Context awareness

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

Middleware for Social Networking on Mobile Devices

Abstract: Two significant but independent trends in recent years are the popularity of social networking applications and the adoption of mobile devices, notably smart phones. The current generation of smart phones are pocket computers that, compared to their predecessors, are relatively well resourced. Existing support for social networking tends to take the form of Web-based applications that are accessed from the desktop. Our interests are in leveraging today's smart phone as a platform for hosting social networking applications. To this end we have developed a middleware solution that includes i) communication and service hosting infrastructure and ii) a context-aware framework. The infrastructure resolves challenges encountered when hosting services on 3G networks offered by mobile network operators. In addition, the middleware includes mechanisms to promote application scalability, availability, and responsiveness -- and generally conserves smart phone resources such as power supply and network bandwidth. The context-aware framework is extensible and allows an open-ended set of context items and context sources to be managed. This framework allows context data, such as user location and activity, to be propagated around a user community. Performance experiments have validated the middleware, demonstrating that it can satisfy the requirements for scalability, availability, and responsiveness. A small user study has confirmed interest in the use of mobile devices to deliver social networking services; the study has also raised concerns -- in particular security and privacy -- relating to the platform.

Sensor-Based Context-Awareness for Situated Computing

Abstract: It can be argued that pervasive access to information and services becomes more valuable when they are related and adapted to the real world situations of their use. We discuss sensor-based approaches to awareness of such situations based on experience from two projects, one investigating context-awareness as add-on technology for mobile devices, and the other exploring the use of everyday things as context suppliers.

A Novel Smart Home Application Using an Internet of Things Middleware

Abstract: The aim of this paper is to describe the development of a novel smart home application based on an architecture and middleware of the Internet of Things. It integrates temperature and light sensors and the residence interacts directly with them by means of the middleware, controls the brightness of the lights, turns on and off the air and entertainment systems of house. The proposed arquitecture provides an intuitive user interface, security, environment self-adaptation and user context awareness.

Usability Assessment of a Context-Aware and Personality-Based Mobile Recommender System

Abstract: In this paper we present STS (South Tyrol Suggests), a context-aware mobile recommender system for places of interest (POIs) that integrates some innovative components, including: a personality questionnaire, i.e., a brief and entertaining questionnaire used by the system to learn users’ personality; an active learning module that acquires ratings-in-context for POIs that users are likely to have experienced; and a matrix factorization based recommendation module that leverages the personality information and several contextual factors in order to generate more relevant recommendations.

Wellness/exercise management method and system by wellness/exercise mode based on context-awareness platform on smartphone

Abstract: A device, method and system provide a wellness management process and/or an exercise management process for use with a smartphone or other mobile computing device. Various data about the user is obtained and used for determining and recommending an action or exercise to the user to improve the user's wellness/physique/health. The action determined can be based on: (1) current biometric and/or motion data about the user (from the sensors), and (2) current physical condition(s), such as health/medical information or condition about the user (from the user's personal information, e.g., health library or programmed into the smartphone). Specific information about the user is taken into consideration when recommending user action or exercise, such as the user's specific physical, health or medical conditions.