Share Email Print
cover

Proceedings Paper

A novel approach to prevent 9/11/2001 events using artificial neural networks and decision support systems
Author(s): Arunkumar Srinivasan; Murugesan K Subramani; Abhijit S. Pandya
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

The ability to detect objects from image sequences and estimate their trajectory is useful in many applications like satellite tracking, missile guidance and interception. This paper proposes a reliable and an effective application for preventing loss of lives on event of airline crashes similar to the one on 9/11/2001. This contribution uses the MixeD algorithm for object detection, velocity estimation and the trajectory of the moving object in the spatiotemporal domain. The case study of the 9/11 event shows that the proposed method could have helped the authorities alert the people inside the towers far in advance about the hostile situation and could have saved a few more lives.

Paper Details

Date Published: 8 August 2003
PDF: 7 pages
Proc. SPIE 5072, Technologies, Systems, and Architectures for Transnational Defense II, (8 August 2003); doi: 10.1117/12.502310
Show Author Affiliations
Arunkumar Srinivasan, Florida Atlantic Univ. (United States)
Murugesan K Subramani, Florida Atlantic Univ. (United States)
Abhijit S. Pandya, Florida Atlantic Univ. (United States)


Published in SPIE Proceedings Vol. 5072:
Technologies, Systems, and Architectures for Transnational Defense II
Mark K. Hamilton; Vince C. Boles, Editor(s)

© SPIE. Terms of Use
Back to Top