A Data-Driven Framework for Predictive Maintenance and Cost-Informed Planning of Airport Pavements
This working paper presents a data-driven framework for predictive maintenance and cost-informed planning of airport pavements. Using multi-airport pavement-condition data, it applies statistical and machine-learning models to forecast deterioration and support maintenance timing, lifecycle-cost analysis, and capital planning. The research demonstrates a reproducible approach designed for continued validation and application across U.S. airports.
Authors
- ESTHER OLUWADAMILOLA AINA
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-10-05
- DOI
- https://doi.org/10.5281/zenodo.23147054
- Primary Topic
- Infrastructure Maintenance and Monitoring
- Type
- article
- Field-Weighted Citation Impact
- 0.00