Artificial Intelligence for Proactive Vehicle Maintenance

This Phase II Sequential effort focuses on advancing the Proactive Combat Vehicle Management System (PCVMS) by leveraging AI-driven predictive maintenance, fault monitoring, and real-time anomaly detection to enhance the operational readiness and reliability of military vehicles. Building upon the previous Phase II achievements, the project aims to refine and validate predictive models using live data from key platforms such as the M10 Booker, ensuring seamless integration with existing Army systems without the need for vehicle modifications. The work will include a comprehensive analysis of critical sensors and components across various military and commercial vehicles to identify the most impactful factors for monitoring, which will inform the system's development. Additionally, the effort will involve  deploying and testing the enhanced PCVMS on selected Army vehicle data (if available, and also on commercial data that we continue to have access to), ensuring its scalability and applicability across different platforms. The ultimate goal is to deliver a robust, MOSA-compliant solution that significantly reduces maintenance costs, minimizes vehicle downtime, and increases mission readiness, all while providing commanders and maintenance crews with actionable insights into vehicle health and performance.