OUSD (R&E) CRITICAL TECHNOLOGY AREA(S): Trusted AI and Autonomy The technology within this topic is restricted under the International Traffic in Arms Regulation (ITAR), 22 CFR Parts 120-130, which controls the export and import of defense-related material and services, including export of sensitive technical data, or the Export Administration Regulation (EAR), 15 CFR Parts 730-774, which controls dual use items. Offerors must disclose any proposed use of foreign nationals (FNs), their country(ies) of origin, the type of visa or work permit possessed, and the statement of work (SOW) tasks intended for accomplishment by the FN(s) in accordance with the Announcement. Offerors are advised foreign nationals proposed to perform on this topic may be restricted due to the technical data under US Export Control Laws. OBJECTIVE: Develop a software solution that utilizes artificial intelligence (AI) and machine learning (ML) to automate the generation of accurate and consistent problem reports for surface navy platforms. DESCRIPTION: The Navy's Aegis Combat System (ACS) currently relies on manually generated problem reports using testing, analysis, and operator feedback. These problem reports are currently populated by personnel with varying degrees of experience. Information is provided by personnel attempting to identify issues that may or may not agree with the written performance specifications for their systems. This produces a lack of details needed to reproduce the issues. The process is time consuming, prone to human error, and lacks consistency across platforms and personnel. The Navy seeks an innovative software solution that is capable of automatically generating accurate and reliable problem reports for surface navy platforms, replacing manual processes used in the current ACS. This can be accomplished either through merging, removing, or automatically generating problem reports to reduce operator workload and improve efficiency. Added capability would provide more accurate problem reports written against specifications for human understanding and improvement of human system integration (HSI). Currently there are no commercially available remedies found to solve this situation. The observation of anomalous behaviors or unexpected testing and analysis results will drive generation of problem reports. The software solution needs to provide a system that can perceive, recognize, learn, decide, and act on their own. The solution will need to consolidate and interpret data. The software solution will utilize ML systems with the ability to explain their rationale, characterize their strengths and weaknesses, and convey understanding of how they will behave in the future. The software application will also need to be capable of analyzing existing reports to understand format and content requirements. It will need to accept input from the test community and operators, automatically generate problem reports that are accurate and reliable based on various data sources, including sensor data, test observations, and operational experiences, and integrate seamlessly with all elements of the ACS. Because of the planned implementation for both operational and testing environments, the software application should permit realistic testing of evolving threat types and configurations in a dynamic test environment. This will enable the proficiency of testing and certification problem reporting timelines for new Aegis program timelines. This will also help in maintaining or improving product quality through the early detection of deficiencies in the product. The speed and accuracy of the solution must exceed existing ACS performance attributes by 10% or better. Work produced in Phase II may become classified. Note: The prospective contractor(s) must be U.S. owned and operated with no foreign influence as defined by 32 U.S.C. 2004.20 et seq., National Industrial Security Program Executive Agent and Operating Manual, unless acceptable mitigating procedures can and have been implemented and approved by the Defense Counterintelligence and Security Agency (DCSA) formerly Defense Security Service (DSS). The selected contractor must be able to acquire and maintain a secret level facility and Personnel Security Clearances. This will allow contractor personnel to perform on advanced phases of this project as set forth by DCSA and NAVSEA in order to gain access to classified information pertaining to the national defense of the United States and its allies; this will be an inherent requirement. The selected company will be required to safeguard classified material during the advanced phases of this contract IAW the National Industrial Security Program Operating Manual (NISPOM), which can be found at Title 32, Part 2004.20 of the Code of Federal Regulations. PHASE I: Develop a concept for a problem report solution that demonstrates it can feasibly meet the parameters in the Description. Feasibility will be demonstrated through modeling and simulation. The Phase I Option, if exercised, will include the initial design specifications and capabilities description to build a prototype solution in Phase II. PHASE II: Develop and deliver a prototype problem report solution based on the results of Phase I that meets the parameters described in the Description. Demonstration will take place at a government provided facility. The government subject matter expert will evaluate the prototype to ensure it improves situational visualization and situational understanding within a varied problem reporting context. It is probable that the work under this effort will be classified under Phase II (see Description section for details). PHASE III DUAL USE APPLICATIONS: Support the Navy in transitioning the technology for Government use within the Aegis Weapon System (AWS in Advanced Capability Build (ACB) 20 or higher) as part of an Integrated AWS database. Refine the prototype for integration into the current AWS operational planning tools. Test and refine the prototype design for the appropriate interfaces with other Navy systems and to comply with information security requirements. The developed technology should be broadly applicable to live testing of manned and unmanned systems and simulations in which users need Course of Action (COA) planning and updates to the plan as time progresses. Dual use applications are numerous, almost any analyst seeking to combine spatial and temporal data in a single display could use this technology including the Federal Aviation Administration or civilian air controllers. REFERENCES: 1. Campos, Luna. Data Synchronization: What It Is and How to Sync Data for Beginners. HubSpot, December 05, 2022. https://blog.hubspot.com/website/data-synchronization 2. Software Solution. https://www.sciencedirect.com/topics/computer-science/software-solution https://www.geeksforgeeks.org/ai-tools-for-generating-reports/#jenni-ai 3. National Industrial Security Program Executive Agent and Operating Manual (NISP), 32 U.S.C. 2004.20 et seq. (1993). https://www.ecfr.gov/current/title-32/subtitle-B/chapter-XX/part-2004 KEYWORDS: Anomalous Behaviors; unexpected testing and analysis results; automatically generate problem reports; Machine Learning to automate; testing and certification problem reporting timelines; consistency across platforms
