Hyperspectral Imaging (HSI) technologies provide the most accurate imaging method for detecting and classifying remotely-sensed Hazardous Materials (HAZMAT). Electric Vertical Takeoff and Landing/Urban Air Mobility (eVTOL/UAM) platforms provide the most cost-effective, rapid response, and easy to use data collection platform to support Humanitarian Assistance and Disaster Response (HADR) scenarios. Our solution combines these two technologies, capable of on-demand, high-fidelity, remotely-sensed material classifications, with cutting-edge data fusion, analysis, and autonomous control to enable rapid, data-driven decision-making to prevent unnecessary human suffering. This proposal introduces multi-purpose hyperspectral sensor technologies suitable for light-weight, low-cost eVTOL/UAM and capable of in situ collection, analysis, and classification at the edge (on-board the sensor) for real-time target-material detection and identification. The HSI sensor's analytic outputs are intended to initiate a chain of events that ultimately informs HADR operators and leadership with the most comprehensive situational awareness (STTR Phase I), data-driven decision support tools (STTR Phase II) and response options based on Pattern of Life (POL) activities (STTR Phase III). Our proposed HSI technologies were initially built for the Precision Agriculture and Smart City markets for real-time, in situ collection, processing, analysis and dissemination to the user for rapid decision-making. The inclusion of Hyperspectral Imaging gives the HADR operator/ground commander the ability to KNOW more about items of interest (e.g. exact HAZMAT name, concentration, extents and potentially the owner/manufacturer.) Other eVTOL/UAM HADR support missions include the location and identification of items of clothing and injured personnel (search and rescue) as well as soil moisture conditions (Lines of Communication (LOC) trafficability) for logistical support response planning. Our solution fuses HSI data with other eVTOL/UAM sensors (e.g. high definition video, thermal) to inform Artificial Intelligence systems for autonomous cross-cuing of collections and prioritization of collection missions. In Phases II and III we introduce Business Intelligence Process Technologies, that use time-series sensor and other data to discover emergent patters and activities typically hidden from view during the critical early-stage HADR scenarios. These emergent patterns can be anticipated through the use of Process Mining to Classify activities and matched to known Patterns of Life for predicted outcomes and recommended responses. Our solution ultimately integrates the very best eVTOL/UAM hyperspectral technologies and cutting edge eVTOL/UAM command and control solutions, with Process technologies to provide a rapidly deployable, high-fidelity, synchronized analytics system to speed responses that prevent unnecessary human suffering.
