A context information manager for dynamic environments

euzenat2006cInternational audienceIn a pervasive environment, heterogeneous devices need to communicate in order to provide services adapted to users. We have developed an extensible context model using semantic web technologies and a context information management component that enable the interaction between context information producer devices and context information consumer devices and as well as their insertion in an open environment

A context information manager for pervasive environments

euzenat2006bInternational audienceIn a pervasive computing environment, heterogeneous devices need to communicate in order to provide services adapted to the situation of users. So, they need to assess this situation as their context. We have developed an extensible context model using semantic web technologies and a context information management component that enable the interaction between context information producer devices and context information consumer devices and as well as their insertion in an open environment

Organisation multi-agent pour la gouvernance de systèmes Machine-to-Machine

http://www.emse.fr/~picard/publications/persson11jfsma.pdfInternational audienceLe paradigme Machine-to-Machine (M2M) implique des appareils (capteurs, effecteurs) interagissant pour fournir des services localisés dans le monde physique. Avec la maturité du M2M, émerge une demande grandissante pour des solutions mutualisées dans lesquelles les applications peuvent partager un ensemble commun d'appareils. Dans ce contexte, le projet SensCity propose une infrastructure pour mettre en oeuvre des applications à l'échelle de la ville, ce qui nécessite de fournir des moyens de gouvernance agile pour prendre en compte l'extensibilité du système (ie. scalability). Nous proposons d'utiliser les technologies multi-agents pour répondre à cette problématique. Selon cette approche, la stratégie de gouvernance est exprimée par une organisation multi-agent à l'aide du framework organisationnel MOISE. Nous illustrons notre proposition par un système de gestion intelligente du strationnement

Multi-agent based governance model for machine-to-machine networks in a smart parking management system

http://www.emse.fr/~picard/publications/bilal12saconet.pdfInternational audienceProposed in this paper is a multi-agent model that defines a set of global functioning rules for a flexible governance, adapted to parking management within a city. This is designed to aid drivers in finding a parking place, which satisfies a group of criteria, predefined in profiles, providing a better parking service to the public. The Multi-Agent model developed is integrated in the platform SensCity, which is dedicated to the development and deployment of Machine-to-Machine (M2M) systems. The city is divided into a number of parking areas that are equipped with sensors and actuators, which are responsible for transferring data from and to the parking places. Therefore, the agents can work to interpret and manipulate the governance principles modeled and implemented by the multi-agent model, independently from drivers and parking spaces. Moreover, this paper proposes an intelligent endto- end management of parking system using the MOISE organization framework

Context Management and Semantic Modelling for Ambient Intelligence

Ambient Intelligence aims at pushing forward a user centric vision of Pervasive Computing, where the environment better serves our need. This paper describes our current work on modelling and managing context information for smart environments

Gestion dynamique de contexte pour l'informatique pervasive

euzenat2006aNational audienceL'informatique diffuse a pour but d'offrir des services aux utilisateurs humains interagissant avec leur environnement (y compris les objets et autres humains qui l'occupent). Les applications dans ce domaine doivent être capable de considérer le contexte dans lequel les utilisateurs évoluent (qu'il s'agisse de leur localisation physique, leur position sociale ou hiérarchique ou leurs tâches courantes ainsi que des informations qui y sont liées). Ces applications doivent gérer dynamiquement l'irruption dans la scène de nouveaux éléments (utilisateurs ou appareils) même inconnus et produire de l'information de contexte utile à des applications non envisagées. Après avoir examiné les différents modèles de contexte étudiés en intelligence artificielle et en informatique diffuse, nous montrons en quoi ils ne répondent pas directement à ces besoins dynamiques. Nous décrivons une architecture dans laquelle les informations de contexte sont distribuées dans l'environnement et où les gestionnaires de contexte utilisent les technologies développées pour le web sémantique afin d'identifier et de caractériser les ressources disponibles. L'information de contexte est exprimée en RDF et décrite par des ontologies en OWL. Les dispositifs de l'environnement maintiennent leur propre contexte et peuvent communiquer cette information à d'autres dispositifs. Ils obéissent à un protocole simple permettant de les identifier et de déterminer quelles informations ils sont susceptibles d'apporter. Nous montrons en quoi une telle architecture permet d'ajouter de nouveaux dispositifs et de nouvelles applications sans interrompre ce qui fonctionne. En particulier, l'ouverture des langages de description d'ontologies permettent d'étendre les descriptions et l'alignement des ontologies permet de considérer des ontologies indépendantes

Inferring Availability for Communication in Smart Homes Using Context

International audienceThis paper presents a technique for inferring the availability of people to receive communications based on their current situation. This technique uses a context model that associates situations with learned preferences for communications. Situations are represented as a tuple composed of identity, time, place, activity, correspondent, and communication modality. A place-based activity recognition technique is used to recognize the current activity from sensor data. Availability for communications is learned from history of the occupant's preferences of availability for each situation. The system is demonstrated using a dataset of availability preferences recorded from the occupant of an instrumented apartment over a period of 4 weeks. Performance of the system is compared under various assumptions of independence of availability from some of the context elements. The paper is completed with a discussion of how such techniques can be used to construct an intelligent communications assistant for smart home services

Multi-agent Self-organization and Reorganization to Adapt M2M Infrastructures

International audienceMachine-to-Machine (M2M) systems are based on networks of sensors and actuators immersed in the physical world, like in Smart Cities. To manage such networks, classical so-called vertical approaches (where one stakeholder is involved from services to sensors) are very expensive. Thus, a growing trend emerges for horizontal architectures, where several stakeholders collaborate within the same infrastructure. Moreover, the growing number of connected devices raises the key issue of properly controlling and adapting capabilities so that human intervention is minimized. Based on a Multi-Agent Oriented Programming approach, the Adaptive Governance MAS for M2M systems (AGaMeMnon) system installs such capabilities by combining self-organization and reorganization mechanisms. This will be the focus of this paper. AGaMeMnon has been implemented and linked to the SensCity project middleware and evaluated experimentally by the means of simulations

Semantic Approach to Smart Home Data Aggregation Multi-sensor Data Processing for Smart Environments

One salient feature of data produced by the IoT is its heterogeneity. Despite this heterogeneity, future IoT applications including Smart Home, Smart City, Smart Energy services, will require that all data be easily compared, correlated and merged, and that interpretation of this resulting aggregate into higher level context better matches people needs and requirements. In this paper we propose a framework based on semantic technologies for aggregating IoT data. Our approach has been assessed in the domain of the Smart Home with real data provided by Orange Homelive solution. We show that our approach enables simple reasoning mechanisms to be conducted on the aggregated data, so that contexts such as the presence, activities of people as well as abnormal situations requiring corrective actions, be inferred