DON26BZ03-NV061 TITLE: Predictive Movement for Object Oriented Tracking
OUSW (R&E) CRITICAL TECHNOLOGY AREA(S): Applied Artificial Intelligence (AAI)
COMPONENT TECHNOLOGY PRIORITY AREA(S): Trusted AI and Autonomy
PROJECTED CMMC LEVEL REQUIREMENT: Level 2 (Self)
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 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:
1. It must use AI-powered tracking algorithms to process sensor data, identify and track objects, and predict their future movements.
2. 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.
3. 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.
4. 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.
5. 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.
6. 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.
PHASE I: Develop a concept for an AI-driven maritime tracking system that automates data processing, object identification and tracking, and threat prioritization. Demonstrate the feasibility of this concept through modeling and simulation, showing how the proposed algorithms can achieve the required levels of accuracy in object identification, tracking, and prioritization using simulated sensor data representing realistic maritime scenarios. Ensure that this simulation demonstrates (1) the concept's ability to handle increasing data loads that reflect the Navy's future needs, (2) improved response times compared to current manual methods, and (3) the feasibility of hierarchical target management to prioritize objects based on predicted threat level. (Note: While full prototypes are not expected in Phase I, performers might need to develop subscale prototypes or surrogates of specific AI modules, such as predictive forecasting or POL analysis components.)
The Phase I Option, if exercised, will include the initial design specifications and capabilities to build a prototype solution in Phase II.
PHASE II: Develop a prototype AI-driven maritime tracking tool based on the results of Phase I. Demonstrate the core functionalities of the prototype, including AI-driven tracking, prioritization, predictive forecasting and change detection, hierarchical target management, enhanced scalability, and improved response time. Support rigorous prototype testing using simulated and/or real-world maritime sensor data and evaluation on the performance against metrics defined in the Description, including accuracy, prioritization effectiveness, and response time improvement. (Note: If a full prototype is cost-prohibitive, advanced modeling and simulation using representative data can be used to demonstrate the technology's potential.) Ensure that the prototype meets key requirements including specified accuracy levels, prioritization thresholds, and demonstrable improvements in response time and scalability.
It is probable that the work under this effort will be classified under Phase II (see the Description for details).
PHASE III DUAL USE APPLICATIONS: Support the Navy in transitioning the technology to Navy use. Support testing to ensure that the system meets the demanding requirements of modern naval operations via operational testing in simulated scenarios and field testing to assess its performance in actual conditions.
Once operators of the system have provided feedback on its usability, effectiveness, and suitability for operational needs, the system will be used to inform future development and deployment decisions, ultimately contributing to an enhanced scalability and improved response time.
Outside of the military, this technology has the potential to revolutionize various sectors, such as law enforcement, marine wildlife protection, climate change research, vessel collision avoidance, supply chain management, coordination of rescue/relief efforts, and meteorology. The system could be deployed across multiple domains, improving safety, efficiency, and environmental protection in diverse environments.
REFERENCES:
KEYWORDS: Pattern of Life; Hierarchical Target Management node; predictive forecasting; object oriented tracking; Change Detection; Automated Prioritization
TPOC 1: Lauren Jones
(202) 781-0451
lauren.l.jones8.civ@us.navy.milTPOC 2: Art Whittaker
(202) 781-2111
arthur.r.whittaker2.civ@us.navy.mil
** TOPIC NOTICE ** |
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