JITMMA/W Training Content Delivery in Low Data Throughput Networking Environments

OUSD (R&E) MODERNIZATION PRIORITY: Network Command, Control and Communications; Artificial Intelligence/Machine Learning; General Warfighting Requirements (GWR) TECHNOLOGY AREA(S): Bio Medical; Air Platform OBJECTIVE: Develop a tool or set of tools and/or processes for data/content storage and application at the edge. These technologies and/or processes would have to intelligently deliver training content in a potentially low data throughput networking environment and on various hardware with potentially limited computing capability. DESCRIPTION: To defeat near-peer adversaries in contested environments, the United State Air Force (USAF) will operate from an expeditionary position requiring significant resiliency and agility. Agile Combat Employment (ACE) is an operational concept that employs a network of existing bases and austere locations to deliver combat power to support expeditionary missions. Combat forces at these bases must be agile and be able to respond quickly with significantly reduced infrastructure and force footprint. Airmen operating at these austere forward operating locations, because of the reduced personnel footprint, will need to be multi-capable (i.e., able to perform multiple tasks across platforms and across specialties.) To enable that capability, the Air Force Research Laboratory (AFRL) has embarked on an applied research program called Just-in-time, Multi-mission airmen/warfighters (JITMMA/W), an integrated capability to support deployed personnel performing a wider variety of mission tasks across traditional AFSC and expertise boundaries. A technology gap that exists within the JITMMA/W space is that of agile intelligent delivery of training content to the tactical edge. Airman who will be supporting ACE tasks in forward and potentially austere locations will need the appropriate training content/courseware (i.e., lessons, demonstrations, assessments, etc.) available where and when they need it, regardless of connectivity to larger networks and data stores (e.g., cloud). These technologies will also need to tailor content delivery to the specific mission and airman requirements (such as familiarization training, differences training, etc.) PHASE I: Develop an approach and a roadmap for an iterative development of this capability, along with references to relevant research in this area. The outcome of the Phase I should be a clear development path for a tool or set of tools and/or processes that propose to overcome the challenges of intelligent training content delivery to ACE multi-mission airmen. PHASE II: Implement the product roadmap features identified during the Phase I. Demonstrate a tool, set of tools, and or processes that can intelligently deliver training content to the tactical edge, when and where needed. An objective would be to show that this approach can incorporate learning to improve content requirements prediction performance. Validate the performance of the content delivery mechanism. Document the design, the design process, and the validation results in a final report. PHASE III DUAL USE APPLICATIONS: Industry engaged in rapid and responsive training of field or line personnel could leverage technologies like these to significantly reduce costs and improve efficiency without sacrificing safety. In addition, as the USAF's Air Education and Training Command (AETC), as well as the training commands of all sister services, begin to take advantage of the power of XR technologies to push training further into the field, they will need technologies that intelligently deliver training content. REFERENCES: Majumder, S., Mondal, T., Deen, M.J. Wearable sensors for remote health monitoring (2017) Sensors (Switzerland), 17 (1), art. no. 130, . Cited 444 times; Pandya, B., Pourabdollah, A., Lotfi, A. A cloud-based pervasive application for monitoring oxygen saturation and heart rate using fuzzy-as-a-service (2021) ACM International Conference Proceeding Series, pp. 69-75; Mahmood, A.S., Jafer, E., Hussain, S., Fernando, X. Wireless body area network development for remote patient health observing (2017) IHTC 2017 - IEEE Canada International Humanitarian Technology Conference 2017, art. no. 8058193, pp. 26-31.Cited 6 times. KEYWORDS: Flexible/Wearable Sensors; Cognitive state assessment; Task/activity performance monitoring and assistance; Performance assessment and prediction; Telemedicine and telemaintenance tools. deployed personnel