Context awareness

About: Context awareness is a research topic. Over the lifetime, 5790 publications have been published within this topic receiving 119944 citations.

TRAcME: Temporal Activity Recognition Using Mobile Phone Data

Abstract: The aim of human activity recognition is to identify what a user or a group of users are doing at a given point in time, for example travelling or working. Activity recognition plays an important role in mobile and ubiquitous computing both as a goal in itself and as an intermediate task in the design of advanced applications. Virtually all existing activity recognition systems for mobile phones base their predictions on location cues. This approach forces the user to disclose personal information such as her home or work area. In this paper, we present a novel activity recognition system called TRAcME (temporal recognition of activities for mobile environments) which recognises generic human activities from large windows of context, Allenpsilas temporal relations and anonymous landmarks. Unlike existing systems, TRAcME handles simultaneous activities and outputs activities which are consistent with each other at the scale of a userpsilas day.

Towards model driven design of service-based context-aware applications

Abstract: Context-aware adaptation is an important feature for pervasive computing applications. In our approach, we intend to support the viewpoint of context-aware adaptation as a crosscutting concern with respect to the core "business logic" of an application. In this way, the design of the application core can be decoupled from the design of the adaptation logic. This facilitate the plugging of different adaptation strategies within the same basic application, tailoring it for different contexts. To this end, we leverage ideas from the domains of model-driven development and aspect-oriented design. We assume that the applications to be adapted are designed according to the service-oriented paradigm. Hence, our adaptation mechanisms only assume the knowledge of information accessible in this kind of applications.

Modeling Context-Aware Behavior by Interpreted ECA Rules

Abstract: The software architecture of distributed systems is about to change due to new requirements of modern mobile devices. New network techniques, like ad-hoc radio communication or peer-to-peer networks allow mobile devices to sense their environment and to interact with other devices dynamically. This paper presents a cutting-edge way to describe objects and their interaction, also called context, as well as the possibility to configure such interaction scenarios. A lookup mechanism collects information about the environment and a role-based classification is responsible for identifying possible interaction partners. Furthermore the configuration of scenario behavior with context rules is introduced. Finally a comparison with already existing context frameworks is given and a practical emergency scenario configuration is shown.

Using Developer Activity Data to Enhance Awareness during Collaborative Software Development

Abstract: Software development is a global activity unconstrained by the bounds of time and space. A major effect of this increasing scale and distribution is that the shared understanding that developers previously acquired by formal and informal face-to-face meetings is difficult to obtain. This paper proposes a shared awareness model that uses information gathered automatically from developer IDE interactions to make explicit orderings of tasks, artefacts and developers that are relevant to particular work contexts in collaborative, and potentially distributed, software development projects. The research findings suggest that such a model can be used to: identify entities (developers, tasks, artefacts) most associated with a particular work context in a software development project; identify relevance relationships amongst tasks, developers and artefacts e.g. which developers and artefacts are currently most relevant to a task or which developers have contributed to a task over time; and, can be used to identify potential bottlenecks in a project through a `social graph' view. Furthermore, this awareness information is captured and provided as developers work in different locations and at different times.