236 research outputs found

    Semantic Brokering of Multimedia Contents for Smart Delivery of Ubiquitous Services in Pervasive Environments

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    With the proliferation of modern mobile devices having the capability to interact each other and with the environment in a transparent manner, there is an increase in the development of those applications that are specifically designed for pervasive and ubiquitous environments. Those applications are able to provide a service of interest for the user that depends on context information, such as the user's position, his preferences, the capability of the device and its available resources. Services have to respond in a rational way in many different situations choosing the actions with the best expected result by the user, so making environment not only more connected and efficient, but smarter. Here we present a semantic framework that provides the technology for the development of intelligent, context aware services and their delivery in pervasive and ubiquitous environments

    Recommendation & mobile systems - a state of the art for tourism

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    Recommendation systems have been growing in number over the last fifteen years. To evolve and adapt to the demands of the actual society, many paradigms emerged giving birth to even more paradigms and hybrid approaches. These approaches contain strengths and weaknesses that need to be evaluated according to the knowledge area in which the system is going to be implemented. Mobile devices have also been under an incredible growth rate in every business area, and there are already lots of mobile based systems to assist tourists. This explosive growth gave birth to different mobile applications, each having their own advantages and disadvantages. Since recommendation and mobile systems might as well be integrated, this work intends to present the current state of the art in tourism mobile and recommendation systems, as well as to state their advantages and disadvantages

    Second Workshop on Modelling of Objects, Components and Agents

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    This report contains the proceedings of the workshop Modelling of Objects, Components, and Agents (MOCA'02), August 26-27, 2002.The workshop is organized by the 'Coloured Petri Net' Group at the University of Aarhus, Denmark and the 'Theoretical Foundations of Computer Science' Group at the University of Hamburg, Germany. The homepage of the workshop is: http://www.daimi.au.dk/CPnets/workshop02

    TOWARD A PLATFORM FOR MULTI-LAYERED MULTI-AGENT SITUATED SYSTEM (MMASS)-BASED SIMULATIONS: FOCUSING ON FIELD DIFFUSION

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    The paper introduces some issues and related solutions adopted in order to realize the MMASS platform. This is a framework to specify and execute simulation applications based on the multilayered multi-agent situated system model (MMASS). MMASS is a model for multi-agent systems (MAS) situated in an environment whose structure is explicitly defined. The behavior and interaction models of MMASS agents are strongly related to the spatial structure of their environment. The MMASS model is the result of a long-term research that has its roots and motivations on application domains and problems that require spatial features to be considered. Our experiences with these problems have concerned the design of domain models and their implementations, according to the MAS approach for simulation purposes. This activity has revealed that currently available tools do not support the management of spatial features of agent environment and interaction mechanisms defined by the MMASS model and thus they are not suitable for our purposes. The paper focuses on the MMASS platform that aims to support the specification and development of applications (mainly, simulations) based on MMASS. Design issues and related solutions that have been adopted in order to manage those aspects that characterize the MMASS model will be shown. After a description of the conceptual model that underlies the MMASS platform and its general architecture, we will overview how the platform supports the specification of agent structured environment, behavior and interaction, and how it supports the execution of agent actions and interactions. Then we will describe issues and adopted solutions (both algorithmic and implementative ones) to manage at-a-distance interaction among MMASS agents

    Ubiquitous Robotics System for Knowledge-based Auto-configuration System for Service Delivery within Smart Home Environments

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    The future smart home will be enhanced and driven by the recent advance of the Internet of Things (IoT), which advocates the integration of computational devices within an Internet architecture on a global scale [1, 2]. In the IoT paradigm, the smart home will be developed by interconnecting a plethora of smart objects both inside and outside the home environment [3-5]. The recent take-up of these connected devices within home environments is slowly and surely transforming traditional home living environments. Such connected and integrated home environments lead to the concept of the smart home, which has attracted significant research efforts to enhance the functionality of home environments with a wide range of novel services. The wide availability of services and devices within contemporary smart home environments make their management a challenging and rewarding task. The trend whereby the development of smart home services is decoupled from that of smart home devices increases the complexity of this task. As such, it is desirable that smart home services are developed and deployed independently, rather than pre-bundled with specific devices, although it must be recognised that this is not always practical. Moreover, systems need to facilitate the deployment process and cope with any changes in the target environment after deployment. Maintaining complex smart home systems throughout their lifecycle entails considerable resources and effort. These challenges have stimulated the need for dynamic auto-configurable services amongst such distributed systems. Although significant research has been directed towards achieving auto-configuration, none of the existing solutions is sufficient to achieve auto-configuration within smart home environments. All such solutions are considered incomplete, as they lack the ability to meet all smart home requirements efficiently. These requirements include the ability to adapt flexibly to new and dynamic home environments without direct user intervention. Fulfilling these requirements would enhance the performance of smart home systems and help to address cost-effectiveness, considering the financial implications of the manual configuration of smart home environments. Current configuration approaches fail to meet one or more of the requirements of smart homes. If one of these approaches meets the flexibility criterion, the configuration is either not executed online without affecting the system or requires direct user intervention. In other words, there is no adequate solution to allow smart home systems to adapt dynamically to changing circumstances, hence to enable the correct interconnections among its components without direct user intervention and the interruption of the whole system. Therefore, it is necessary to develop an efficient, adaptive, agile and flexible system that adapts dynamically to each new requirement of the smart home environment. This research aims to devise methods to automate the activities associated with customised service delivery for dynamic home environments by exploiting recent advances in the field of ubiquitous robotics and Semantic Web technologies. It introduces a novel approach called the Knowledge-based Auto-configuration Software Robot (Sobot) for Smart Home Environments, which utilises the Sobot to achieve auto-configuration of the system. The research work was conducted under the Distributed Integrated Care Services and Systems (iCARE) project, which was designed to accomplish and deliver integrated distributed ecosystems with a homecare focus. The auto-configuration Sobot which is the focus of this thesis is a key component of the iCARE project. It will become one of the key enabling technologies for generic smart home environments. It has a profound impact on designing and implementing a high quality system. Its main role is to generate a feasible configuration that meets the given requirements using the knowledgebase of the smart home environment as a core component. The knowledgebase plays a pivotal role in helping the Sobot to automatically select the most appropriate resources in a given context-aware system via semantic searching and matching. Ontology as a technique of knowledgebase representation generally helps to design and develop a specific domain. It is also a key technology for the Semantic Web, which enables a common understanding amongst software agents and people, clarifies the domain assumptions and facilitates the reuse and analysis of its knowledge. The main advantages of the Sobot over traditional applications is its awareness of the changing digital and physical environments and its ability to interpret these changes, extract the relevant contextual data and merge any new information or knowledge. The Sobot is capable of creating new or alternative feasible configurations to meet the system’s goal by utilising inferred facts based on the smart home ontological model, so that the system can adapt to the changed environment. Furthermore, the Sobot has the capability to execute the generated reconfiguration plan without interrupting the running of the system. A proof-of-concept testbed has been designed and implemented. The case studies carried out have shown the potential of the proposed approach to achieve flexible and reliable auto-configuration of the smart home system, with promising directions for future research

    4th International Symposium on Ambient Intelligence (ISAmI 2013)

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    Ambient Intelligence (AmI) is a recent paradigm emerging from Artificial Intelligence (AI), where computers are used as proactive tools assisting people with their day-to-day activities, making everyone’s life more comfortable. Another main concern of AmI originates from the human computer interaction domain and focuses on offering ways to interact with systems in a more natural way by means user friendly interfaces. This field is evolving quickly as can be witnessed by the emerging natural language and gesture based types of interaction. The inclusion of computational power and communication technologies in everyday objects is growing and their embedding into our environments should be as invisible as possible. In order for AmI to be successful, human interaction with computing power and embedded systems in the surroundings should be smooth and happen without people actually noticing it. The only awareness people should have arises from AmI: more safety, comfort and wellbeing, emerging in a natural and inherent way. ISAmI is the International Symposium on Ambient Intelligence and aiming to bring together researchers from various disciplines that constitute the scientific field of Ambient Intelligence to present and discuss the latest results, new ideas, projects and lessons learned, namely in terms of software and applications, and aims to bring together researchers from various disciplines that are interested in all aspects of this area

    Micro-intelligence for the IoT: logic-based models and technologies

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    Computing is moving towards pervasive, ubiquitous environments in which devices, software agents and services are all expected to seamlessly integrate and cooperate in support of human objectives. An important next step for pervasive computing is the integration of intelligent agents that employ knowledge and reasoning to understand the local context and share this information in support of intelligent applications and interfaces. Such scenarios, characterised by "computation everywhere around us", require on the one hand software components with intelligent behaviour in terms of objectives and context, and on the other their integration so as to produce social intelligence. Logic Programming (LP) has been recognised as a natural paradigm for addressing the needs of distributed intelligence. Yet, the development of novel architectures, in particular in the context Internet of Things (IoT), and the emergence of new domains and potential applications, are creating new research opportunities where LP could be exploited, when suitably coupled with agent technologies and methods so that it can fully develop its potential in the new context. In particular, the LP and its extensions can act as micro-intelligence sources for the IoT world, both at the individual and the social level, provided that they are reconsidered in a renewed architectural vision. Such micro-intelligence sources could deal with the local knowledge of the devices taking into account the domain specificity of each environment. The goal of this thesis is to re-contextualise LP and its extensions in these new domains as a source of micro-intelligence for the IoT world, envisioning a large number of small computational units distributed and situated in the environment, thus promoting the local exploitation of symbolic languages with inference capabilities. The topic is explored in depth and the effectiveness of novel LP models and architectures -and of the corresponding technology- expressing the concept of micro-intelligence is tested

    Multi-Agent Approach to Modeling and Implementing Fault-Tolerance in Reactive Autonomic Systems

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    Recently, autonomic computing has been proposed as a promising solution for software complexity in IT industry. As an autonomic approach, the Reactive Autonomic Systems Framework (RASF) proposes a formal modeling based on mathematical category theory, which addresses the self-* properties of reactive autonomic systems in a more abstract level. This thesis is about the specification and implementation of the reactive autonomic systems (RAS) through multi-agent approach by laying emphasis on the fault-tolerance property of RAS. Furthermore, this thesis proposes a model-driven approach to transform the RAS model to agent templates in multi-agent model using Extensible Stylesheet Language Transformation (XSLT). The multi-agent approach in this research is implemented by Jadex, a high-level Java-based agent programming language. The intelligent agents are created in Jadex based on the Belief-Desire-Intension (BDI) agent architecture. The approach is illustrated on a case study

    Service architecting and dynamic composition in pervasive smart ecosystems for the Internet of things based on sensor network technology

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    Why pervasive awareness and Ambient Intelligence are perceived by a great part of the academia and industry as a massive revolution in the short-term? In our best knowledge, a cornerstone of this thought is based on the fact that the ultimate nature of the smart environment paradigm is not in the technology itself, but on a people-centered approach. Perhaps, is in this apparently simple conception where precisely lies the boldness of this promising vision, which has been consolidated in recent years with the emerging proliferation of mobile, personal, portable, wearable and sensory computing: to reach everyone and everywhere. On the one hand, it touches our daily lives in a close manner, minimizing the required attention from the users, anticipating to their needs with the main intention of redefining our idea of Quality of Experience. On the other hand, this new wave impacts everywhere at both global and personal scales allowing expanded connectivity between devices and smart objects, in a dynamic and ubiquitous manner, as a natural extension of the physical world around us. According to the above, this doctoral dissertation focuses on contributing to the integration of software and networking engineering advances in the field of pervasive smart spaces and environment using sensor networks. This is founded on the convergence of some information technology and computer science paradigms, such as service and agent orientation, semantic technologies and knowledge management in the framework of pervasive computing and the Internet of Things. To this end, the nSOM (nano Service-Oriented Middleware) and nSOL (nano Semantics-Oriented Language) approaches are presented. Firstly, the nSOM proposal defines a service-oriented platform for the implementation, deployment and exposure of agent-based in-network services to the Internet cloud on heterogeneous sensor devices. Secondly, the nSOL solution enables an abstraction for supporting ubiquitous service composition based on semantic knowledge management. The integration of both contributions leads to the formal modelling and practical development of adaptive virtual sensor services for pervasive Ambient Intelligence ecosystems. This work includes also the related performance characterization of the resulting prototype according to several metrics such as code size, volatile memory footprint, CPU overhead, service time delay and battery lifetime. Main foundations and outcomes presented in this essay are contextualized in the following European Research Projects: μSWN (FP6 code: IST-034642), DiYSE (ITEA2 code: 08005) and LifeWear (ITEA2 code: 09026). --------------------¿Por qué la sensibilidad ubicua y la inteligencia ambiental son percibidas por una gran parte de las comunidades académica e industrial como una revolución masiva en el corto plazo? En nuestra opinión, una piedra angular de este pensamiento es el hecho de que la naturaleza última del paradigma de entornos inteligentes no reside en la tecnología en sí misma, sino en una aproximación centrada en las personas. Y es quizá en esta aparente simple concepción donde se halla precisamente el atrevimiento de esta prometedora visión, consolidada en los últimos años con la emergente proliferación de la computación móvil, personal, portable, llevable y sensorial: llegar a todos y a todas partes. Por un lado, esta alcanza nuestras vidas de una manera cercana, minimizando la atención requerida por los usuarios, anticipándose a sus necesidades con el objetivo de redefinir nuestra idea de calidad de experiencia. Por otro lado, esta impacta en todas partes tanto a escala global como personal, con una conectividad expandida entre dispositivos y objetos inteligentes, de un modo ubicuo y dinámico, como una extensión natural del mundo que nos rodea. Conforme a lo anterior, esta tesis doctoral se centra en contribuir en la integración de los avances de ingeniería de redes y software en el ámbito de los espacios y entornos inteligentes ubicuos basados en redes de sensores. Esto se fundamenta en la convergencia de diversos paradigmas de las tecnologías de la información y ciencia de la computación, tales como orientación a servicios y agentes, tecnologías semánticas y de gestión del conocimiento en el contento de la computación ubicua en la Internet de las Cosas. Para este fin, se presentan las aproximaciones nSOM (nano Service-Oriented Middleware) y nSOL (nano Semantics-Oriented Language). En primer lugar, nSOM define una plataforma orientada a servicios para la implementación, despliegue y exposición a la nube de servicios basados en agentes e implementados en red sobre dispositivos heterogéneos de sensores. En segundo lugar, nSOL habilita una abstracción para proporcionar composición ubicua de servicios basada en gestión semántica del conocimiento. La integración de ambas contribuciones conduce a un modelado formal y de implementación práctica de servicios de sensor virtual adaptativos para ecosistemas de inteligencia ambiental. Este trabajo incluye la caracterización del rendimiento del prototipo resultante, basándonos para ello en métricas tales como tamaño de código, tamaño de memoria volátil, sobrecarga de procesamiento, retardo en tiempo de servicio y autonomía de baterías. Los principales fundamentos y resultados discutidos en este ensayo están contextualizados en los siguientes Proyectos de Investigación Europeos: μSWN (FP6 código: IST-034642), DiYSE (ITEA2 código: 08005) y LifeWear (ITEA2 código: 09026).Presidente: Juan Ramón Velasco Pérez; Vocal: Juan Carlos Dueñas; Secretario: Mario Muñoz Organer
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