Title :
hSpy: An intelligent framework for context and predictive analysis for smarter health devices
Author :
Araujo Oliveira, Eduardo ; Kirley, Michael ; Vanz, Elena ; Gama, Kiev
Author_Institution :
Dept. of Comput. & Inf. Syst., Univ. of Melbourne, Melbourne, VIC, Australia
Abstract :
The world is experiencing an unprecedented explosion in the number of smart devices and mobile apps available. In particular in health area devices and technologies related to market place are often restricted to proprietary platforms, typically working in isolation with fixed hardware settings. Gaining access to high-quality data - including aggregated data from existing sensors, gadgets and smart devices is one important challenge. This article explores the idea of hSpy, an intelligent framework to support context and predictive analysis based on the integration of distributed and heterogeneous mobile sensor data for smarter health devices. hSpy aims to help users monitoring their current health status via the acquisition of meaningful and accurate information.
Keywords :
health care; mobile computing; context awareness; hSpy; intelligent framework; mobile sensor data; predictive analysis; smart health devices; Computer architecture; Context-aware services; Intelligent sensors; Medical services; Mobile handsets; Monitoring; context aware; health monitoring; internet of things; mobile sensors; predictive analysis; smarter devices;
Conference_Titel :
Information and Communication Technology Convergence (ICTC), 2014 International Conference on
Conference_Location :
Busan
DOI :
10.1109/ICTC.2014.6983083