Context awareness

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

Context Awareness in Mobile Computing Environments

Abstract: In this article, we report software architectures for context awareness in mobile computing environments, sensor centric systems and discuss context modeling issues. Defining an architecture for supporting context-aware applications for mobile devices explicitly implies a scalable description of how to represent contextual information and which are the abstraction models capable of handling such information. Using sensors to retrieve contextual information (e.g., user location) leads to a sensor network scheme that provides services to the applications level. Operations for capturing, collating, storing, and disseminating contextual information at the lowest level and aggregating it into increasingly more abstract models qualify the context-aware systems. In this article, we introduce context aware systems in mobile computing environments, review the basic mechanisms underlying the operation of such systems, and discuss notable work and important architectures in the area.

Context-aware middleware for pervasive elderly homecare

Abstract: The growing aging population faces a number of challenges, including rising medical cost, inadequate number of medical doctors and healthcare professionals, as well as higher incidence of misdiagnosis. There is an increasing demand for a better healthcare support for the elderly and one promising solution is the development of a context-aware middleware infrastructure for pervasive health/wellness-care. This allows the accurate and timely delivery of health/medical information among the patients, doctors and healthcare workers through a widespread deployment of wireless sensor networks and mobile devices. In this paper, we present our design and implementation of such a context-aware middleware for pervasive homecare (CAMPH). The middleware offers several key-enabling system services that consist of P2P-based context query processing, context reasoning for activity recognition and context-aware service management. It can be used to support the development and deployment of various homecare services for the elderly such as patient monitoring, location-based emergency response, anomalous daily activity detection, pervasive access to medical data and social networking. We have developed a prototype of the middleware and demonstrated the concept of providing a continuing-care to an elderly with the collaborative interactions spanning multiple physical spaces: person, home, office and clinic. The results of the prototype show that our middleware approach achieves good efficiency of context query processing and good accuracy of activity recognition.

Context awareness for dynamic service-oriented product lines

Abstract: This paper presents a Context-Aware Dynamic Software Product Line (DSPL) for building service oriented applications and adapting them at runtime in accordance with their using context. This DSPL, named CAPucine for Context-Aware Service-Oriented Product Line is based on two different processes for product derivation. The first process uses assets that represent features of the product family. The assets, represented as models, get composed and transformed in order to generate the product. The second process relates to dynamic adaptation. This process introduces context-aware assets that operate at runtime. These context-aware assets contain three kinds of data: the context when the assets can be modified, the place where the assets must be applied and the change that must be performed. The realization of these context-aware assets combines two runtime platforms. On the one hand,COSMOS is a context-aware framework connected to the environment by the use of sensors. On the other hand FraSCAti is a Service Component Architecture (SCA) platform with dynamic properties that enables to bind and unbind components at runtime. CAPucine allows designing and processing context-aware applications based on an SCA platform which is dynamic, introspectable, and reconfigurable in accordance with the context environment.

TagSense: a smartphone-based approach to automatic image tagging

Abstract: Mobile phones are becoming the convergent platform for personal sensing, computing, and communication. This paper attempts to exploit this convergence towards the problem of automatic image tagging. We envision TagSense, a mobile phone based collaborative system that senses the people, activity, and context in a picture, and merges them carefully to create tags on-the-fly. The main challenge pertains to discriminating phone users that are in the picture from those that are not. We deploy a prototype of TagSense on 8 Android phones, and demonstrate its effectiveness through 200 pictures, taken in various social settings. While research in face recognition continues to improve image tagging, TagSense is an attempt to embrace additional dimensions of sensing towards this end goal. Performance comparison with Apple iPhoto and Google Picasa shows that such an out-of-band approach is valuable, especially with increasing device density and greater sophistication in sensing/learning algorithms.

Real-time analysis of data from many sensors with neural networks

Abstract: Much research has been conducted that uses sensor-based modules with dedicated software to automatically distinguish the user's situation or context. The best results were obtained when powerful sensors (such as cameras or GPS systems) and/or sensor-specific algorithms (like sound analysis) were applied A somewhat new approach is to replace the one smart sensor by many simple sensors. We argue that neural networks are ideal algorithms to analyze the data coming from these sensors and describe how we came to one specific algorithm that gives good results, by giving an overview of several requirements. Finally, wearable implementations are given to show the feasibility and benefits of this approach and its implications.