| Idea Name: |
Pavement Monitoring |
| Slogan: |
drones, the future is now! |
| Supervisor Name: |
Dr. Khurrum Kamal |
| Supervisor Designation: |
Associate Professor |
| Supervisor School: |
PNEC |
| Supervisor Department: |
Mechanical Engineering |
| Contact number: |
+92 335 3309916 |
| Email ID: |
[email protected] |
| Abstract: |
| We are proposing a digital process of accommodating inspection of roads in terms of time and
efficiency. Performing detection of road cracks via drone and producing its summarized reports.
|
| What is the unmet need in society that your idea will fulfill ? |
| Road surveys are performed manually by detecting, localizing, and recording significant and
insignificant road damages, which become a nuisance and compromise quality. Lack of technology,
knowledge, and funds for equipment for data collection and analysis creates unnecessary hassle. |
| Who needs it ? How many would benefit ? |
| Roads and Highway construction companies need to implement an automated evaluation of road damage instead of manual road surveys by localizing an entire road, closing it off to public use. This will save the public from the hassle, the labor from extensive manual surveys, and reduce overall time. |
| How will the solution works |
| The solution proposed is to use Raspberry Pi with a drone for imaging purposes. It collects defects on
the roads, from where we transfer all the relevant data as images to a cloud service. When data is received
at the cloud, it will be sent to a Machine Learning model, already deployed at the cloud server, which
generates outputs. Once it detects the desired result, it will display the work on a mobile app and website. Meanwhile, it will also create reports of the conditions of the road. |
| Who are your competitors ? How is your solution different |
| Currently, in Pakistan, there is no such competition in this field. Students have attempted research to train models to detect roads, but no proper prototype was built that serves the purpose as we are pitching. |
| Status: |
new |
| Entry Date & Time: |
2021-12-13 (1735) |
