Une approche autonome pour la gestion logicielle des espaces intelligents

Depuis une vingtaine d'années, les développements dans les technologies de l'information ont fait évoluer les paradigmes de l'informatique. L'arrivée d'approches telles que l'informatique diffuse et l'intelligence ambiante ont fait émerger de nouvelles technologies permettant d'améliorer la qualité des interactions avec les systèmes informatisés. Entre autres, l'application de l'informatique diffuse et de l'intelligence ambiante à des environnements tels que des habitats, les espaces intelligents, offre des milieux où une assistance contextualisée est offerte aux utilisateurs dans la réalisation de leurs activités quotidiennes. Toutefois, la démocratisation de l'informatique diffuse et la mise en place des espaces intelligents rencontrent un bon nombre de problèmes. Le nombre important de composantes matérielles et logicielles, les dépendances entre celles-ci et leurs natures hétérogènes contribuent à la complexité de déploiement et de gestion de ces milieux, entraînant des coûts élevés. Cette thèse vise à contribuer à la gestion logicielle des espaces intelligents par la réduction de la complexité des tâches de gestion. Notre proposition consiste en une approche autonome de la gestion logicielle, fondée sur l'approche de l'informatique diffuse autonome. L'objectif est de fournir un ensemble de fonctionnalités et de mécanismes permettant de rendre autonome la majeure partie des tâches de gestion des logiciels déployés dans des espaces intelligents. Dans le cadre de ce travail, nous proposons une solution permettant l'organisation autonome des logiciels des espaces intelligents. Ainsi, cette solution utilise les informations contextuelles des milieux afin de déterminer quelle répartition des logiciels parmi les appareils des milieux correspond le mieux aux besoins des applications, aux caractéristiques propres des environnements et, non le moindre, aux modalités et préférences d'interaction des utilisateurs de ces milieux. La solution proposée a été implémentée et évaluée à l'aide d'une série de tests et de mises en situation d'organisation logicielle. Les contributions de ce travail à l'état de l'art de la gestion des espaces intelligents sont multiples avec comme principales innovations la présentation d'une vision de l'informatique diffuse autonome, l'implémentation d'un intergiciel d'organisation logicielle autonome basé sur une sensibilité au contexte macroscopique et microscopique et l'intégration des modalités d'interaction des utilisateurs dans le raisonnement portant sur l'organisation des logiciels. Enfin, ce travail de thèse se déroule dans le contexte des recherches du laboratoire DO-MUS de l'Université de Sherbrooke, Canada, et du laboratoire Handicom de Telecom SudParis, France. Ces deux laboratoires travaillent à la conception de solutions permettant d' améliorer la qualité de vie et l' autonomie de personnes dépendantes, atteinte par exemple de troubles cognitifs ou de handicaps physiques

A Toolkit for Exploring Augmented Reality Through Construction with Children

International audienceAugmented Reality begins to be widely mainstream among children, due to some interactive successes in video games and social networks. Based on this interest, we present CartonEd, an open and complete toolkit suitable for children dedicated to the construction of an augmented reality headset device. The toolkit let the children play and explore augmented reality with and beyond handheld devices. Inspired by the Do-It-Yourself movement, the toolkit includes different components such as blueprints, tutorials, videos, mobile apps, a software development kit and an official website. Among the mobile applications, one is implemented to guide the children through the construction process while experiencing augmented reality. To validate our solution (in particular the construction process and the guiding app) and understand its effect on children in regard to their relation to the augmented reality, we conducted four construction sessions. Our study examines the usability of the guiding app and the construction process. We report in this paper the main components of the CartonEd toolkit and the results of an evaluation among 57 children and teenagers (ages 8-16), showing a positive outcome about their own constructed device (all functional), their feelings and wishes regarding the augmented reality

CARTON Project: Do-It-Yourself Approach to Turn a Smartphone into a Smart Eyewear

International audienceThis paper presents a tool to transform a smartphone into a smart eyewear, named "CARTON", following a Do-It-Yourself (DIY) approach. The hardware prototype is made with very simple materials and regular tools we could find anywhere. It also includes a Software Development Kit (SDK) with samples in order to easily adapt or develop new mobile app compatible with this kind of device. By providing everything open-source and open-hardware, we intend to solve the reachability of technologies related to smart eyewear and aim to accelerate research around it. Users experiments were conducted in which participants were asked to create, by themselves, the CARTON's hardware part and perform usability tests with their own creation. Qualitative user feedback and quantitative results prove that CARTON is functional and feasible by anyone, without specific skills

Hand interaction designs in mixed and augmented reality head mounted display: a scoping review and classification

Mixed reality has made its first step towards democratization in 2017 with the launch of a first generation of commercial devices. As a new medium, one of the challenges is to develop interactions using its endowed spatial awareness and body tracking. More specifically, at the crossroad between artificial intelligence and human-computer interaction, the goal is to go beyond the Window, Icon, Menu, Pointer (WIMP) paradigm humans are mainly using on desktop computer. Hand interactions either as a standalone modality or as a component of a multimodal modality are one of the most popular and supported techniques across mixed reality prototypes and commercial devices. In this context, this paper presents scoping literature review of hand interactions in mixed reality. The goal of this review is to identify the recent findings on hand interactions about their design and the place of artificial intelligence in their development and behavior. This review resulted in the highlight of the main interaction techniques and their technical requirements between 2017 and 2022 as well as the design of the Metaphor-behavior taxonomy to classify those interactions

Unsupervised graph-based feature selection via subspace and pagerank centrality

Feature selection has become an indispensable part of intelligent systems, especially with the proliferation of high dimensional data. It identifies the subset of discriminative features leading to better learning performances, i.e., higher learning accuracy, lower computational cost and significant model interpretability. This paper proposes a new efficient unsupervised feature selection method based on graph centrality and subspace learning called UGFS for ‘Unsupervised Graph-based Feature Selection’. The method maps features on an affinity graph where the relationships (edges) between feature nodes are defined by means of data points subspace preference. Feature importance score is then computed on the entire graph using a centrality measure. For this purpose, we investigated the Google’s PageRank method originally introduced to rank web-pages. The proposed feature selection method has been evaluated using classification and redundancy rates measured on the selected feature subsets. Comparisons with the well-known unsupervised feature selection methods, on gene/expression benchmark datasets, demonstrate the validity and the efficiency of the proposed method

Activity recognition in the city using embedded systems and anonymous sensors

This paper presents an embedded system that performs activity recognition in the city. Arduino Due boards with infrared, distance and sound sensors are used to collect data in the city and the activity, profile, and group size recognition performance of different machine learning algorithms (RF, SVM, MLP) are compared. The features were extracted based on fixed-size windows around the observations. We show that it is possible to achieve a high accuracy for binary activity recognition with simple features, and we discuss the optimization of different parameters such as the sensors collection frequency, and the storage buffer size. We highlight the challenges of activity recognition using anonymous sensors in the environment, its possible applications and advantages compared to classical smartphone and wearable based approaches, as well as the improvements that will be made in future versions of this system. This work is a first step towards real-time online activity recognition in smart cities, with the long-term goal of monitoring and offering extended assistance for semi-autonomous people

An autonomic approach for the software management of smart spaces

Depuis une vingtaine d'années, les développements dans les technologies de l'information ont fait évoluer les paradigmes de l'informatique. L'arrivée d'approches telles que l'informatique diffuse ont fait émerger de nouvelles technologies permettant d'améliorer la qualité des interactions avec les systèmes informatisés. Toutefois, la démocratisation de l'informatique diffuse et la mise en place des espaces intelligents rencontrent un bon nombre de problèmes. Le nombre important de composantes matérielles et logicielles et leurs natures hétérogènes contribuent à la complexité de déploiement et de gestion de ces milieux, entraînant des coûts élevés. Cette thèse vise à contribuer à la gestion logicielle des espaces intelligents par la réduction de la complexité des tâches de gestion. Notre proposition consiste en une approche autonome de la gestion logicielle, fondée sur l'approche de l'informatique diffuse autonome. Dans le cadre de ce travail, nous proposons une solution utilisant les informations contextuelles des milieux, afin de déterminer quelle répartition des logiciels parmi les appareils des milieux correspond le mieux au besoin des applications, des caractéristiques propres des environnements et, non le moindre, des modalités et préférences d’interaction des utilisateurs de ces milieux. La solution proposée a été implémentée et évaluée à l’aide d’une série de tests et de mises en situation d’organisation logicielleSince two decades, the developments in the information technologies have changed the computer science paradigms. The arrival of new approaches such as the pervasive computing create new technologies, which improved the quality of the interactions with the I.T. systems, However, the broad utilization of the pervasive computing and the development of smart spaces are facing several challenges. The large number of hardware and software components and their heterogeneous natures, contributes to the complexity of deploying and managing these environments, resulting in high costs. This thesis contributes to the software management of the smart spaces by reducing the complexity of the management tasks. Our proposal consists of an autonomic approach to software management based on the autonomic pervasive computing. As part of this work, we propose a solution using the environment’s contextual information to determine the software distribution among the environment’s devices, which best fits the needs of the software, environments and the interaction modalities and preferences of the environment’s users. The proposed solution was implemented and evaluated using a series of tests and software organization scenario

Augmented human mind: Case of reasoning

In this position paper we try to extend the discussion about the human augmentation of the mind through reasoning. Memory seems favored but both of them play a major role in the mind, we want to equilibrate it. Those two components of our cognitive system are actually quite intertwined with sometimes similar properties and goals. Both are failing, in many ways, that is why we are interested in it, a slight augmentation to those abilities would have huge impact. Therefore, we made a first attempt to propose an approach of a system capable of augmenting the reasoning of his user. First by sensing his context and detect a kind of cognitive bias for many domains through wearable devices and natural language processing. Then we propose a radical method to debiasing that could be used in different scenarios thanks to augmented reality. Finally, those propositions are a beginning of a much needed bigger work that confronts many challenges discussed at the end

Recognizing blind spot check activity with car drivers based on decision tree classifiers

Blind spot check is important driving activity that is a good indicator of drivers’ proficiency and vigilance. By recognizing the blind spot check activity with drivers, it is possible to quantify and qualify the proficiency of the drivers, but also to cross validate this information with other data such the fatigue level. Thus, in this paper, we present a blind spot check activity recognition system where decision tree classifiers are modeled for each drivers and are used to automatically recognize the blind spot checks