The proposed project aims to improve CMV safety by reducing tire-related violations through the use of a real-time artificial intelligence (AI)-based tire monitoring system

The Federal Motor Carrier Safety Administration awarded North Carolina Agricultural and Technical State University $1.022 million in project grant funding on December 1, 2025, under the Motor Carrier Safety Assistance High Priority Activities Grants and Cooperative Agreements program (CFDA 20.237) to develop and pilot a real-time artificial intelligence-based tire monitoring system designed to reduce tire-related violations in commercial motor vehicle fleets.

The recipient will create and deploy a tire monitoring system using AI and sensors to detect tire problems in real time on CMVs. The system will be installed on vehicles operated by participating motor carriers or enforcement partners, with data collected and analyzed to track performance against a target of achieving a 10 percent reduction in tire-related violations over one year based on inspection or enforcement data.

The project runs through September 30, 2028, with performance in North Carolina. Two sub-recipients will deliver specialized technical components. The University of South Carolina will design, build, and field-validate a cyber-secure, edge-enabled smart-sensor platform for real-time health monitoring, including fabrication of three prototype testbeds with multi-modal transducers and RF communications, development of embedded machine-learning algorithms for onboard anomaly detection, implementation of cybersecurity safeguards, and iterative bench and full-scale evaluations, with deliverables including three integrated sensor systems, validated edge-ML models, test reports, software documentation, and at least two peer-reviewed conference papers. Iowa State University will co-lead field evaluations and lead development of soft sensor integration for tire monitoring, machine-learning models to detect anomalies using time-domain analysis, and the real-time inference and alert system.

The goal is to pilot the technology with CMV fleets or enforcement partners and achieve a 10% reduction in tire-related violations over one year, based on inspection or enforcement data. The project will create and test a tire monitoring system that uses AI and sensors to detect problems in real time. The system will be installed on CMV s, and data will be collected and analyzed. The team will work with motor carriers or enforcement partners to track improvements and report results.