Automated situational awareness sensing for homeland defense

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. Low-level, wide-bandwidth sensor data can be confined at the subsystems level and only higher-level information needs to be shared between monitoring modules for different subsystems or at higher levels. 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. Intelligent sensors may consist of traditional transducer elements, electronics, and processing capability, or may exist as virtual processing nodes resident on a data network. 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 will ease the integration of monitoring system components from different vendors and apply to surveillance systems in general as well as condition monitoring systems. Examples from fielded system health monitoring applications are presented along with their parallels to surveillance systems with application to homeland defense.