Technology Enablers for Just In Time Multimission Airmen/Warfighters (JIT MMA/W)

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: Create an integrated capability to support deployed personnel performing a wider variety of mission tasks across traditional AFSC and expertise boundaries. DESCRIPTION: Deploying large numbers of personnel will not be feasible at forward austere locations in future fights. Multi-capable airmen must have point-of-need support for performance and resilience. The goal is to leverage maturing technologies in key areas of focus under this topic to provide seamless, adaptive and resilient airman performance across a range of mission types and tasks especially focused on multi-mission performance in deployed, austere locations. Technology areas of interest include but are not limited to Training and aiding content management ; Augmentation strategies and technology; Sensing, sensors and fusion methods; Intelligent and naturalistic user interfaces; Software models for agents (SME and Wingman); Data on/data off and augmented analytics; and tools for persistent, secure, covert networks and data movement. This topic seeks relevant technologies in areas of relevance to achieve the objective. While eventual integration will be accomplished the goal here is to solicit viable candidates in the areas and work to mature and apply those to meet the stated objective. PHASE I: This topic is intended for technology proven ready to move directly into a Phase II. Therefore, a Phase I award is not required. The offeror is required to provide detail and documentation in the Direct to Phase II proposal which demonstrates accomplishment of a Phase I-like effort, including a feasibility study. This includes determining, insofar as possible, the scientific and technical merit and feasibility of ideas appearing to have commercial potential. PHASE II: Eligibility for D2P2 is predicated on the offeror having performed a Phase I-like effort predominantly separate from the SBIR Programs. Phase II involves the identification and selection of technology alternatives in two or more of the areas of relevance to support the objectives. Several distinct Phase II efforts are envisioned to both mature specific technology options and capabilities in and of themselves but to also to tailor and focus them on the objectives for JIT MMA/W specifically. A number of the products from the Phase II efforts are expected to mature as stand alone capabilities, but will also mature with a goal of integration into an overall set of technology capabilities to meet the objectives for the topic. PHASE III DUAL USE APPLICATIONS: The contractor will pursue commercialization of the various technologies developed in Phase II for transitioning expanded mission capability to a broad range of potential government and civilian users and alternate mission applications. Direct access with end users and government customers will be provided with opportunities to receive Phase III awards for providing the government additional research & development, or direct procurement of products and services developed in coordination with the program. 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.; Fouse, A., Weiss, C., Mullins, R., Hanna, C., Nargi, B., & Keefe, D. F. (2018, June). Multimodal Interactions In Multi-Display Semi-Immersive Environments. In 2018 IEEE Conference on Cognitive and Computational Aspects of Situation Management (CogSIMA) (pp. 36-41). IEEE.; Rebensky, S., Carroll, M., Bennett, W., & Hu, X. (2021). Impact of Heads-up Displays on Small Unmanned Aircraft System Operator Situation Awareness and Performance: A Simulated Study. International Journal of Human Computer Interaction, 1-13.; Oviatt, S. (2007). Multimodal interfaces. In The human-computer interaction handbook (pp. 439-458). CRC press.; Jones, G., Berthouze, N., Bielski, R., & Julier, S. (2010, May). Towards a situated, multimodal interface for multiple UAV control. In 2010 IEEE International Conference on Robotics and Automation (pp. 1739-1744). IEEE.; B hme, H. J., Wilhelm, T., Key, J., Schauer, C., Schr ter, C., Gro , H. M., & Hempel, T. (2003). An approach to multi-modal human machine interaction for intelligent service robots. Robotics and Autonomous Systems, 44(1), 83-96.; Lemmel , S., Vetek, A., M kel , K., & Trendafilov, D. (2008, October). Designing and evaluating multimodal interaction for mobile contexts. In Proceedings of the 10th international conference on Multimodal interfaces (pp. 265-272).; Cummings, M. L. (2015). Operator interaction with centralized versus decentralized UAV architectures. Handbook of Unmanned Aerial Vehicles, 977-992. KEYWORDS: Augmented, virtual and extended reality technology; Flexible/Wearable Sensors; Cognitive state assessment; Physiological state assessment (e.g., Vital Signs); Task/activity performance monitoring and assistance; Environmental monitoring (e.g., CBRNE; DE);