6,228 research outputs found
Using ontologies for modeling context-aware services platforms
This paper discusses the suitability of using ontologies for modeling context-aware services platforms. It addresses the directions of research we are following in the WASP (Web Architectures for Services Platforms) project. For this purpose a simple scenario is considered
Position paper on realizing smart products: challenges for Semantic Web technologies
In the rapidly developing space of novel technologies that combine sensing and semantic technologies, research on smart products has the potential of establishing a research field in itself. In this paper, we synthesize existing work in this area in order to define and characterize smart products. We then reflect on a set of challenges that semantic technologies are likely to face in this domain. Finally, in order to initiate discussion in the workshop, we sketch an initial comparison of smart products and semantic sensor networks from the perspective of knowledge
technologies
Ami-deu : un cadre sémantique pour des applications adaptables dans des environnements intelligents
Cette thĂšse vise Ă Ă©tendre lâutilisation de l'Internet des objets (IdO) en facilitant le dĂ©veloppement dâapplications par des personnes non experts en dĂ©veloppement logiciel. La thĂšse propose une nouvelle approche pour augmenter la sĂ©mantique des applications dâIdO et lâimplication des experts du domaine dans le dĂ©veloppement dâapplications sensibles au contexte. Notre approche permet de gĂ©rer le contexte changeant de lâenvironnement et de gĂ©nĂ©rer des applications qui sâexĂ©cutent dans plusieurs environnements intelligents pour fournir des actions requises dans divers contextes. Notre approche est mise en Ćuvre dans un cadriciel (AmI-DEU) qui inclut les composants pour le dĂ©veloppement dâapplications IdO. AmI-DEU intĂšgre les services dâenvironnement, favorise lâinteraction de lâutilisateur et fournit les moyens de reprĂ©senter le domaine dâapplication, le profil de lâutilisateur et les intentions de lâutilisateur. Le cadriciel permet la dĂ©finition dâapplications IoT avec une intention dâactivitĂ© autodĂ©crite qui contient les connaissances requises pour rĂ©aliser lâactivitĂ©. Ensuite, le cadriciel gĂ©nĂšre Intention as a Context (IaaC), qui comprend une intention dâactivitĂ© autodĂ©crite avec des connaissances colligĂ©es Ă Ă©valuer pour une meilleure adaptation dans des environnements intelligents.
La sĂ©mantique de lâAmI-DEU est basĂ©e sur celle du ContextAA (Context-Aware Agents) â une plateforme pour fournir une connaissance du contexte dans plusieurs environnements. Le cadriciel effectue une compilation des connaissances par des rĂšgles et l'appariement sĂ©mantique pour produire des applications IdO autonomes capables de sâexĂ©cuter en ContextAA. AmI- DEU inclut Ă©galement un outil de dĂ©veloppement visuel pour le dĂ©veloppement et le dĂ©ploiement rapide d'applications sur ContextAA. L'interface graphique dâAmI-DEU adopte la mĂ©taphore du flux avec des aides visuelles pour simplifier le dĂ©veloppement d'applications en permettant des dĂ©finitions de rĂšgles Ă©tape par Ă©tape. Dans le cadre de lâexpĂ©rimentation, AmI-DEU comprend un banc dâessai pour le dĂ©veloppement dâapplications IdO. Les rĂ©sultats expĂ©rimentaux montrent une optimisation sĂ©mantique potentielle des ressources pour les applications IoT dynamiques dans les maisons intelligentes et les villes intelligentes.
Notre approche favorise l'adoption de la technologie pour amĂ©liorer le bienĂȘtre et la qualitĂ© de vie des personnes. Cette thĂšse se termine par des orientations de recherche que le cadriciel AmI-DEU dĂ©voile pour rĂ©aliser des environnements intelligents omniprĂ©sents fournissant des adaptations appropriĂ©es pour soutenir les intentions des personnes.Abstract: This thesis aims at expanding the use of the Internet of Things (IoT) by facilitating the development of applications by people who are not experts in software development. The thesis proposes a new approach to augment IoT applicationsâ semantics and domain expert involvement in context-aware application development. Our approach enables us to manage the changing environment context and generate applications that run in multiple smart environments to provide required actions in diverse settings. Our approach is implemented in a framework (AmI-DEU) that includes the components for IoT application development. AmI- DEU integrates environment services, promotes end-user interaction, and provides the means to represent the application domain, end-user profile, and end-user intentions. The framework enables the definition of IoT applications with a self-described activity intention that contains the required knowledge to achieve the activity. Then, the framework generates Intention as a Context (IaaC), which includes a self-described activity intention with compiled knowledge to be assessed for augmented adaptations in smart environments. AmI-DEU framework semantics adopts ContextAA (Context-Aware Agents) â a platform to provide context-awareness in multiple environments. The framework performs a knowledge compilation by rules and semantic matching to produce autonomic IoT applications to run in ContextAA. AmI-DEU also includes a visual tool for quick application development and deployment to ContextAA. The AmI-DEU GUI adopts the flow metaphor with visual aids to simplify developing applications by allowing step-by-step rule definitions. As part of the experimentation, AmI-DEU includes a testbed for IoT application development. Experimental results show a potential semantic optimization for dynamic IoT applications in smart homes and smart cities. Our approach promotes technology adoption to improve peopleâs well-being and quality of life. This thesis concludes with research directions that the AmI-DEU framework uncovers to achieve pervasive smart environments providing suitable adaptations to support peopleâs intentions
Context Aware Computing for The Internet of Things: A Survey
As we are moving towards the Internet of Things (IoT), the number of sensors
deployed around the world is growing at a rapid pace. Market research has shown
a significant growth of sensor deployments over the past decade and has
predicted a significant increment of the growth rate in the future. These
sensors continuously generate enormous amounts of data. However, in order to
add value to raw sensor data we need to understand it. Collection, modelling,
reasoning, and distribution of context in relation to sensor data plays
critical role in this challenge. Context-aware computing has proven to be
successful in understanding sensor data. In this paper, we survey context
awareness from an IoT perspective. We present the necessary background by
introducing the IoT paradigm and context-aware fundamentals at the beginning.
Then we provide an in-depth analysis of context life cycle. We evaluate a
subset of projects (50) which represent the majority of research and commercial
solutions proposed in the field of context-aware computing conducted over the
last decade (2001-2011) based on our own taxonomy. Finally, based on our
evaluation, we highlight the lessons to be learnt from the past and some
possible directions for future research. The survey addresses a broad range of
techniques, methods, models, functionalities, systems, applications, and
middleware solutions related to context awareness and IoT. Our goal is not only
to analyse, compare and consolidate past research work but also to appreciate
their findings and discuss their applicability towards the IoT.Comment: IEEE Communications Surveys & Tutorials Journal, 201
Internet of Things Strategic Research Roadmap
Internet of Things (IoT) is an integrated part of Future Internet including existing and evolving Internet and network developments and could be conceptually defined as a dynamic global network infrastructure with self configuring capabilities based on standard and interoperable communication protocols where physical and virtual âthingsâ have identities, physical attributes, and virtual personalities, use intelligent interfaces, and are seamlessly integrated into the information network
Integrating building and urban semantics to empower smart water solutions
Current urban water research involves intelligent sensing, systems integration, proactive users and data-driven management through advanced analytics. The convergence of building information modeling with the smart water field provides an opportunity to transcend existing operational barriers. Such research would pave the way for demand-side management, active consumers, and demand-optimized networks, through interoperability and a system of systems approach. This paper presents a semantic knowledge management service and domain ontology which support a novel cloud-edge solution, by unifying domestic socio-technical water systems with clean and waste networks at an urban scale, to deliver value-added services for consumers and network operators. The web service integrates state of the art sensing, data analytics and middleware components. We propose an ontology for the domain which describes smart homes, smart metering, telemetry, and geographic information systems, alongside social concepts. This integrates previously isolated systems as well as supply and demand-side interventions, to improve system performance. A use case of demand-optimized management is introduced, and smart home application interoperability is demonstrated, before the performance of the semantic web service is presented and compared to alternatives. Our findings suggest that semantic web technologies and IoT can merge to bring together large data models with dynamic data streams, to support powerful applications in the operational phase of built environment systems
A Semantic Agent Framework for Cyber-Physical Systems
The development of accurate models for cyber-physical systems (CPSs) is hampered by the complexity of these systems, fundamental differences in the operation of cyber and physical components, and significant interdependencies among these components. Agent-based modeling shows promise in overcoming these challenges, due to the flexibility of software agents as autonomous and intelligent decision-making components. Semantic agent systems are even more capable, as the structure they provide facilitates the extraction of meaningful content from the data provided to the software agents. In this book chapter, we present a multi-agent model for a CPS, where the semantic capabilities are underpinned by sensor networks that provide information about the physical operation to the cyber infrastructure. As a specific example of the semantic interpretation of raw sensor data streams, we present a failure detection ontology for an intelligent water distribution network as a model CPS. The ontology represents physical entities in the CPS, as well as the information extraction, analysis and processing that takes place in relation to these entities. The chapter concludes with introduction of a semantic agent framework for CPS, and presentation of a sample implementation of the framework using C++
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