Auscultation of cracks in asphalt pavements plays a fundamental role for ensuring transportation infrastructure maintenance and longevity. This paper presents a system that combines neural network algorithms to detect, classify, and segment pavement cracks in order to produce reports of the concentration of cracks in asphalt pavements. The proposed approach generates a choropleth map that allows road inspectors to quickly determine the state of the pavement and get more information on the type of cracks present on the pavement. By implementing this system, continuous auscultation of asphalt pavements becomes feasible, contributing to effective infrastructure management and maintenance practices.
Crack Auscultation in Asphalt Pavements Using Computer Vision
Lect. Notes Electrical Eng.
International Conference on Applications in Electronics Pervading Industry, Environment and Society ; 2023 ; Genoa, Italy September 28, 2023 - September 29, 2023
Applications in Electronics Pervading Industry, Environment and Society ; Kapitel : 35 ; 251-257
2024-01-13
7 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
Maintenance of asphalt pavements
Engineering Index Backfile | 1929
|Asphalt Recycling of Pavements
SAE Technical Papers | 1979
|Cost-Effectiveness of Crack Sealing Materials and Techniques for Asphalt Pavements
Transportation Research Record | 2000
|Cost-Effectiveness of Crack Sealing Materials and Techniques for Asphalt Pavements
Online Contents | 2000
|