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Detection, Identification and Monitoring (DIM) of hazardous chemical, biological, and radiological material is a critical component to Situational Awareness. Timely generated information just before and following a positive detection will lead to the most appropriate Course of Action (COA). The Technical Cooperation Program (TTCP) orchestrated a series of experiments to understand the operational limitations of new technologies in a Contested Urban Environment (CUE). One of the urban challenges occurred in Montreal, Canada in September 2018 where several technologies including a suite of biological DIM sensors were deployed. The urban environment adds complexity to the already challenging DIM task with potential line-of-sight limitations, changing wind conditions, complex communication spectrum, limited maneuverability, etc. The biological DIM suite deployed at this event included standoff, fixed point, mobile point and sampling, and identification sensing assets. The event revealed that the combination of various types of technologies might increase the overall system effectiveness. BioSense, a standoff technology, demonstrated its capacity to perform bio threat surveillance in urban environments having different constraints: short to long ranges; day and night operation; presence of various background sources; multiple surveillance areas without a deployment site having a line-of-sight on all of them and GPS-denied environment. The dedicated Chemical/Biological (CB) Sensor Data Viewer generated an integrated view of the available information from all sensors in real-time and provided a subset of this information to a central common operating software. The Class I mini UAS was equipped with an optical particle counter and filter collector membrane that was targeted to the appropriate location based on the cloud detected by the standoff sensor; and then, material classification obtained in near-real-time from the standoff spectral Laser Induced Fluorescence (LIF) interrogation was confirmed by simple post-processing of samples collected by the UAS.
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