With the ageing of the world population, Do-ItYourself approaches and Smart Personal Assistant are combined to provide customised systems that help people in their daily lives, including fostering their self-reliance and promoting ageing in place, even when these people have cognitive disabilities or perceptual impairments such as “Alzheimer” disease. Ambient Assisted Living systems which rely on this combination can also help caregivers reduce their workload by giving them much relevant information about the health status and the situation of the patients at home, and, furthermore, by giving them facilities to create home automation scenarios to assist the patients. A scenario is the arrangement of daily activities in order to achieve a particular goal. In this paper, we propose a new approach to creating assistance scenarios through voice command, involving two types of ontologies, a smart home ontology (OntoDomus) and a knowledge graph of an activity/action extracted from a scenario in the form of structured knowledge. In particular, we leverage ontology alignment to process voice requests in order to create an assistance scenario for the elderly.

Software technology has exponentially evolved leading to the development of intelligent applications using artificial intelligence models and techniques.Such development impacts all scientific and social fields: home automation, medicine, communication, etc.To make those new applications useful to a larger number of people, researchers are working on how to integrate artificial intelligence into real world while respecting the notion of calm technology.This paper fits in the context of the development of intelligent systems termed "wise systems" that aim at satisfying the calm technology requirement.Those systems are based on the concept of "Wise Object": a software entityobject, service, component, application, etc. -able to learn by itself how it is expected to behave and how it is used by a human or another software entity.During its learning process, a Wise Object constructs a graph that represents its behavior and the way it is used.A major weakness of Wise Objects is that the numerical information that they generate is mostly meaningless to humans.Therefore the objective of the work presented in this paper is to extend Wise Objects with semantic that enable them communicate with humans whose attention will consequently be less involved.In this paper, we address the issue of how to relate two different views using two state-based formalisms: State Transition Graph for views generated by the Wise Objects and Input Output Symbolic Transition System for conceptual views.Our proposal extends previous work done to extend the generated information with the conceptual knowledge using a matching algorithm founded on graph morphism.The first version of the algorithm has several limitations and constraints on the graphs that make it difficult to use in realistic cases.In this paper, we propose to generalize the algorithm and raise those restrictions.To illustrate the complete process, the construction of a sample graph matching on a home-automation system is considered.

International audience

Several architecture analysis methods are proposed in the literature for evaluating both the structure and the behavior of architectures. A parallel between humans and software systems leads to some interesting consideration on kinds of analysis that can be performed on a system architecture, such as the identification of vital element. Such identification improves the system architecture understanding and allows us to estimate to what extent, a change on some components could impact the rest of the architecture.

Large object-oriented applications are structured over large number of packages. Packages are important but complex structural entities that may be difficult to understand since they play different development roles (i.e., class containers, code ownership basic structure, architectural elements...). Maintainers of large applications face the problem of understanding how packages are structured in general and how they relate to each others. In this paper, we present a compact visualization, named Package Surface Blueprint, that qualifies the relationships that a package has with its neighbours. A Package Surface Blueprint represents packages around the notion of package surfaces: groups of relationships according to the packages they refer to. We present two specific views one stressing the references made by a package and another showing the inheritance structure of a package. We applied the visualization on two large case studies: ArgoUML and Squeak.