Real-Time Sensor Fusion to Enhance Plume Detection in Urban Zones

The intentional or accidental large-scale release of a chemical-biological agent in an urban zone remains a viable threat to Homeland Security. As these silent, invisible and odorless plumes can cause massive casualties that would overwhelm emergency facilities, modeling, tracking and real-time prediction of plume dispersion and lethality is central to developing a user-friendly first responder's tool for evacuating civilians and managing emergency personnel. In response to this need, the authors and their collaborators have developed a wireless sensor network concept that fuses real-time meteorological and contaminant detection data with a simplified computational fluid dynamics model called CT-Analyst to hindcast plume origins and project subsequent dispersion. This paper overviews the development of the sensor network, the interfacing of real-time data to the pre-existing computational model, and the development of a hindcast algorithm to determine likely contaminant sources from measured sensor data. The results of field demonstrations conducted on the campus of the University of Notre Dame are presented to evaluate the effectiveness of embedded sensor networks fused with simplified computational models in tracking airborne contaminants. The paper concludes with a discussion of the scaled-up deployment of a larger network of sensors for demonstration in a major metropolitan area in August 2009.