Wildfire Prediction, Mitigation and Management Experiment Proposal

1. Wildfire Prediction, Mitigation and Management Experiment Proposal Prediction, Detection, Rapid Mitigation to save Lives,Forest, and Property in the State of Florida Presented To: Charles H. Bronson Commissioner Department of Agriculture and Consumer Services

2. Introduction Dr. Jim O’Brien, COAPS at Florida State University The AEgis Technologies Group Leadership Mr. Lance Cooper, VP, the AEgis Technologies Group Experiment Goals Mr. Paul Thielen, the AEgis Technologies Group Detailed Experiment Methodology Modeling and Simulation Ms. Deborah Heystek, the AEgis Technologies Group Dr. Eric Chassignet, COAPS at Florida State University Fire Chemistry Sensor Dr. Milan Buncick, the AEgis Technologies Group ResponderNet Command Management Solution Mr. Paul Thielen, the AEgis Technologies Group Ms. Rhonda Copley, Praxsoft Summary Mr. Paul Thielen Discussion All Agenda

3. AEgis Technologies • About AEgis Technologies • Provides world-class modeling and simulation technical services, products, and professional training. • Small Business • Established in 1989 • Headquartered in Huntsville, AL • 160+ Employees • 2005 Revenue $26.5M • Of our 160+ Employees • 37% have Master’s Degree or better • 63% have Engineering or CS degrees • 35% have Military Service experience • Relevant Facts • Recognized three times on INC Magazine’s “INC 500” list of the fastest growing privately held companies in America • Recognized on the Military Training Technology Top 100 list of companies that have made significant contributions to the military training industry • Recognized by the Better Business Bureau for Marketplace Ethics • Recognized by the Society of Financial Service Professionals for Ethics in the Business Community

4. Experiment Thesis • AEgis Team brings 3 pillar integrated approach to Florida Division of Forestry • Provides capability to predict, detect, and react to forest hot spots • Allows visibility of personnel / assets to reduce risk and enhance responsiveness

5. Project Team

6. Modeling Data Analysis • Predictive Forecasting of risk factors • Direction of resources in advance of events • Optimal resource employment/planning • FSU/COAPS • AEgis Technologies Group • Praxis • Division of Forestry

7. Model Analysisand Coupling FARSITE

8. Multi-Modal Approach to Sensor Placement Prediction CO CO2 HCL C2H2 CH4 CH3OH H2O Chemical Model Weather Model Global Atmospheric Model Fire Model Climate Model

9. Teamed with the Florida State University Center for Ocean Atmospheric Prediction Studies (COAPS) to accomplish the following services: Identify appropriate Weather and Fire Forecast/Dispersion Models for inclusion in potential Multi-Modal Prediction System Conceptualize each selected model and identify input/output data for Multi-Modal Integration Execute Models as necessary to validate Model Data and forecast for Experiment area for Field Trial Events Create (Deliverable) Microclimate Fire Prediction Conceptual Model for implementation Create High Level Design (Deliverable) for Microclimate Fire Prediction System Modeling and Simulation Activities

10. Sensing/Monitoring Approach • Integrate chemicals to detect fire initiation • Evaluate sensor technologies to develop/combine approaches • Prototype sensor for laboratory experiments • Develop stand-alone prototype for generated field experiment

11. Fire Detection Predominant Smoke Detection Techniques • Ionization Detection • Photoelectric Detection • Cloud chamber Detection Preferred Smoke Detection Technique • Cloud Chamber Detection is the most sensitive smoke detection technique. • Small handheld battery operated CCD systems are available for integration.

12. Fire Chemical Detection Fires produce gaseous combustion byproducts which depend on fuel type and combustion Common Compounds CO/CO2 Methanol Formaldehyde Ethylene Acetic Acid Formic Acid

13. Chemical transduction: Chemo-mechanical (cantilevers) Chemi-capacitive Chemi-resistive Chemical coating identifies analyte vapor type – arrays for multiple vapor typing Devices are miniature, sensitive, fast response, electrical readout, low power Low-power MEMS vapor sensors Seacoast Science Cyrano Sciences

14. MEMS array integration with mixed detection Coating Polysilicon beam Beam anchor Bottom plate Substrate Plate Capacitor Cantilever (capacitive readout) Interdigitated C or R Coating Ink-Jet Deposition Built-in temperature control

15. AEgis will produce a system that detects Smoke CO/CO2 Methanol, Formaldehyde, Ethylene, Ethane, Acetic acid and Formic acid Identification and Acquisition of Detection Chemistry Validate fire chemistry model for FCS Device Conduct Laboratory Examination of fire chemistries and deliver testable Lab Prototype FCS Device for Lab testing Develop Test and Acceptance Plan/Criteria for Production FCS Create a field test prototype FCS device for deployment and testing (Deliverable) Conduct Field Trials of FCS Device Fire Chemistry Sensors

16. Tracking and Response Management • Development and fielding of RF based communication network • Provides integrated tracking and responsive management system • Deployment of weather detection stations for data acquisition • Provides command center operations with graphical display system to track personnel and assets

17. Architecture –ResponderNetwith CFS and Models Sensors – meteorological and chemical fire sensor Internet Universal Sensor Interface Server to ingest real-time data and perform FSU modeling algorithms AssetActive USI provides ability to read active tags, interfaces to AEgis CFS and transmits data to other Receivers/Repeaters Receiver/Repeater Server AEgis Web-based GIS Software and Modeling Output AssetActive LR Active tags on responders with GPS for outdoor location In-vehicle readers collect data from tags and send the data back through cell

18. ResponderNet Command Management System

20. Distributed Architecture Concept UDP(TCP/IP) State Response Managers City/County Response Managers On-Scene Commander Authorized Subscribers

21. ResponderNet Command Management System (RCMS) Hardware/Software Delivery Schedule: 1 Primary and 1 Backup Server Based RCMS Application and Database License 12 Command and Control Vehicle Suites Hardened Laptop with RCMS Application and Database ResponderNet Vehicle Tracking Suite 100 ResponderNet Vehicle Tracking Suites Digital VHF Transceiver RF Repeater GPS Positioning 200 GPS/RFID Enabled ResponderNet Personnel Tracking Tags RF/GPS 3D Locator Tags 4 Weather Stations RCMS PlatformDeployment Plan

22. Conduct Analysis and Design Activities and develop the Systems Architectural Design (Deliverable) Develop Graphical User Interfaces and RCMS Applications within accepted Systems Architecture Design Document (SADD) Develop Test and Acceptance Criteria for all RCMS components Conduct installation services and End User Training for RCMS Devices and Interfaces Conduct Field Trials and Acceptance Testing for RCMS at Division of Forestry ResponderNet CommandManagement System

23. Application of multiple proven modeling architectures in a collaborative environment will achieve a predictive posture within fire management processes to enhance response effectiveness. The Fire Chemistry Sensor offers a reliable sound architecture which has a great deal of flexibility and benefit beyond Fire Chemistry and with modification will provide AGLAW a significant advance in Narcotics Trafficking Interdiction and Methamphetamine Detection. The ResponderNet Command Management Solution will provide great value and improved safety in virtually every agency within DOACS. Summary

24. ResponderNet Applies to all DOACS Roles