GCM usa o ContextMatcher, que também faz parte deste trabalho. ContextMatcher é um módulo para aplicações ContextNet que permite a entrega de mensagens para nós cujo contexto esteja de compatível com um determinado conjunto de características contextuais. / [en] The current dissemination of IoT increases the deployment of stream processing solutions for monitoring and controlling elements of the real world. One of those solutions is Complex Event Processing (CEP). Initially, a single computer/cluster would concentrate all the CEP execution. However, a centralized execution of CEP is not suitable for coping with the high volume, velocity, and volatility of IoT sensors’ data streams. Instead, applications using CEP should deploy a distributed CEP Event Processing Network, preferably having CEP agents both in the cloud and at edge devices. Also, deciding the arrangement used to split the processing among these tiers and their devices can be just as important. That said, being aware of each of the devices current context, for instance, their location and available sensors, can help to collect and (partially) process the data on devices close to the data s production site. This work presents a contextaware distributed CEP platform called Global CEP Manager (GCM). GCM is a service of the ContextNet middleware that supports the context-based deployment, and dynamic rearrangement of CEP queries to CEP engines executing in the cloud, stationary edge devices, and M-Hubs, which are ContextNet s mobile edge devices. GCM uses the ContextMatcher, which is also part of this work. ContextMatcher is a module for ContextNet applications that enables the delivery of messages for nodes that match a specified set of contextual requirements.

La Computaci'on Ubicua plantea proveer de inteligencia a nuestros entornos ofreciendo servicios a los usuarios que permitan ayudarlos en su vida cotidiana. Con la inclusi'on de dispositivos ubicuos en nuestra vida (por ejemplo los dispositivos m'oviles), los usuarios hemos pasado a estar siempre conectados al entorno, pudiendo interactuar con el. Sin embargo, a diferencia de las interacciones de escritorio tradicionales donde los usuarios eran quienes ped'¿an informaci'on o introduc'¿an datos, las interacciones ubicuas tienen que lidiar con un entorno de los usuarios variable, demandando uno de los recursos mas valiosos para los usuarios: la atenci'on humana. De esta forma, un reto en el paradigma de computaci'on ubicua es regular las peticiones de atenci'on del usuario. Esto implica que las interacciones de los servicios deber'¿an comportarse de una manera ¿considerada¿ teniendo en cuenta el grado en que cada servicio se inmiscuye en la mente del usuario (el nivel de molestia). Partiendo de las bases de la Ingenier'¿a Dirigida por Modelos (MDE) y de los principios de la Computaci'on Considerada, esta tesis se orienta a dise¿nar y desarrollar servicios que sean capaces de adaptar sus interacciones de acuerdo a la atenci'on del usuario en cada momento. El principal objetivo de esta tesis es introducir capacidades de adaptaci'on considerada en los servicios ubicuos para proporcionar interacciones que no perturben al usuario. Esto lo conseguimos mediante un proceso de desarrollo que cubre desde el dise¿no de los servicios hasta su implementaci'on, centr'andose en los requisitos de adaptaci'on de la interacci'on particulares para cada usuario. Para el dise¿no del comportamiento de la interacci'on en base al nivel de molestia se han de¿nido unos modelos de intromisi'on e interacci'on independientes de la tecnolog'¿a. Estos modelos son los que posteriormente conducen la adaptaci'on de la interacci'on din'amicamente, por medio de una infraestructura aut'onoma que los usa en tiempo de ejecuci'on. Esta infraestructura es capaz de detectar cambios en la situaci'on del usuario (por ejemplo cambios en su localizaci'on, su actividad, etc.) y planear y ejecutar modi¿caciones en la interacci'on de los servicios. Cuando se detecta un cambio del contexto del usuario, los servicios se auto-adaptan para usar los componentes de interacci'on m'as apropiados de acuerdo a la nueva situaci'on y no molestar al usuario. Adem'as, como las necesidades y preferencias de los usuarios pueden cambiar con el tiempo, nuestra aproximaci'on utiliza la estrategia del aprendizaje por refuerzo para ajustar los modelos de dise¿no iniciales de forma que maximicemos la experiencia del usuario. El dise¿no inicial de la interacci'on basado en el nivel de molestia nos asegura un comportamiento inicial consistente con las necesidades de los usuarios en ese momento. Luego, este dise¿no se va re¿nando de acuerdo al comportamiento y preferencias de cada usuario por medio de su retroalimentaci'on a trav'es de la experiencia de uso. Adem'as, tambi'en proporcionamos una interfaz m'ovil que permite a los usuarios ¿nales personalizarse de forma manual los modelos en base a sus propias preferencias. El trabajo presentado en esta tesis se ha llevado a la pr'actica para su evaluaci'on desde el punto de vista de los dise¿nadores y de los usuarios ¿nales. Por una parte, el m'etodo de dise¿no se ha validado para comprobar que ayuda a los dise¿nadores a especi¿car este tipo de servicios. Pese a que el proceso de desarrollo no ofrece una automatizaci'on completa, las gu'¿as ofrecidas y la formalizaci'on de los conceptos implicados ha demostrado ser 'util a la hora de desarrollar servicios cuya interacci'on es no molesta. Por otra parte, la adaptaci'on de la interacci'on en base al nivel de molestia se ha puesto en pr'actica con usuarios para evaluar su satisfacci'on con el sistema y su experiencia de usuario. Esta validaci'on ha desvelado la importancia de considerar los aspectos de molestia en el proceso de adaptaci'on de la interacci'on para ayudar a mejorar la experiencia de usuario. / In Ubiquitous Computing environments, people are surrounded by a lot of embedded services. Since ubiquitous devices, such as mobile phones, have become a key part of our everyday life, they enable users to be always connected to the environment and interact with it. However, unlike traditional desktop interactions where users are used to request for information or input data, ubiquitous interactions have to face with variable user¿s environment, making demands on one of the most valuable resources of users: human attention. A challenge in the Ubiquitous Computing paradigm is regulating the request for user¿s attention. That is, service interactions should behave in a considerate manner by taking into account the degree in which each service intrudes the user¿s mind (i.e., the obtrusiveness degree). In order to prevent service behavior from becoming overwhelming, this work, based on Model Driven Engineering foundations and the Considerate Computing principles, is devoted to design and develop services that adapt their interactions according to user¿s attention. The main goal of the present thesis is to introduce considerate adaptation capabilities in ubiquitous services to provide non-disturbing interactions. We achieve this by means of a systematic method that covers from the services¿ design to their implementation and later adaptation of interaction at runtime / Gil Pascual, M. (2013). Adapting Interaction Obtrusiveness: Making Ubiquitous Interactions Less Obnoxious. A Model Driven Engineering approach [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/31660

Advances in Internet-of-Things integrate sensors and actuators in everyday items or even people transforming our society at an accelerated pace. This occurs in areas such as agriculture, logistics, transport, healthcare, and smart cities and has created new ways to interact with and experience entertainment, (serious) games, education, etc. Common to these domains is the challenge to realize and maintain complex relations with any object or individual globally, with the requirement for immediacy in maintaining relations of varying complexity. Existing architectures for maintaining relations on the Internet, e.g., DNS and search engines are insufficient in meeting these challenges. Their deficiencies mandate the research presented in this dissertation enabling the maintenance of dynamic and multi-criteria relationships among entities in real-time in an Internet-of-Things while minimizing the overall cost for maintaining such context-centric relationships. A second challenge is the need to represent nearness in context-centric relationships, since solutions need to build on what is closely related. The dissertation shows that the proximity on relations can be used to bring about the scalability of maintaining relationships across the IoT. It successfully demonstrates the concept and feasibility of self-organizing context-centric overlay networks for maintaining scalable and real-time relationships between endpoints co-located with associated physical entities. This is complemented by an object model for annotating objects and their relationships as derived and defined over the underpinning context interactions. Complementing measures of nearness are added through a non-metric multi-criteria approach to evaluating the notion of context proximity. A query language and an extension to the publish-subscribe approaches achieves distributed support for discovering such relationships; locating entities relative to a defined hyper-sphere of interest. Furthermore, it introduces adaptive algorithms for maintaining such relationships at minimal overall costs. The results demonstrate the feasibility of moving towards context-centric approaches to immersion and that such approaches are realizable over vast and distributed heterogeneous collections of user and their associated context information.