Description
Objective: Develop a capability using Artificial Intelligence (AI) that investigates, tracks, and assigns priority for future state forecasting such as Geospatial-temporal Pattern of Life Analysis and change detection for the Maritime Targeting Cell (MTC). Description: Maritime Targeting Cell is a high-tech “fusion” node, which receives massive amounts of data from diverse sources (e.g., satellites, sensors), making it difficult to process and interpret effectively. Current tracking relies heavily on manual methods, which can overwhelm staff and lead to inefficient resource allocation. They are essentially trying to find the proverbial needle in a haystack. Without an automated system, it is difficult to prioritize which objects require immediate attention, which can lead to critical threats being overlooked. The Maritime Targeting Cell has a need to increase readiness for potential conflicts with adversaries. There are currently a large number of objects that need to be tracked, both above and below the surface of the ocean, across the globe. These objects include U.S. Navy Ships, other U.S. Government vessels, allied and partner Naval vessels, commercial vessels, adversary vessels, U.S. and other nations’ submarines, underwater drones and sensors, and aircraft. The Navy needs to utilize efficient tracking methods for large numbers of objects so future state forecasting, pattern of life, and change detection can enable analysts to investigate targets, maintain track custody, and assign priority to objects detected. As more sensors come online, the data volume will only increase, exacerbating existing problems. The current manual processes simply cannot scale and as the Navy’s specific requirements are unique and complex, off-the-shelf tracking software is insufficient. Currently no existing commercial technology can meet this need. The Navy envisions an AI-driven solution that aims to address these challenges by automating key aspects of the tracking process. The solution must meet the following parameters: It must use AI-powered tracking algorithms to process sensor data, identify and track objects, and predict their future movements. It must use Automated Prioritization in which AI is used for activity prediction and Pattern of Life (POL) analysis to assign a priority level to each tracked object, allowing analysts to focus on the most important targets first. It must use Predictive Forecasting and Change Detection to analyze historical data and current behavior and predict future object states and quickly identify deviations from expected patterns, enhancing situational awareness. It must contain Hierarchical Target Management to allow the system to maintain track custody of all objects, but present them to analysts in a prioritized hierarchy, allowing for efficient resource allocation. It will need to have Enhanced Scalability so as new sensors are added, the AI can seamlessly integrate the additional data without requiring a proportional increase in manpower. It will need to have Improved Response Time through automating analysis and prioritization to accelerate the decision-making process, enabling faster responses to developing situations. In essence, the proposed AI solution aims to transform the Navy from a reactive overwhelmed center to a proactive highly efficient hub for maritime domain awareness, which will empower the Navy to better manage the vast amount of data it collects and make more informed decisions, ultimately enhancing national security. Evaluation metrics will be used to quantify the system’s performance, including accuracy, precision, recall, F1-score (a balanced measure of precision and recall), processing time, false positive rate, and false negative rate. These metrics will measure how often the system correctly identifies and tracks objects, the proportion of correctly identified objects out of all identified and all actual objects, a balance of precision and recall, the data processing time, and the rates of incorrect object identification and missed object identification. 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. Keywords: Pattern of Life; Hierarchical Target Management node; predictive forecasting; object oriented tracking; Change Detection; Automated Prioritization CMMC Level: Level 2 (Self)