By Topic

Toward Managing Uncertain Spatial Information for Situational Awareness Applications

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Yiming Ma ; Nokia Res. Center, Palo Alto, CA ; Kalashnikov, D.V. ; Mehrotra, S.

Situational awareness (SA) applications monitor the real world and the entities therein to support tasks such as rapid decision-making, reasoning, and analysis. Raw input about unfolding events may arrive from variety of sources in the form of sensor data, video streams, human observations, and so on, from which events of interest are extracted. Location is one of the most important attributes of events, useful for a variety of SA tasks. In this article, we consider the problem of reaching situation awareness from textual input. We propose an approach to probabilistically model and represent (potentially uncertain) event locations described by human reporters in the form of free text. We analyze several types of spatial queries of interest in SA applications. We design techniques to store and index the models, to support the efficient processing of queries. Our extensive experimental evaluation over real and synthetic datasets demonstrates the effectiveness and efficiency of our approaches.

Published in:

Knowledge and Data Engineering, IEEE Transactions on  (Volume:20 ,  Issue: 10 )