Pilot Training Next - Program RFI

BACKGROUND The Air University (AU), Maxwell Air Force Base, Alabama, is conducting a research effort to build and evaluate a training and education model that synthesizes various existing technologies toward the goal of improving and gaining efficiencies in training and education. The model leverages virtual/augmented reality, artificial intelligence, data analytics, and human-machine interface technologies to select candidates, perform training and training management functions, enhance education, and collect/analyze large quantities of relevant data. This proof of concept study will require the integration of multiple distinct functions along the following lines: - Talent Selection: This research begins with determining the best candidates for participation in the training process. This project requires up to 30 high-quality candidates that have been vetted for qualities that suggest success in the rigorous pilot training environment. - Virtual Reality, Augmented Reality, and Mixed Reality (VR/AR/MR): This research will rely heavily on this technology as the primary means of training. The project will require up to 20 fixed VR/AR/MR computer stations, and 10 portable stations. These stations will need to be linked to one another, and to a data collection system (either hardware or cloud-based) capable of storing the large amounts of data that will be produced throughout training. They must run advanced flight simulation software with an open architecture to allow integration of other technologies, and real-time training management. - Artificial Intelligence (AI): The vision for this research is that training management and real-time performance monitoring and feedback can be provided by AI. Student performance will be measured against an objective and prescribed model of an Air Force pilot. This technology must integrate with the computer system and software selected for the test. - Human-Machine Interface (HMI): The test will involve various forms of HMI biometric sensing, eye-tracking, pupilometry etc. that can provide real-time information to the AI for training management and student performance assessment. - Data Analysis: If feasible, the large amounts of data produced by this study will be analyzed by individual, laterally across trainees, and longitudinally as this training program progress through time. The desire is to better understand the training process and develop best-practices to improve the model iteratively. This data will also be fed back into the recruiting and talent selection process. INSTRUCTIONS THERE IS NO SOLICITATION AT THIS TIME. This Request for Information (RFI) notice does not constitute a request for quotes or proposals. Submission of any information in response to this sources sought notice is purely voluntary. The Government assumes no financial responsibility for any costs incurred. The responses to this source sought notice will be used for market research purposes. If your organization has the potential capability to perform these services, please provide a response as follows- Cover Sheet - 1 page Include the following information: 1. Organization name, address, DUNS number, and web site. 2. Point of contact to include e-mail address and telephone number. 3. Business size under NAICS code 541612 (Specify all SBA programs if applicable). 4. If applicable, GSA contract number, schedule, and SIN category. (This is only necessary if all services are within the scope of the referenced GSA schedule.) Capabilities Statement and Market Information - no more than 5 pages Demonstrate your understanding of and experience using research or any other proven methodologies in selecting the best pilot candidates or pilot trainees. Although it is not Air University's intent to publicly disclose proprietary information obtained during this RFI, Air University reserves the right to share the information received in response to this RFI within the U.S. Government. Any information submitted in response to this RFI that is marked as "Proprietary" or "Confidential Commercial or Financial Information" will be treated as labeled.