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Proceedings Paper

Automated situational awareness sensing for homeland defense
Author(s): Karl M. Reichard; Edward C. Crow; David C. Swanson
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Paper Abstract

Advances in information technology enable a capability to gather large amounts of raw data from all parts of our society to a degree of efficiency that can actually encumber surveillance missions. Today one can create automated networks of sensors to gather enormous volumes of data, but we do not have the human capacity to sort through all this raw data. Similar problems exist in the area of machinery condition or health monitoring - another surveillance problem. By automating data collection, processing, fusion and interpretation, one can bring the most relevant and timely information to human analysts, planners, and responders. Key technologies that enable this transformation from data to knowledge are distributed hardware and software architectures, intelligent sensors, data fusion and reasoning algorithms, and open system architectures for information exchange. Distributed hardware and software structures partition complex systems into a collection of interconnected subsystems. Intelligent sensors enable this conversion of data to information by processing massive amounts of data at the subsystem and higher levels to extract contextually relevant information. The transformation from raw sensor data to useful information requires the application of subsystem-specific signal processing and feature extraction algorithms, data fusion, and classification algorithms to combine data and features from commensurate and non-commensurate sensors or information sources. Emerging standards in open system architectures for condition based maintenance apply equally to surveillance systems and condition monitoring systems. Examples from fielded system health monitoring applications are presented along with their parallels to surveillance systems with application to homeland defense.

Paper Details

Date Published: 8 August 2003
PDF: 8 pages
Proc. SPIE 5107, System Diagnosis and Prognosis: Security and Condition Monitoring Issues III, (8 August 2003); doi: 10.1117/12.487106
Show Author Affiliations
Karl M. Reichard, The Pennsylvania State Univ. (United States)
Edward C. Crow, The Pennsylvania State Univ. (United States)
David C. Swanson, The Pennsylvania State Univ. (United States)


Published in SPIE Proceedings Vol. 5107:
System Diagnosis and Prognosis: Security and Condition Monitoring Issues III
Peter K. Willett; Thiagalingam Kirubarajan, Editor(s)

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