Azadegan-OloomTahqiqat-1 Computer Vision Project

Here are a few use cases for this project:

1. Road Maintenance: Municipal or state organizations responsible for road maintenance can utilize this model to automatically detect different levels of road distress such as high or low rutting, high or low corrugation etc. This can help prioritize maintenance efforts and allocate resources more efficiently.

2. Infrastructure Planning: Urban planners or civil engineers could use this model to gather data on road conditions for infrastructure planning. Detailed information on pavement distress can help in decision-making in terms of repairs, reallocation of routes, or infrastructure development projects.

3. Automated Driving System: The Azadegan-OloomTahqiqat-1 model could be integrated into autonomous vehicles' navigation system, aiding them in identifying road conditions and automatically adjusting their driving patterns, such as speed and lane use, for improved safety.

4. Insurance Claims: Insurance companies can employ this model to verify claims related to car damages from road conditions. By identifying the road distress classes, insurers can validate if the reported damages are aligned with the type and level of road wear.

5. Research and Studies: Researchers studying urban development, road infrastructure, or transportation engineering could use Azadegan-OloomTahqiqat-1 to facilitate their research work, providing a quicker and more detailed analysis of road conditions.