Conference Paper

A Middleware Framework for Ambiguous Context Mediation in Smart Healthcare Application.

Univ. of Texas at Arlington, Arlington
DOI: 10.1109/WIMOB.2007.4390866 Conference: Third IEEE International Conference on Wireless and Mobile Computing, Networking and Communications, WiMob 2007, White Plains, New York, USA, 8-10 October 2007, Proceedings
Source: DBLP

ABSTRACT Ubiquitous healthcare applications envision future computing and networking environments as being filled with sensors that can determine various types of contexts of its inhabitants, such as location, activity and vital signs. While such information is useful in providing context-sensitive services to the inhabitants to promote intelligent independent living, however in reality, both sensed and interpreted contexts may often be ambiguous. Thus, a challenge facing the development of realistic and deployable context-aware services is the ability to handle ambiguous contexts to prevent hazardous situations. In this paper, we propose a framework which supports efficient context-aware data fusion for healthcare applications that assume contexts could be ambiguous. Our framework provides a systematic approach to derive context fragments, and deal with context ambiguity in a probabilistic manner. We also incorporate the ability to represent contexts within the applications, and the ability to easily compose rules to mediate ambiguous contexts. Through simulation and analysis, we demonstrate the effectiveness of our proposed framework for monitoring elderly people in the smart home environment.

  • Source
    Dataset: UTM Paper
  • [Show abstract] [Hide abstract]
    ABSTRACT: In a pervasive system, users have very dynamic and rich interactions with the environment and its elements, including other users. To efficiently support users in such environments, a high-level representation of the system (namely, context) is usually exploited. However, since pervasive environments are inherently people-centric, context might consist of sensitive information. As a consequence, privacy concerns arise, especially in terms of how to control information disclosure to third parties (e.g., other users). In this paper we propose context-aware approaches to privacy preservation in wireless and mobile pervasive environments. Specifically, we design two schemes: (i) to reduce the interactions between the user and the system, and (ii) to exploit the interactions between different users. Both of our solutions are adaptive, thus suitable for dynamic scenarios. In addition, our schemes require limited computational and storage resources, so that they can be implemented on resource-constrained personal and sensing devices. We apply our solutions to a smart healthcare scenario, and show that our schemes not only effectively protect the user privacy, but also significantly reduce the interactions with the system, thus improving the user experience.
    World of Wireless, Mobile and Multimedia Networks (WoWMoM), 2012 IEEE International Symposium on a; 01/2012
  • [Show abstract] [Hide abstract]
    ABSTRACT: Health professionals, nursing and care staff are in short supply to cater to all the needs of the growing, global elderly population. This paper presents the design and implementation of a low cost and low power context aware robotic system to assist the elderly due to a desire to develop accessible technology for all countries and considering the poverty of many elderly. The system is furnished with 4 wheels for indoor navigation. It is equipped with 'environmental parameter monitoring' sensors and the system can be controlled by the user through voice commands. The system interprets the environmental contexts and makes context aware decisions based on the sensed information. On the basis of the previous medical history from the database server and the newly interpreted data, the decision making unit makes efficient decisions and gives feedback to the device control unit. The system improves the health of the elderly by regularly monitoring the environmental conditions of people.
    Computer Science & Education (ICCSE), 2013 8th International Conference on; 01/2013

Full-text (2 Sources)

Available from
May 28, 2014