Alexandru Sorici

Exploiting the JaCaMo framework for realising an adaptive room governance application

Ambient Intelligent (AmI) applications are often meant to be used in complex and highly dynamic environments and are characterized by features such as context-awareness, personalisation, adaptivity and anticipation of users desires. In this demo we focus on how the use of the high level of abstraction provided by multi agent-oriented technologies and related programming languages - and in particular of the ones rooted on a strong notion of agency - can ease the conceiving and realisation of AmI applications exhibiting such features. For doing this we present here an adaptive governance application, realised using the JaCaMo framework, for the dynamic management and allocation of rooms in the context of a smart co-working space.

CONSERT: Applying semantic web technologies to context modeling in ambient intelligence

Representation and reasoning about context information is a main research area in Ambient Intelligence (AmI). Context modeling in such applications is facing openness and heterogeneity. To tackle such problems, we argue that usage of semantic web technologies is a promising direction. We introduce CONSERT, an approach for context meta-modeling offering a consistent and uniform means for working with domain knowledge, as well as constraints and meta-properties thereof. We provide a formalization of the model and detail its innovative implementation using techniques from the semantic web community such as ontology modeling and SPARQL. A stepwise example of modeling a commonly encountered AmI scenario showcases the expressiveness of our approach. Finally, the architecture of the representation and reasoning engine for CONSERT is presented and evaluated in terms of performance.

Multi-Agent Based Flexible Deployment of Context Management in Ambient Intelligence Applications

Industry involvement in the Ambient Intelligence (AmI) domain together with openness and complexity expected from context-aware applications drive research into generic context management middleware (CMM) solutions. However, the variety of AmI scenarios requires flexibility in design-time and run-time deployment options, while existing CMM approaches do not sufficiently address the means to easily configure and engineer such mechanisms. In response to these challenges we propose a context management middleware with a design based on techniques and principles from the research fields of Multi-Agent Systems and the Semantic Web. We focus on showing how deployment principles based directly on the application context model and ontology-based configuration options offered by CONSERT lead to flexible development. We showcase the usage of our solution with a scenario from the area of smart university life management.

Applying Semantic Web Technologies to Context Modeling in Ambient Intelligence

Representation and reasoning about context information is a main area of research in Ambient Intelligence (AmI). Given the openness and decentralization of many AmI applications, we argue that usage of semantic web technologies for context modeling brings advantages in terms of standards, uniform representation and expressive reasoning. We present an approach for modeling of context information which builds and improves upon related lines of work (SOUPA, CML, annotated RDF). We provide a formalization of the model and an innovative realization using the latest proposals for semantic web standards like RDF and SPARQL. A commonly encountered ambient intelligence scenario showcases the approach.

A Novel Integrated Architecture for Ambient Assisted Living Systems

The increase in life expectancy and the slumping birth rates across the world result in lengthening the average age of the society. Therefore, we are in need of techniques that will assist the elderly in their daily life, while preventing their social isolation. The recent developments in Ambient Intelligence and Information and Communication Technologies have facilitated a technological revolution in the field of Ambient Assisted Living. At present, there are many technologies on the market that support the independent life of older adults, requiring less assistance from family and caregivers, yet most of them offer isolated services, such as health monitoring, reminders etc, moreover none of current solutions incorporates the integration of various functionalities and user preferences or are formally analyzed for their functionality and quality-of-service attributes, a much needed endeavor in order to ensure safe mitigations of potential critical scenarios. In this paper, we propose a novel architectural solution that integrates necessary functions of an AAL system seamlessly, based on user preferences. To enable the first level of the architectures analysis, we model our system in Architecture Analysis and Design Language, and carry out its simulation for analyzing the end-to-end data-flow latency, resource budgets and system safety.

Policy-Based Adaptation of Context Provisioning in AmI

With the increasing openness and complexity introduced by recent Ambient Intelligence application domains (e.g. Web-of-Things, Sensing-as-a-Service), adaptation of Context Provisioning becomes a key issue. However, methods to easily specify and engineer such mechanisms remain insufficiently explored. In this work we present and evaluate our approach of using semantic-web and multi-agent technologies to define and execute context provisioning policies within our Context Management Middleware called CONSERT.

CAMI - An Integrated Architecture Solution for Improving Quality of Life of the Elderly

The increasing ageing population worldwide imposes some new challenges to the society like the provision of dependable support while facing a shortage in the numbers of caregivers, increased health ...

User Detection, Tracking and Recognition in Robot Assistive Care Scenarios

The field of assistive robotics is gaining traction in both research as well as industry communities. However, capabilities of existing robotic platforms still require improvements in order to implement meaningful human-robot interactions. We report on the design and implementation of an external system that significantly augments the person detection, tracking and identification capabilities of the Pepper robot. We perform a qualitative analysis of the improvements achieved by each system module under different interaction conditions and evaluate the whole system on hand of a scenario for elderly care assistance.

Multi-agent Based Context Management in AmI Applications

Ambient Intelligence (AmI) is experiencing an increasing development of applications. Flexibility and genericity in the deployment and provisioning of context management solutions are key issues to be able to tackle with the large variety of domains of these context-aware applications. Existing proposals of Context Management Middleware (CMM) are still lacking such generic and flexible capabilities. To respond to these challenges, we propose CONSERT, a CMM, based on techniques and principles from the Semantic Web and Multi-Agent Systems domains. In this paper we focus on showing how the multi-agent architecture of this CMM provides the necessary flexibility to deploy different kinds of context provisioning patterns to address different AmI applications. We showcase the usage of our solution with a scenario from the domain of smart university life management.

Towards an Agent enabled Context Management Middleware

Industry involvement in the Ambient Intelligence (AmI) domain and development of internet-connected sensor networks drive research into generic context management middleware (CMM) solutions. However, no current CMM solution seems capable of addressing the diversity of AmI applications and the entire set of functional and non-functional requirements for context management. In this work we propose a context management middleware based on the multi-agent paradigm, supporting a flexible and open management of context.