隨著資訊及通訊技術的快速發展，智慧家庭技術日漸成熟，使得人們的家居生活環境更加便利。由於智慧家庭中技術多元，不同廠商所生產的設備互不相通，導致其操作及安裝程序複雜，影響人們的使用意願，使得目前智慧家庭的願景仍不普及。本論文主要為利用CWMP結合OAuth建立出一個功能完整的智慧家庭服務管理架構，同時兼顧服務使用者與服務供應者的需求，整合家庭內部與外部之間的互動，提供遠端購買模組、佈署服務、監控、計費以及自動偵錯與恢復等管理功能，亦加入了授權與認證規範，期望能提供更完善的管理架構，使得每個家庭雖然由不同的服務與設備組成，但皆能透過同一種技術進行管理，以利智慧家庭維運技術的發展。 / With the rapid development of Information and Communications Technology (ICT), smart home technology has become more and more mature. The applications of smart home technology are still not popular because home devices are usually made by different vendors and thus are not compatible. As a result, the management and setup procedures of these smart home products are complicated. This thesis presents the design and implementation of a CWMP and OAuth based operations management architecture that supports remote purchasing of services and components, deployment of services, diagnosis, billing of service usage and autonomic failure detection and recovery of services. The architecture uses OAuth for supporting security functions of users’ private information. It is expected that the proposed architecture can facilitate the practical applications of smart home technology and provide a reference design for designing operations management mechanisms for smart homes.

隨著智慧家庭概念與技術的興盛與成熟，未來ISP(Internet Service Provider)業者勢必面臨管理大量智慧家庭中各種不同應用競爭頻寬資源的情況。為因應大量且繁雜類型的應用服務彼此競爭智慧家庭端及ISP端的頻寬資源，考量並應用適當的頻寬分配法則以盡可能優化使用者體驗(QoE)是本研究的研究動機。相關文獻的排程演算法如TDPSS (Time Domain Priority Set Scheduler)、MSCDL (Mac Scheduler)、Proportional Fair (PF)及Adaptive Modified Largest Weighted Delay First (AMLWDF)等。若要用以管理大量智慧家庭的頻寬資源時，ISP業者須將家庭申辦頻寬方案以及ISP端的系統頻寬分開考量。ISP在整合(aggregate)多個家庭的頻寬資源請求時，會依服務類別分配頻寬，最後依據不同類別採取適當處理，進而提升不同應用的QoS品質。 本篇論文著重於延遲時間的考量，提出能分類來自各個智慧家庭中，屬於不同 QCI (QoS Class Identifier)級別的頻寬請求並以不同佇列存放，依DADS (Delay Aware Dynamical Scheduling)演算法計算優先權值。我們利用保障頻寬與動態配置頻寬給不同用戶服務佇列，並優先分配頻寬給較高優先權的用戶服務，以期在維持一定公平性的前提下，盡可能地降低延遲來提升QoS品質。 在我們的實驗數據分析中，我們將DADS和其他方法如MSCDL、PF、TDPSS以及AMLWDF進行公平性、產能、延遲以及抖動率等效能優劣的比較與分析。最後在總結與未來研究方向，我們歸納與整理了DADS與PF、MSCDL、TDPSS以及AMLWDF等演算法的效能優劣。實驗結果顯示，在延遲上，DADS勝過PF和TDPSS，但略輸MSCDL及AMLWDF；在抖動率及產能上，DADS均較其它四者為差；公平性上則是劣於TDPSS、PF及MSCDL但優於AMLWDF。雖然DADS在整體的表現並非最好，但在特別重視延遲時間的Category1類別(包含QCI級別為1、2及5的應用服務)的延遲效能僅輸AMLWDF些許，而產能卻明顯勝過AMLWDF，由此可見DADS在Category1的表現最佳。 / With the concept and technology of smart homes becoming more and more mature and popular, Internet service provider (ISP) must face managing large set of various applications from smart homes which competing for bandwidth resources. In order to enhance Quality of Services (QoS) of a lot of various applications while they are competing bandwidth resources of both smart homes (home internal) and Internet service provider (home external), we propose a QoS aware bandwidth allocation criterion to optimize Quality of user Experience (QoE). Since ISP has to manage bandwidth resources of large set of smart homes, in the proposed criterion each ISP separates the bandwidth resources for home external bandwidth and system bandwidth of ISP, respectively. Then, aggregates bandwidth requests of large number of smart homes according to distinct service classes. This thesis focuses on the performance index of delay. We proposed to classify bandwidth requests from smart homes and put them into different queues, finally, calculate priority values by DADS (Delay Aware Dynamical Scheduling) algorithm. The proposed method is able to effectively reduce delay time with certain degree of fairness guarantee by dynamically allocate bandwidth resources for services with distinct service priorities. In the experiments, we compared DADS with other algorithms such as MSCDL (Mac Scheduler), PF (Proportional Fair), TDPSS (Time Domain Priority Set Scheduler) and AMLWDF (Adaptive Modified Largest Weighted Delay First), etc. in terms of fairness, throughput, delay and jitter. The experiments results show that DADS performs much better than PF and TDPSS but a bit worse than MSCDL and AMLWDF in terms of delay. However, DADS shows no better performance than all other algorithms in terms of jitter and throughput. In fairness comparison, DADS is worse than PF, TDPSS and MSCDL but is better than AMLWDF. Though DADS has no superior performance on overall indices, it is a bit worse than AMLWDF in delay of Category1 (including QCI 1, 2 and 5), its throughput is better than AMLWDF. Therefore, DADS’s performance is the best on Category1 considering overall indices.

L'habitat intelligent est l'objet de nombreux travaux de recherche. Il permet d'assister des personnes âgées ou handicapées, d'améliorer le confort, la sécurité ou encore d'économiser de l'énergie. Aujourd'hui, l'informatique ubiquitaire se développe et s'intègre dans l'habitat intelligent notamment en apportant la sensibilité au contexte. Malheureusement, comprendre ce qui se passe dans une maison n'est pas toujours facile. Dans cette thèse, nous explicitons comment le contexte peut permettre de déployer des services adaptés aux activités et aux besoins des habitants. La compréhension du contexte passe par l'installation de capteurs mais aussi par l'abstraction des données brutes en données intelligibles facilement exploitables par des humains et des services. Nous mettons en avant une architecture multi-couches de fusion de données permettant d'obtenir des données contextuelles de niveaux d'abstraction différents. La mise en place des couches basses y est présentée en détail avec l'application de la théorie des fonctions de croyance pour l'abstraction de données brutes issues de capteurs. Enfin, sont présentés le déploiement d'un prototype nous ayant permis de valider notre approche, ainsi que les services déployés. / Smart home is a major subject of interest. It helps to assist elderly or disabled people, improve comfort, safety, and also save energy. Today, ubiquitous computing is developed and integrated into the smart home providing context-awareness. Unfortunately, understanding what happens in a home is not always easy. In this thesis, we explain how context can be used to deploy services tailored to the activities and needs of residents. Understanding context requires the installation of sensors but also the abstraction of raw data into easily understandable data usable by humans and services. We present a multi-layer architecture of data fusion used to obtain contextual information of different levels of abstraction. The implementation of the lower layers is presented in detail with the application of the theory of belief functions for the abstraction of raw sensor data. Finally, are presented the deployment of a prototype that allowed us to validate our approach and the deployed services.

The growth of Internet of Things is steadily increasing, both in Sweden and globally. This relative new technology improves the lives of many; but at the price of their security, privacy and safety. This thesis consists of a literature study and an online survey. It investigates what security, privacy and safety risks Internet of Things devices may bring, how aware people are about these risks, how the user can minimize the risk of being hacked or attacked and what manufacturers can do to make safer Internet of Thing devices. The survey was created based on the risks related to Internet of Things devices which was found during the literature study. It was possible to identify security, privacy and safety risks related to Internet of Things. It was also possible to find answers of how both users and manufacturers can protect their devices from being hacked. The survey showed that there was a correlation between how interested people are in technology and how aware they are of the risks with Internet of Things. Internet of Things can be used to do DDoS attacks, espionage and eavesdropping. People who are interested in technology tends to protect themselves more actively (by changing default password and updating the software) compared to those who are not interested.

A challenge in Human-Robot Interaction is tailoring the social skills of robot companions to match those expected by individual humans during their rst encounter. Currently, large amounts of user data are needed to con gure robot companions with these skills. This creates the need of running long-term Human-Robot Interaction studies in domestic environments. A new approach using personas is explored to alleviate this arduous data collection task without compromising the level of interaction currently shown by robot companions. The personas technique was created by Alan Cooper in 1999 as a tool to de ne user archetypes of a system in order to reduce the involvement of real users during the development process of a target system. This technique has proven bene cial in Human-Computer Interaction for years. Therefore, similar bene ts could be expected when applying personas to Human-Robot Interaction. Our novel approach de nes personas as the key component of a computational behaviour model used to adapt robot companions to individual user's needs. This approach reduces the amount of user data that must be collected before a Human-Robot Interaction study, by associating new users to pre-de ned personas that adapt the robot behaviours through their integration with the computational behaviour model. At the same time that the current robot social interaction level expected by humans during the rst encounter is preserved. The University of Hertfordshire Robot House provided the naturalistic domestic environment for the investigation. After incorporating a new module, an Activity Recognition System, to increase the overall context-awareness of the system, a computational behaviour model will be de ned through an iterative research process. The initial de nition of the model was evolved after each experiment based on the iii ndings. Two successive studies investigated personas and determined the steps to follow for their integration into the targeted model. The nal model presented was de ned from users' preferences and needs when interacting with a robot companion during activities of daily living at home. The main challenge was identifying the variables that match users to personas in our model. This approach open a new discussion in the Human-Robot Interaction eld to de ne tools that help reduce the amount of user data requiring collection prior to the rst interaction with a robot companion in a domestic environment. We conclude that modelling people's preferences when interacting with robot companions is a challenging approach. Integrating the Human-Computer Interaction technique into a computational behaviour model for Human-Robot Interaction studies was more di cult than anticipated. This investigation shows the advantages and disadvantages of introducing this technique into Human-Robot Interaction, and explores the challenges in de ning a personas-based computational behaviour model. The continuous learning process experienced helps clarify the steps that other researchers in the eld should follow when investigating a similar approach. Some interesting outcomes and trends were also found among users' data, which encourage the belief that the personas technique can be further developed to tackle some of the current di culties highlighted in the Human-Robot Interaction literature.

Comprendre le contexte ambiant d'une maison est essentiel pour pouvoir proposer à ses occupants des services adaptés à leurs situations de vie, et qui répondent donc à leurs besoins. Un exemple de tel service est un assistant de communication, qui pourrait par exemple informer les personnes hors de la maison à propos de la disponibilité des habitants de celle-ci pour communiquer. Pour implémenter un tel service, il est en effet nécessaire que la maison prenne en compte les situations de ses occupants, pour ensuite en déduire leurs disponibilités.Dans cette thèse, nous nous intéressons dans un premier temps à définir ce qu'est le contexte dans une maison. Nous défendons que l'activité des occupants est l'une des dimensions principales du contexte d'une maison, nécessaire à la mise en œuvre de systèmes sensibles au contexte. C'est pourquoi nous étudions dans un second temps le problème de la reconnaissance automatique d'activités humaines, à partir des données de capteurs ambiants installés dans la maison. Nous proposons une nouvelle approche d'apprentissage automatique supervisé basée sur les lieux de la maison, qui améliore à la fois les performances de reconnaissance correcte d'activités ainsi que les temps de calcul nécessaires, par rapport aux approches de l'état de l'art.Par ailleurs, ces services sensibles au contexte auront probablement besoin de pouvoir anticiper les situations futures de la maison. En particulier, ils doivent pouvoir anticiper les activités futures réalisées par les occupants. C'est pourquoi nous proposons un nouveau modèle de prédiction supervisée d'activités, basé sur des modèles de l'état de l'art. Nous introduisons un certain nombre d'extensions à ce modèle afin d'améliorer les performances de prédiction, en se basant sur des spécificités des environnements de maisons instrumentées.Enfin, nous nous intéressons à l'estimation de la disponibilité des occupants à communiquer, afin d'illustrer la faisabilité de notre exemple de service d'assistance à la communication. Nous suggérons que la disponibilité peut être inférée à partir des dimensions primaires du contexte, comme le lieu et l'activité (que l'on peut reconnaitre et prédire à l'aide de nos contributions précédentes), mais en prenant également en compte le correspondant initiant la communication, ainsi que la modalité utilisée. Nous discutons de l'impact de l'étape de reconnaissance d'activités sur l'estimation de la disponibilité.Nous évaluons expérimentalement ces contributions sur différents jeux de données de l'état de l'art, ainsi que sur un nouveau jeu de données d'activités et de disponibilités dans la maison que nous avons spécifiquement construit durant cette thèse : Orange4Home. À travers nos contributions à ces trois problèmes, nous démontrons l'implémentabilité d'un service d'assistance à la communication, pouvant conseiller des correspondants extérieurs sur les futures disponibilités des occupants de la maison. De manière plus générale, nous montrons comment des dimensions secondaires du contexte, comme la disponibilité, peuvent être inférées d'autres dimensions du contexte, comme l'activité. Il est donc essentiel pour qu'une maison devienne sensible au contexte, que celle-ci dispose de systèmes de reconnaissance et de prédiction d'activités les plus fiables possibles. / Understanding the context of a home is essential in order to provide services to occupants that fit their situations and thus fulfil their needs. One example of service that such a context-aware smart home could provide is that of a communication assistant, which can for example advise correspondents outside the home on the availability for communication of occupants. In order to implement such a service, it is indeed required that the home understands the situations of occupants, in order to derive their availability.In this thesis, we first propose a definition of context in homes. We argue that one of the primary context dimensions necessary for a system to be context-aware is the activity of occupants. As such, we then study the problem of recognizing activities, from ambient smart home sensors. We propose a new supervised place-based approach which both improves activity recognition accuracy as well as computing times compared to standard approaches.Smart home services, such as our communication assistance example, may often need to anticipate future situations. In particular, they need to anticipate future activities of occupants. Therefore, we design a new supervised activity prediction model, based on previous state-of-the-art work. We propose a number of extensions to improve prediction accuracy based on the specificities of smart home environments.Finally, we study the problem of inferring the availability of occupants for communication, in order to illustrate the feasibility of our communication assistant example. We argue that availability can be inferred from primary context dimensions such as place and activity (which can be recognized or predicted using our previous contributions), and by taking into consideration the correspondent initiating the communication as well as the modality of communication used. We discuss the impact of the activity recognition step on availability inference.We evaluate those contributions on various state-of-the-art datasets, as well as on a new dataset of activities and availabilities in homes which we constructed specifically for the purposes of this thesis: Orange4Home. Through our contributions to these 3 problems, we demonstrate the way in which an example context-aware communication assistance service can be implemented, which can advise on future availability for communication of occupants. More generally, we show how secondary context dimensions such as availability can be inferred from other context dimensions, in particular from activity. Highly accurate activity recognition and prediction are thus mandatory for a smart home to achieve context awareness.

WebRTC est une technologie récente de communication qui permet d’établir des échanges multimédia conversationnels directement entre navigateurs. Nous nous intéressons dans cette thèse à des locuteurs dans un Smart Space (SS) défini comme un environnement centré-utilisateur instrumenté par unensemble de capteurs et d’actionneurs connectés. Nous analysons les capacités nécessaires pour permettre à un participant d’une session WebRTC d’impliquer dans cette même session, les flux induits par les objets connectés appartenant au SS d’un utilisateur quelconque de la session. Cette approche recèle un gisement de nombreux nouveaux usages. Nous limitons notre analyse à ceux concernant l’exercice distant d’une expertise et d’un savoir-faire. Techniquement, il s’agit d’articuler de façon contrôlée WebRTC et IoT/WoT. Nous procédons à une extension de WebRTC par WoT pour fournir à tout utilisateur d’une session WebRTC, un accès aux objets connectés du SS de tout autre participant à la session, en mettant l’accent sur la sécurisation de cet accès ainsi que sur sa conformité aux exigences de respect de la vie privée (RGPD) de l’utilisateur concerné. Le positionnement de notre approche dans le contexte des services de communication opérant dans les villes connectées, impose la prise en compte de SSs multiples et variés induisant chacun ses propres politiques de routage et de sécurité. Pour répondre à nos objectifs, il devient nécessaire au cours d’une session WebRTC, d’identifier, sélectionner, déployer et appliquer les règles de routage et de sécurité de façon à garantir un accès rapide et sécurisé aux différents SSs concernés et distribués sur tout le réseau. Nous développons une architecture originale répondant à ces besoins et intégrant un contrôleur SDN du fait de l’étroite imbrication entre les problématiques de routage et de sécurité. Un prototype illustrant notre approche a été mis en oeuvre et testé afin d’évaluer la performance et la sécurité du système. Nous illustrons finalement notre approche dans le domaine de la santé en démontrant son apport pour gérer une infrastructure de grande taille telle qu’un hôpital. / The richness and the versatility of WebRTC, a new peer-to-peer, real-time and browser based communication technology, allowed the imagination of new and innovative services. In this thesis, we analyzed the capabilities required to allow a participant in a WebRTC session to access the smart Things belonging to his own environment as well as those of any other participant in the same session. The access to such environment, which we call “SmartSpace (SS)”, can be either passive, for example by monitoring the contextual information provided by the sensors, or active by requesting the execution of commands by the actuators, or a mixture of both. This approach deserves attention because it allows solving in an original way various issues such as allowing experts to remotely exercise and provide their expertise and/or knowing how. From a technical point of view the issue is not trivial because it requires a smooth and mastered articulation between two different technologies: WebRTC and the Internet of Things (IoT) /Web of Things (WoT). Hence, the first part of the problem studied in this thesis, consists in analyzing the possibilities of extending WebRTC capabilities with theWoT. So as to provide a secure and privacy-respectful access to the various smart objects located in the immediate environment of a participant to any otherend-user involved in the same ongoing WebRTC session. This approach is then illustrated in the ehealth domain and tested in a real smart home (a typical example of a smart space). Moreover,positioning our approach in the context of communication services operating in smart cities requires the ability to support a multiplicity of SSs,each with its own network and security policy. Hence,in order to allow a participant to access one of his own SSs or one of another participant (through a delegation of access process), it becomes necessary to dynamically identify, select, deploy, and enforce the SS’s specific routing and security rules, so as to have an effective, fast and secure access. Therefore, the second part of the problem studied in this Ph.D.consists in defining an efficient management of the routing and security issues regarding the possibility of having multiple SSs distributed over the entire network.

A principal motivação para o surgimento do conceito de Smart Grid é a otimização do uso das redes de energia através da inserção de novas tecnologias de medição, automação e telecomunicações. A implementação desta complexa infra-estrutura produz ganhos em confiabilidade, eficiência e segurança operacional. Além disso, este sistema tem como principais objetivos promover a geração distribuída e a tarifa diferenciada de energia para usuários residenciais, provendo ferramentas para a participação dos consumidores no gerenciamento global do fornecimento de energia. Considerando também o uso de dispositivos de armazenamento de energia, o usuário pode optar por vender ou armazenar energia sempre que lhe for conveniente, reduzindo a sua conta de energia ou, quando a geração exceder a demanda de energia, lucrando através da venda deste excesso. Esta pesquisa propõe um Sistema Inteligente de Suporte à Decisão baseado em técnicas de aprendizado por reforço como uma solução para o problema de decisão sequencial referente ao gerenciamento de energia de uma Smart Home. Resultados obtidos mostram um ganho significativo na recompensa financeira a longo prazo através do uso de uma política obtida pela aplicação do algoritmo Q-Learning, que é um algoritmo de aprendizado por reforço on-line, e do algoritmo Fitted Q-Iteration, que utiliza uma abordagem diferenciada de aprendizado por reforço ao extrair uma política através de um lote fixo de transições adquiridas do ambiente. Os resultados mostram que a aplicação da técnica de aprendizado por reforço em lote é indicada para problemas reais, quando é necessário obter uma política de forma rápida e eficaz dispondo de uma pequena quantidade de dados para caracterização do problema estudado. / The main motivation for the emergence of the Smart Grid concept is the optimization of power grid use by inserting new measurement, automation and telecommunication technologies into it. The implementation of this complex infrastructure also produces gains in reliability, efficiency and operational safety. Besides, it has as main goals to encourage distributed power generation and to implement a differentiated power rate for residential users, providing tools for them to participate in the power grid supply management. Considering also the use of energy storage devices, the user can sell or store the power generated whenever it is convenient, reducing the electricity bill or, when the power generation exceeds the power demand, make profit by selling the surplus in the energy market. This research proposes an Intelligent Decision Support System as a solution to the sequential decision-making problem of residential energy management based on reinforcement learning techniques. Results show a significant financial gain in the long term by using a policy obtained applying the algorithm Q-Learning, which is an on-line Reinforcement Learning algorithm, and the algorithm Fitted Q-Iteration, which uses a different reinforcement learning approach called Batch Reinforcement Learning. This method extracts a policy from a fixed batch of transitions acquired from the environment. The results show that the application of Batch Reinforcement Learning techniques is suitable for real problems, when it is necessary to obtain a fast and effective policy considering a small set of data available to study and solve the proposed problem.

Smart homes are residences equipped with information and communication technologies that anticipate and respond to the needs of the occupants. Despite the numerous research and industrial efforts, today only few expensive smart homes have been built and sold. The reason behind this slow uptake is the technology-driven approach characterizing existing solutions. The doctoral Thesis aims at demonstrating that a smart home can provide functionalities designed with a user-centered approach, taking into account ergonomic considerations about domestic activity and human cognition. This is achieved in collaboration with cognitive ergonomists, which help "minding the gap" between human context and machine-understandable context. Using off-the-shelf and lightweight instrumentation (also minimizing privacy concerns), extending existing context modeling, reasoning and management tools and following the Ubiquitous Computing principles, the doctoral work led to the following achievements: (i) the inter-disciplinary design of suitable functionalities, in collaboration with cognitive ergonomists; (ii) the design of a context-aware system that captures and reasons about uncertain contextual information in a distributed fashion; (ii) the realization of a working prototype that demonstrates the provision of energy-saving and comfort-preserving functionalities.

IoT is a technology where different devices are equipped with internet connection which makes it possible to control them and exchange data over internet. IoT can be thought of as an umbrella term covering a broad and ever-growing range of services and technologies. One of the segments within IoT is the smart home ecosystem. The tremendous development the last decade within smartphones, wearable devices and broadband has created new ways to connect individual devices in the home (Qasim and Abu-Shanab, 2016; Jeong et al, 2016; Wilson et al, 2017; Hubert et al, 2017). This creates a synergy effect; by connecting multiple devices to a system new value is created. Energy, home controls, security, communication and entertainment services are all included in the smart home (Miller, 2015; Wilson et al, 2017). Even though the concept of smart homes has a large potential it seems like it has not reached its full potential and the diffusion of the innovation among the consumers is still at an early stage (Balta-Ozkan et.al, 2013; Yang et.al 2017). So far, many studies have been performed on the technical aspects of IoT and smart home ecosystems but less attention has been paid on the consumer point of view and what determinants that play a role in the intention to adopt the technology (Yang, Lee, and Zo. 2017). In addition, previous studies have mainly focused of one single device and has not considered the entire ecosystem (Yang, Lee, and Zo. 2017). Therefore, the purpose with this thesis is to study what are the key determinants for the intention to adopt smart homes from an ecosystem point of view. To fulfill the purpose known theoretical models regarding intention to adopt technology have been used to develop a research model. The basis to establish the research model has been the theory of innovation adoption, TRA, TPB, TAM, VAM and UTAUT. Based on the literature four determinants were selected to be included in the model; these were cost, perceived ease of use, perceived usefulness and individualization. The first three are all included in the mentioned theoretical models and have previously been proven to be important for intention to adopt. The last one, individualization is derived from the field of product differentiation. In the literature it is mentioned that the possibility to refine, adjust and modify may be crucial for the user (Dodgson et.al. 2008). With this background it was interested to include individualization as a determinant in the research model and study how it impacts intention to adopt. In addition to the determinants one moderator was included; the composition of the household. In order to collect the empirical data a survey was conducted using the snowball sampling approach via Facebook and LinkedIn. The survey consisted of two sections where the first section aimed to collect background information about the respondent and the second section consisted of questions regarding the determinants. In the second section the respondents were asked to respond according to a 5-point Likert scale. The used questions in the survey was predefined in the literature. Study results show that consumers’ use intention is shaped by individualization, perceived usefulness and perceived ease of use. Cost was found not to be statistically significant. Neither was the composition of the household.