Publication Type
Conference Proceeding Article
Version
publishedVersion
Publication Date
3-2010
Abstract
This paper presents MediAlly, a middleware for supporting energy-efficient, long-term remote health monitoring. Data is collected using physiological sensors and transported back to the middleware using a smart phone. The key to MediAlly's energy efficient operations lies in the adoption of an Activity Triggered Deep Monitoring (ATDM) paradigm, where data collection episodes are triggered only when the subject is determined to possess a specified context. MediAlly supports the on-demand collection of contextual provenance using a novel low-overhead provenance collection sub-system. The behaviour of this sub-system is configured using an application-defined context composition graph. The resulting provenance stream provides valuable insight while interpreting the `episodic' sensor data streams. The paper also describes our prototype implementation of MediAlly using commercially available devices.
Discipline
Health Information Technology | Software Engineering
Research Areas
Software and Cyber-Physical Systems
Publication
2010 IEEE International Conference on Pervasive Computing and Communications 8th PerCom: March 29 -April 2, Mannheim, Germany
First Page
125
Last Page
134
ISBN
9781424453290
Identifier
10.1109/PERCOM.2010.5466985
Publisher
IEEE Computer Society
City or Country
Los Alamitos, CA
Citation
ROY CHOWDHURY, Atanu; FALCHUK, Ben; and MISRA, Archan.
MediAlly: A Provenance-Aware Remote Health Monitoring Middleware. (2010). 2010 IEEE International Conference on Pervasive Computing and Communications 8th PerCom: March 29 -April 2, Mannheim, Germany. 125-134.
Available at: https://ink.library.smu.edu.sg/sis_research/666
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1109/PERCOM.2010.5466985