The article reviews Machine Learning and Computer Vision methods for detecting cracks in concrete. It is the basis of automatic structural health monitoring and predictive maintenance.
Key findings
- Collection of guidelines for crack inspection using images and Machine Learning.
- Compare the evolution of traditional methods with Deep Learning.
- Addressing the problem of data diversity Real environment and standard assessment
Why this matters globally
Automated structural inspection systems can help reduce costs and increase the frequency of monitoring of bridges, buildings, and infrastructure around the world.
Thai researcher contribution
Tidarut Jirawattana-Somkul which is affiliated with Thailand according to OpenAlex data, co-authored by an international research team
Limitations to consider
This is a review article and affiliation information should be double-checked against the publisher's records before use in official documents. The results of the model also depend on the data set and on-site conditions.