Context awareness

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

Situation Awareness Inferred From Posture Transition and Location: Derived From Smartphone and Smart home Sensors

Abstract: Situation awareness may be inferred from user context such as body posture transition and location data. Smartphones and smart homes incorporate sensors that can record this information without significant inconvenience to the user. Algorithms were developed to classify activity postures to infer current situations; and to measure user's physical location, in order to provide context that assists such interpretation. Location was detected using a subarea-mapping algorithm; activity classification was performed using a hierarchical algorithm with backward reasoning; and falls were detected using fused multiple contexts (current posture, posture transition, location, and heart rate) based on two models: “certain fall” and “possible fall.” The approaches were evaluated on nine volunteers using a smartphone, which provided accelerometer and orientation data, and a radio frequency identification network deployed at an indoor environment. Experimental results illustrated falls detection sensitivity of 94.7% and specificity of 85.7%. By providing appropriate context the robustness of situation recognition algorithms can be enhanced.

A distributed information repository for autonomic context-aware MANETs

Abstract: Due to the emergence of multimedia context-rich applications and services over wireless networks, networking protocols and services are becoming more and more integrated, thus relying on context and application information to support their operation. Further, wireless protocols and services now employ information from several network layers and the environment, breaking the layering paradigm. In order to cope with this increasing reliance on information, we have proposed MANIP, a middleware for MANETs that instantiates a new networking plane. The Information Plane (InP) is a distributed entity to store and disseminate information concerning the network, its services and the environment, orchestrating the collaboration among cross-layer protocols, autonomic management solutions and context-aware services. We use MANIP to support the autonomic reconfiguration of a P2P network over MANETs. Simulation results show that the MANIP-enabled solutions reduce the response time and increase the number of solved P2P queries when compared to classic, cross-layer implementations of the same protocols.

A novel recommendation system based on semantics and context awareness

Abstract: The existing content-based recommendation methods have two major limitations. First, due to the defects of the items and the user model matching algorithms, the recommendation results are very narrow. Second, scant attention is paid to the scenario, making the recommendation system not context-aware. It is essential to improve user satisfaction through high-quality recommendation. In this paper, two state-of-the-art methods are analyzed and extended to enhance recommendation performance. The first method is the context-aware recommender, which integrates context information into the recommendation process. The second method is the semantic analysis-based recommender, which incorporates domain semantics. Despite their compatibility, the challenge is to combine them in a way that will fully exploit their potential. An improved content-based model is proposed in this paper incorporating both semantics and context. Context-aware recommendation is performed to improve sensitivity to the context. Semantic relevance-based instance similarity is computed to address the problem of narrowness. The proposed recommendation system is evaluated using metrics (for instance, recall metric) and paralleled with the current methods grounded on the content. Results demonstrate the superiority of the proposed system in terms of accuracy.

On security level usage in context-aware role-based access control

Abstract: Huge contemporary trend is adding context awareness into software applications. It allows both better user experience as well as a lot useful features for application owner. Nowadays, there are various approaches enabling particular context awareness but none of them concerns security. We tackle this problem and describe it further in the paper. Our solution extends role based access control with certain context awareness elements. Based on already existing solutions we propose own lightweight, universal solutions, which allows instant enhancement of current RBAC even in existing applications. The uniqueness of our solution is based on using security levels, which are granted to user based on his context. Security levels represents how the users can be trusted and are determined during users login procedure. The levels are used as additional security constrain so to access resources in application user need to have not only right permission granted through roles, but also to have corresponding level.

PriCal: context-adaptive privacy in ambient calendar displays

Abstract: PriCal is an ambient calendar display that shows a user's schedule similar to a paper wall calendar. PriCal provides context-adaptive privacy to users by detecting present persons and adapting event visibility according to the user's privacy preferences. We present a detailed privacy impact assessment of our system, which provides insights on how to leverage context to enhance privacy without being intrusive. PriCal is based on a decentralized architecture and supports the detection of registered users as well as unknown persons. In a three-week deployment study with seven displays, ten participants used PriCal in their real work environment with their own digital calendars. Our results provide qualitative insights on the implications, acceptance, and utility of context-adaptive privacy in the context of a calendar display system, indicating that it is a viable approach to mitigate privacy implications in ubicomp applications.