Search
  Advanced Search
 
Journal search
Journal cover: International Journal of Pervasive Computing and Communications

International Journal of Pervasive Computing and Communications

ISSN: 1742-7371

Online from: 2005

Subject Area: Information and Knowledge Management

Content: Latest Issue | icon: RSS Latest Issue RSS | Previous Issues

 

Icon: .Table of Contents.Next article.Icon: .

ContextAlert: context-aware alert mode for a mobile phone


Document Information:
Title:ContextAlert: context-aware alert mode for a mobile phone
Author(s):Santi Phithakkitnukoon, (Massachusetts Institute of Technology, Cambridge, Massachusetts, USA), Ram Dantu, (University of North Texas, Denton, Texas, USA)
Citation:Santi Phithakkitnukoon, Ram Dantu, (2010) "ContextAlert: context-aware alert mode for a mobile phone", International Journal of Pervasive Computing and Communications, Vol. 6 Iss: 3, pp.1 - 23
Keywords:Adaptive system theory, Mobile communication systems
Article type:Research paper
DOI:10.1108/17427371011084266 (Permanent URL)
Publisher:Emerald Group Publishing Limited
Acknowledgements:This work is supported by the National Science Foundation under grants CNS-0627754, CNS-0619871, and CNS-0551694.
Abstract:

Purpose – Mobile computing research has been focused on developing technologies for handheld devices such as mobile phones, notebook computers, and mobile IP. Today, emphasis is increasing on context-aware computing, which aims to build the intelligence into mobile devices to sense and respond to the user's context. The purpose of this paper is to present a context-aware mobile computing model (ContextAlert) that senses the user's context and intelligently configures the mobile phone alert mode accordingly.

Design/methodology/approach – The paper proposes a three-step approach in designing the model based on the embedded sensor data (accelerometer, GPS antenna, and microphone) of a G1 Adriod phone. As adaptivity is essential for context-aware computing, within this model a new learning mechanism is presented to maintain a constant adaptivity rate for new learning while keeping the catastrophic forgetting problem minimal.

Findings – The model has been evaluated in many aspects using data collected from human subjects. The experiment results show that the proposed model performs well and yields a promising result.

Originality/value – This paper is distinguished from other previous papers by: first, using multiple sensors embeded in the mobile phone, which is more realistic for detecting the user's context than having various sensors attached to different parts of user's body; second, by being a novel model that uses sensed contextual information to provide a service that better synchronizes the user's daily life with a context-aware alert mode. With this service, the user can avoid the problems such as forgetting to switch to vibrate mode while in a meeting or a movie theater, and taking the risk of picking up a phone call while driving, and third, being an adaptive learning algorithm that maintains a constant adaptivity rate for new learning while keeping the catastrophic forgetting problem minimal.



Fulltext Options:

Login

Login

Existing customers: login
to access this document

Login


- Forgot password?
- Athens/Institutional login

Purchase

Purchase

Downloadable; Printable; Owned
HTML, PDF (424kb)

Due to our platform migration, pay-per-view is temporarily unavailable.

To purchase this item please login or register.

Login


- Forgot password?

Recommend to your librarian

Complete and print this form to request this document from your librarian


Marked list


Bookmark & share

Reprints & permissions