| Idea Name: |
Traffic Drones |
| Slogan: |
Drone deployment solution for traffic surveillance |
| Supervisor Name: |
Dr Tahir Nawaz |
| Supervisor Designation: |
Assistant Professor |
| Supervisor School: |
CEME |
| Supervisor Department: |
Mechatronics |
| Contact number: |
03335674843 |
| Email ID: |
[email protected] |
| Abstract: |
| Smart traffic management is pivotal to sustainable urban growth. This project aims to deploy UAVs in crucial city areas for aerial monitoring of traffic. Deep learning algorithms running onboard the UAV will help identify traffic choking points, violations of traffic rules, ineffective routes, and ultimately the road engineering flaws that make these problems arise in the first place. |
| What is the unmet need in society that your idea will fulfill ? |
| Poor traffic management causes inconvenience for people and for authorities who have to deal with traffic violations. |
| Who needs it ? How many would benefit ? |
| Commuters, drivers, everyone on the roads, and people who manage the traffic. |
| How will the solution works |
| Object tracking using fast, lightweight deep learning algorithms deployed onboard a UAV for real-time traffic surveillance. Vehicle trajectories help identify choking points, violations of traffic rules such as wrong parking and one-way traffic, and also road engineering flaws, and faulty routes.
|
| Who are your competitors ? How is your solution different |
| So far, drones for traffic monitoring have been introduced by the Sci&Tech ministry and traffic police department, but only at an experimental stage, and mainly just for data acquisition. The use of deep learning algorithms for data processing will be a new first if successfully implemented. |
| Status: |
new |
| Entry Date & Time: |
2022-12-30 (1334) |
