Document Type
Doctoral Thesis
Disciplines
1.2 COMPUTER AND INFORMATION SCIENCE, 2. ENGINEERING AND TECHNOLOGY
Abstract
Regular inspections of pavements are conducted by civil infrastructure departments to evaluate the surface condition. Pavement surfaces are subject to deterioration caused by several factors such as traffic, weather, and sunlight. This deterioration becomes evident through various distresses, including potholes, rutting, cracking, bleeding, patching, and ravelling, which gradually affects the surface layer over time. It is essential to assess the condition of pavements as it not only ensures their usability but also maximises public safety. Effective pavement maintenance requires substantial resources and capital investment to carry out the most suitable maintenance treatments at the optimal time. Furthermore, the outcomes of pavement inspections play a crucial role in making informed decisions regarding pavement maintenance planning. These decisions include considerations of costs, maintenance expenses, and long-term investment schemes in road infrastructure. By conducting inspections of pavement surfaces, authorities can accurately identify the maintenance requirements and allocate resources effectively to extend the lifespan of pavements, enhance their performance, and minimise potential hazards to road users.
DOI
https://doi.org/10.21427/v9rz-6b31
Recommended Citation
Hassam, Syed Ibrahim, "Assessing the Condition of Pavements (Road Surfaces) using Computer Vision & Machine Learning" (2024). Doctoral. 148.
https://arrow.tudublin.ie/engdoc/148
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 4.0 International License.
Publication Details
This dissertation is submitted for the degree of Doctor of Philosophy. School of Computer Science, Technological University Dublin, 2024.
doi:10.21427/v9rz-6b31