The Automatic SIEV-Net Instantiation for Collection Planning and Execution by ORM
Abstract
George Mason University has developed a scalable, information-based, real-time methodology for heterogeneous sensor management in support of maritime domain awareness. We propose to continue the development of an enabling technology for this research by investigating and implementing an automatic method for implementing additional evidence nodes in our Situation Information Expected Value network (SIEV-Net). The SIEV-Net is one component of our method of Information Based Sensor Management (IBSM) which captures the situation assessment and develops and evaluates situation information needs. The technical approach is to develop a method for automatically editing xml scripts which are used to describe Bayes nets to instantiate and delete evidence nodes related to situation information based on the results of orchestrated sensor actions. We will also define an appropriate measure of information based on the SIEV-Net paradigm. The anticipated outcome of this research is the development of a method for, and implementation of, an automatic SIEV-Net generator and updater. The principle investigator for this proposed research is Dr. Kenneth J. Hintz, Ph.D. who will perform the research at George Mason University, Fairfax, VA. The anticipated public benefit of this research is to enable effective resource allocation and collection planning for situation information gathering in the event of an unplanned disaster.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Jul 06, 2016
- Source ID
- N002441610026
Entities
People
- Kenneth Hintz
Organizations
- George Mason University
- United States Department of Defense