Modeling Users, Context and Devices for Ambient Assisted Living Environments

The participation of users within AAL environments is increasing thanks to the capabilities of the current wearable devices. Furthermore, the significance of considering user’s preferences, context conditions and device’s capabilities help smart environments to personalize services and resources for them. Being aware of different characteristics of the entities participating in these situations is vital for reaching the main goals of the corresponding systems efficiently. To collect different information from these entities, it is necessary to design several formal models which help designers to organize and give some meaning to the gathered data. In this paper, we analyze several literature solutions for modeling users, context and devices considering different approaches in the Ambient Assisted Living domain. Besides, we remark different ongoing standardization works in this area. We also discuss the used techniques, modeled characteristics and the advantages and drawbacks of each approach to finally draw several conclusions about the reviewed works

Modeling Users, Context and Devices for Ambient Assisted Living Environments

The participation of users within AAL environments is increasing thanks to the capabilities of the current wearable devices. Furthermore, the significance of considering user’s preferences, context conditions and device’s capabilities help smart environments to personalize services and resources for them. Being aware of different characteristics of the entities participating in these situations is vital for reaching the main goals of the corresponding systems efficiently. To collect different information from these entities, it is necessary to design several formal models which help designers to organize and give some meaning to the gathered data. In this paper, we analyze several literature solutions for modeling users, context and devices considering different approaches in the Ambient Assisted Living domain. Besides, we remark different ongoing standardization works in this area. We also discuss the used techniques, modeled characteristics and the advantages and drawbacks of each approach to finally draw several conclusions about the reviewed works

Modélisation d'une interaction système-résident contextuelle, personnalisée et adaptative pour l'assistance cognitive à la réalisation des activités de la vie quotidienne dans les maisons connectées

Alors que le nombre de personnes vivant avec des déficits cognitifs qui découlent d’un traumatisme craniocérébral (TCC) va en croissant, les technologies d’assistance sont de plus en plus développées pour résoudre les problèmes qu’ils induisent dans la réalisation des activités de la vie quotidienne. L’Internet des objets et l’intelligence ambiante offrent un cadre pour fournir des services d’assistance sensibles au contexte, adaptatifs, autonomes et personnalisés pour ces personnes ayant des besoins particuliers. Une revue de la littérature sur le sujet permet de constater que les systèmes existants offrent très souvent une assistance excessive, quand l’aide contient plus d’information que nécessaire ou quand elle est fournie automatiquement à chaque étape de l’activité. Cette assistance, inadaptée aux besoins et aux capacités de la personne, est contraire à certains principes de la réadaptation cognitive qui prônent la fourniture d’une assistance minimale pour encourager la personne à agir au meilleur de ses capacités. Cette thèse propose des modèles pour automatiser l’assistance cognitive sous forme de dialogue contextuel entre une personne ayant des déficits cognitifs dus au TCC et un système lui fournissant l’assistance appropriée qui l’encourage à réaliser ses activités par lui-même. Les principales contributions sont : (1) un modèle ontologique comme support de l’assistance cognitive dans les maisons connectées ; (2) un modèle d’interaction entre l’agent intelligent d’une maison connectée et une personne ayant subi un TCC, dans le cadre de l’assistance cognitive. Le modèle ontologique proposé s’appuie sur les actes de langages et les données probantes de la réadaptation cognitive afin que l’assistance reflète la pratique clinique. Il vise à fournir aux maisons intelligentes la sémantique des données nécessaires pour caractériser les situations où il y a besoin d’assistance, les messages d’assistance de gradations différentes et les réactions de la personne. Informé par le modèle ontologique, le modèle d’interaction basé sur des arbres de comportement (« behaviour trees ») permet alors à un agent intelligent de planifier dynamiquement la diffusion de messages d’assistance progressifs avec des ajustements si nécessaire, en fonction du profil et du comportement du résident de la maison connectée lors de l’accomplissement de ses activités. Une validation préliminaire montre l’applicabilité des modèles dans l’implémentation de scénarios relatifs à l’utilisation sécuritaire d’une cuisinière connectée dédiée aux personnes ayant subi un TCC

Apport de l'intelligence artificielle au domaine des villes intelligentes : application à l'assistance des déplacements des personnes à mobilité réduite

La transformation des villes en « villes intelligentes » est un des objectifs que les gouvernements visent depuis une dizaine d’années. Cette transformation touche à plusieurs aspects de la ville, dont l’éco-citoyenneté, la gouvernance durable ou encore la mobilité intelligente. C’est sur cet aspect que nos travaux se focalisent. En effet, malgré une certaine progression depuis quelques années, les personnes à mobilité réduite sont souvent oubliées dans la question de l’amélioration des déplacements urbains grâce aux technologies de l’information et de la communication. Parmi ces technologies, l’intelligence artificielle englobe plusieurs domaines et est en plein essor. Un de ces derniers, l’intelligence ambiante vise à la conception de services interconnectés interagissant avec l’environnement physique réel pour offrir des services visant à supporter les activités humaines. C’est dans ce contexte que se placent nos travaux : l’étude et la construction d’un système ambiant dédié à l’assistance des personnes à mobilité réduite en milieu urbain. Or, plusieurs verrous contraignent la conception d’un tel système. Tout d’abord, dans ces domaines, nous avons remarqué que le vocabulaire des termes issus de ces domaines était inconstant, et que toute la communauté scientifique n’est pas unanime sur la définition de certains concepts. Notre première contribution consiste en une ontologie, décrite en OWL, qui recouvre l’ensemble des éléments et concepts nécessaires à la conception de ce type de systèmes. Ensuite, plusieurs études scientifiques actuelles soulignent le manque de modèle d’architecture générique pour de tels systèmes. Ce faisant, la myriade de solutions proposées dans ce domaine souffre de limites fortes sur le plan de l’interopérabilité et de la réutilisabilité des travaux. C’est pourquoi notre deuxième contribution se traduit en un modèle générique facilitant la conception de tout type de système ambiant dédié à l’assistance. Ce modèle s’appuie sur l’ontologie proposée, tout en gardant les utilisateurs au centre du modèle. Enfin, il a été remarqué que les systèmes ambiants dédiés à l'assistance sont déployés de manière ad-hoc. Soit en simulation, en évaluant statistiquement les sorties du système. Soit en milieu réel, où l'évaluation du système se fait par la même observation statistique des sorties, ou par un questionnaire d'évaluation soumis aux utilisateurs. Nous proposons une approche originale de mise en œuvre de tels systèmes. D'une part, cette dernière se base sur une mise en opération du système par simulation hybride, sur laquelle les éléments réels sont ajoutés progressivement, jusqu'à un déploiement en milieu réel complet. D'autre part, dans le but d'évaluer l'impact direct du système, nous proposons l'analyse de son impact par les outils issus du domaine de l'analyse du réseau social des utilisateurs.Abstract: The transformation of cities into "smart cities" is one of the goals that governments have been aiming at for the last ten years. This transformation affects several aspects of the city, including eco-citizenship, sustainable governance, and smart mobility. It is on this aspect that our work focuses. Indeed, despite a certain progress in the last few years, people with reduced mobility are often forgotten when it comes to improving urban travel thanks to information and communication technologies. Among these technologies, artificial intelligence is booming and encompasses several fields. Among them, ambient intelligence aims at the design of interconnected services interacting with the real physical environment to provide services to support human activities. It is in this context that our work is placed: the study and construction of an ambient system dedicated to the assistance of people with reduced mobility in an urban environment. However, the design of such a system is constrained by several obstacles. First, we noticed that the vocabulary of the terms coming from these domains was inconstant, and that the whole scientific community is not unanimous on the definition of certain concepts. Our first contribution consists in an ontology, described in OWL, which covers all the elements and concepts necessary for the design of this type of system. Secondly, several current scientific studies underline the lack of a generic architecture model for such systems. As a result, the myriad of solutions proposed in this field suffer from strong limitations in terms of interoperability and reusability of the works. Therefore, our second contribution translates into a generic model facilitating the design of any type of ambient system dedicated to assistance. This model is based on the proposed ontology, while keeping the users at the center of the model. Finally, it has been noticed that ambient systems dedicated to assistance are deployed in an ad-hoc way, either in simulation or in real environment, with an evaluation limited to a statistical analysis of the outputs, or by an evaluation questionnaire submitted to users. We propose an original approach to the implementation of such systems. On the one hand, this approach is based on a simulation-based implementation of the system, on which real elements are progressively added, until a complete deployment in real environment. On the other hand, to evaluate the direct impact of the system, we introduce the analysis of its impact by tools coming from the field of user social network analysis

A business model framework for the Internet of Things

The Internet of Things (IoT) is an emerging technology with research interests transcending disciplines of computer sciences and computer engineering to agriculture, business management, civil engineering, architecture, medical sciences, social science etc. This is because of the potential expanding range of its application areas of wind mill operation and irrigation control, supply chain and logistics, manufacturing, home and office environment, healthcare, social care, etc. As it is usually the case with emerging technologies, IoT is faced with the challenge of bridging the gap between the technology development and corresponding business model design. Without a workable business model, the IoT paradigm may end up in research labs and subsequently fade away. A business model should show how lucrative it is to be in the IoT business by adding value to the customer and generating revenue for the business firm. This research is a contribution towards the goal of developing a business model for IoT, with customer/user value potential as the focal point. The comprehensive literature review carried out during this research (i) outlines the concept of business models; (ii) investigates through desk research, existing digital technology business models with focus on two (2) established digital technology firms and identified five generic components of their business models including but not limited to subscription, training, price, satisfaction, and trust, which were used for the primary investigation; (iii) investigates the IoT state-of-the-arts by elaborating on the IoT space and precursor technologies that are part of its ecosystem with the aim of describing, illustrating and developing application prototypes for three IoT scenarios of health monitoring, the use of the library and borrowing of books (a novel idea), and home environment; (iv) evaluates business model framework representation maps in current use, and specifically modified the general structure, content, and performance framework map to design an adoption framework map called a customer-focused business model framework map for IoT (CBMF4IoT). The unique approach to business model research involved conducting a user-led experiment to investigate the likelihood of IoT adoption of existing digital technology business models, as the customer value potential aspect of a business model design was the focal point of this research. Specifically, the experiment was aimed at determining if there was any significant differences in user inclinations towards the five generic components of existing digital technology business models based on smartphone context and IoT products context in a within-subjects design, with sample population drawn from University of Sussex community. The experimental design relied on participants' past experiences with smartphone for them to indicate their pre-purchase inclinations towards the five generics components. For the IoT products context, descriptions and diagrammatic illustration of the three IoT scenarios with their corresponding Just-in-Mind clickable prototypes served as educational tools to enable participants to be acquainted with IoT in order for them to indicate their potential pre-purchase inclinations towards the five generic components. A unique procedure for business model adoption likelihood was designed using the Sign test for high, low, and medium likelihood of adoption. The results of this test indicate medium likelihood of adoption for three of the generic components and low likelihood of adoption for two of the generic components. The results of this test was then fed to the CBMF4IoT. This thesis demonstrates that reusability of successful digital technology business models could potentially result in market success for an emerging digital technology in a B2C context, as users opinion formed the bases for the conclusions, instead of the conventional opinion gathering from only experts, business owners, and practitioners for a BM research

AN INVESTIGATION INTO CONTEXT-AWARE AUTOMATED SERVICE IN SMART HOME FACILITIES: SEARCH ENGINE AND MACHINE LEARNING WITH SMARTPHONE

Technological advances, in general, coupled with the widespread use of smartphones, create ever more opportunities for mobile applications. This thesis considers the use of such devices within embedded systems to provide automated services in smart home automation. The overall approach links together context-aware data from the physical environment, sensors and actuators for domestic appliances and statistics-based decision-making. A prototype system named ‘Wireless Sensor/Actuator Mobile Computing in the Smart Home’ (WiSAMCinSH) is developed, which in turns aims to provide services that can benefit clients who are currently dependent on others in their daily activities. This research highlights and covers the following concepts. Firstly, it addresses the need to improve the prototypical decision-making model by enabling it to take into account context-aware information as conditions under which particular action decisions are appropriate. Secondly, an essential aspect of context-aware performance architecture is that its features must be of high accuracy, explicitly readable and fast. Thirdly, it is necessary to determine which probability-based rules are most effective in generating the dynamic environment to control the home facilities. Finally, it is important to analyse and classify in depth the accuracy of context acquisition and the corresponding context control using cross-validation methods. A case study uses integrated mobile detection technology to improve the efficiency of mobile applications, taking into account the resource limitations forced on the use of mobile devices. It also utilises other embedded sensing technologies to predict expectations, thereby enabling automatic control of facilities in the home. The main approach is to combine search engines and machine learning to create a system architecture for a context-aware computing service. Among the major challenges are finding the best statistics-based rules for decision-making and overcoming the heterogeneous character of the many devices which are used together. The results achieved show very promising potential for the use of mobile applications within a context-aware computing service, albeit one which still presents problems to be resolved through future research