750,328 research outputs found

    A Knowledge-Based Model For Context-Aware Smart Service Systems

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    The advancement of the Internet of Things, big data, and mobile computing leads to the need for smart services that enable the context awareness and the adaptability to their changing contexts. Today, designing a smart service system is a complex task due to the lack of an adequate model support in awareness and pervasive environment. In this paper, we present the concept of a context-aware smart service system and propose a knowledge model for context-aware smart service systems. The proposed model organizes the domain and context-aware knowledge into knowledge components based on the three levels of services: Services, Service system, and Network of service systems. The knowledge model for context-aware smart service systems integrates all the information and knowledge related to smart services, knowledge components, and context awareness that can play a key role for any framework, infrastructure, or applications deploying smart services. In order to demonstrate the approach, two case studies about chatbot as context-aware smart services for customer support are presented

    Towards a Context-Aware Knowledge Model for Smart Service Systems

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    The advancement of the Internet of things, big data, and mobile computing leads to the need for smart services that enable the context awareness and the adaptability to their changing contexts. Today, designing a smart service system is a complex task due to the lack of an adequate model support in awareness and pervasive environment. In this paper, we present a context-aware knowledge model for smart service systems that organizes the domain and context-aware knowledge into knowledge components based on the three levels of services: Services, Service system and Network of service systems. The context-aware knowledge model for smart service systems integrates all the information and knowledge related to smart services, knowledge components and context awareness that can play a key role for any framework, infrastructure, or applications deploying smart services. To demonstrate the approach, a case study about a chatbot as a smart service for customer support is presented

    Service-oriented Context-aware Framework

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    Location- and context-aware services are emerging technologies in mobile and desktop environments, however, most of them are difficult to use and do not seem to be beneficial enough. Our research focuses on designing and creating a service-oriented framework that helps location- and context-aware, client-service type application development and use. Location information is combined with other contexts such as the users' history, preferences and disabilities. The framework also handles the spatial model of the environment (e.g. map of a room or a building) as a context. The framework is built on a semantic backend where the ontologies are represented using the OWL description language. The use of ontologies enables the framework to run inference tasks and to easily adapt to new context types. The framework contains a compatibility layer for positioning devices, which hides the technical differences of positioning technologies and enables the combination of location data of various sources

    A conceptual framework for development of context-aware location-based services on smart-M3 platform

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    The paper presents a conceptual framework for development of context-aware location-based services. This framework provides relevant objects from the database to the user taking his/her preferences and context into account. It is based on the framework for context-aware preference queries, which provides a model of context- and preference-aware system based on the database, and the open source Smart-M3 platform, which allows to develop intelligent services using the smart space paradigm. The main components of the proposed framework include context-aware preference term generators that translate context information into context-aware preference terms, and a preference query executor that combines all preference terms and conducts their execution using PreferenceSQL JDBC driver. Evaluation of the proposed approach is made using the case study of context-aware restaurant data retrieval

    Elgar framework: context-aware service orchestration with data Petri net

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    The Internet of Things is composed of many heterogeneous devices and services. In general, the phase of orchestrating different devices in order to allow interoperability in different environment is difficult. This is because most IoT services are not reusable because of data interpretation and service interoperability problem. In this research, we embrace the concept of design once, deploy anywhere for IoT services. We proposed two major methods which are (i) modeling IoT services with data-aware service model and (ii) semantical approach using context ontology to support service orchestration. Finally, we showed that IoT services with various ontologies can be composed based on our orchestration method

    Business Model Development for a Mobile Context-aware Service

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    Mobile information services, preceded on tablet computers, smartphones or other mobile devices, are a significant source of information for people nowadays. By including context data, a new category of information services has been established. On the application side, a range of innovative services, providing the user with an added-value, could be observed in the previous years, boosted by the wide-spread adoption of smartphones in developed countries. For the application provider, the question how to configure the business model is crucial: several factors such as the service configuration, the revenue model and the configuration of the value creation network, which all can be seen as decisive factors for success or failure of a service. In this paper we present a context-aware service named \u27Digital Graffiti\u27 and describe the process of the business model development. As an outcome of this process, a specific business model, based on feasibility and future prospect, was chosen and further described

    Context awareness computing in smart spaces using stochastic analysis of sensor data

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    In building a smart space, it becomes more critical to develop a recognition system which enables to be aware of contexts, since the appropriate services can be provided under the accurate recognition. As services satisfying for desires of individual human residents are more demanding, the necessity for more sophisticated recognition algorithms is increasing. This paper proposes an approach to discover the current context by stochastically analyzing data obtained from sensors deployed in the smart space. The approach proceeds in two phases, which is to build context models and to find one context model matching the current state space, however we mainly focus on the phase building context models. Experimental validation supports the approach and approved validity

    Context-Aware Service Registry: Modeling and Implementation

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    Modern societies have become very dependent on information and services. Technology is adapting to the increasing demands of people and businesses. Context-Aware Systems are becoming ubiquitous. These systems comprise mechanisms to acquire knowledge about the surrounding environment and adapt its behaviour and service provision accordingly. Service oriented computing is the main stream software development methodology. In Service-oriented Applications (SOA), service providers publish the services created by them in service registries. These services are accessed by service requesters during discovery process. For large scale SOA, the registry structure and the type of quires that it can handle are central to efficient service discovery. Moreover, the role of context in determining services and affecting execution is central. This thesis investigates the structure of a context-aware service registry in which context-aware services are stored by service producers and retrieved by service requesters in different contexts. The thesis builds on an existing rich theoretical service model in which contract, functionality, and contexts are bundled together. The thesis investigates generic models and structures for context, context history, and context-aware registry. Also, it studies state of the arts database technologies to analyse its suitability for implementing a registry for rich services. Specifically, the thesis provides a thorough study of the structures, implementation, performance, limitations, and features of Key-Value, Documented Oriented, and Column Oriented databases while considering options for implementing a rich service registry. Database models of contexts and context-aware services are discussed and implemented. The relative performance of the models are discussed after evaluating the test results run on large data sets. Based upon test results a justification for the selected model is given
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