Topic
Context awareness
About: Context awareness is a research topic. Over the lifetime, 5790 publications have been published within this topic receiving 119944 citations.
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23 Jun 2008
TL;DR: Gently is born as the combination of the Context-aware Adaptive Routing (CAR) and the socially aware LABEL protocol which combines techniques of context awareness and social knowledge to concretely solve issues related to opportunistic forwarding.
Abstract: Developing protocols and applications for opportunistic networking can represent a daunting task given the many aspects that must be taken into consideration, such as intermittent connectivity, smart choice among multiple interfaces and intelligent data storage. The implementation of these protocols can be based on generic layer-less communication frameworks that provide programming abstractions for the extraction and analysis of social, colocation and mobility information and allows data exchange by means of heterogeneous devices. We propose Gently, a novel fully implemented solution which combines techniques of context awareness and social knowledge to concretely solve issues related to opportunistic forwarding. More precisely, Gently is born as the combination of the Context-aware Adaptive Routing (CAR) and the socially aware LABEL protocol. We discuss the implementation of our solution on top of the layer-less Haggle framework presenting the key design choices and the lessons learnt.
29 citations
21 Jun 2011
TL;DR: HEP is a system that recommends communication services to the caller based on the callee’s context, which is the usage history of the different communication services as well as the users’ calendars.
Abstract: Context aware systems are a promising approach to facilitate daily-life activities. Concerning communication services, business users may be sometimes overloaded with work so that they become temporally unable to handle incoming communications. After having surveyed the challenges to build context-aware systems, we introduce here HEP, a system that recommends communication services to the caller based on the callee’s context. HEP’s main context source is the usage history of the different communication services as well as the users’ calendars. It has been prototyped and tested at Orange Labs.
29 citations
TL;DR: A framework that facilitates the development of Context-Aware Recommendation Systems for mobile environments and an experimental evaluation of the proposed system are described.
29 citations
TL;DR: The proposed method designs a system that can distribute and manage situational information in mobile nodes using mobile devices in distributed and ubiquitous environments and share the service content between interactive middleware through publication.
Abstract: Due to the development of IT convergence, a wide variety of information is being produced and distributed rapidly in digital form. Lifelog based context awareness is a technology that provides a service automatically based on perceived situational information in ubiquitous environments. To offer customized services to users, the technology of acquiring lifelog based context information in real time is the most important consideration. We propose the interactive middleware architecture for lifelog based context awareness in distributed and ubiquitous environments. Conventional middleware to support ubiquitous environments stores and manages the situational information and service content acquired by centralized storage or a DBMS. Centralized situational information and service content management may impede the autonomy of mobile nodes and the interoperation between different middle software. The proposed method designs a system that can distribute and manage situational information in mobile nodes using mobile devices in distributed and ubiquitous environments and share the service content between interactive middleware through publication. The application system designed in this study was used in a scenario providing situational perception based mobile service and proved to be useful.
29 citations
12 Apr 2010
TL;DR: The data analysis obtained from the interview study showed that participants had different individual mobile learning preferences, which can be used as a foundation for building successful personalized m- learning applications catered to learners’ individual m-learning needs.
Abstract: The purpose of this paper is to present the data analysis obtained from our interview study, which showed that participants had different individual mobile learning (hereafter, abbreviated as m-learning) preferences. The understanding of these preferences for different m-learning requirements can be used as a foundation for building successful personalized m-learning applications catered to learners’ individual m-learning needs. Participants’ dynamic m-learning preferences (including location of study, noise/distractions level in a location, and time of day) are described. We propose a context-aware personalized m-learning application based on these m-learning preferences. Six scenarios are given to illustrate the m-learning preferences of different learners. The system architecture consists of a learner profile, personalization mechanism and learning objects repository. An initial m-learning preferences questionnaire is used to obtain learners’ dynamic m-learning preferences. Current context values are retrieved from context-aware technologies. Appropriate learning objects are selected to learners based on their preferences and context values.
29 citations