The Alabama Department of Transportation (ALDOT) is leveraging Blyncsy, an AI-powered roadway analytics solution from infrastructure engineering software company Bentley Systems, to enhance its long-standing performance-based budgeting approach for highway maintenance.
ALDOT adopted performance-based budgeting more than 15 years ago and has continued to refine the model to ensure maintenance funding is allocated based on objective, data-driven insights rather than historical assumptions.
A key challenge has been collecting consistent and timely asset condition data across Alabama’s 11,000-mile roadway network.
Traditionally, this data has relied on statewide surveys and manual inspections — methods that are labour-intensive, resource-heavy, and prone to variability. To improve both efficiency and consistency, ALDOT is now integrating Blyncsy’s automated AI analytics into its assessment process, enabling faster and more standardised evaluations of designated roadway assets.
Blyncsy, part of Bentley’s Asset Analytics portfolio, uses crowdsourced high-resolution dash camera imagery from vehicles and applies AI to automatically analyse roadway conditions. This approach delivers consistent, empirical assessments of critical assets such as guardrails and signage across the entire network.
In a previous pilot project, Blyncsy’s AI models achieved 97% accuracy, providing the reliable data foundation required to support precise financial planning.
“To strengthen our performance-based budgeting, we need consistent, quantified data to produce condition assessments across all districts,” said Morgan Musick, assistant maintenance management engineer at ALDOT.
“Blyncsy enhances our existing statewide survey by automating selected asset inspections, giving us an objective snapshot of roadway conditions and allowing us to align budgets with actual maintenance needs to meet targeted levels of service.”
Mark Pittman, senior director of transportation AI at Bentley Systems, said the integration reflects a broader shift in infrastructure management.
“The future of asset management lies in making financial decisions based on empirical evidence rather than historical precedent. By embedding AI-driven inspections into its budgeting framework, ALDOT is advancing a more accountable and data-led approach to infrastructure planning,.”