1st place at IIT-Roorkee Road-Safety Hackathon. 

OpenCV | Python | Utralytics | Object Detection

Developed 6 ML models for road-safety. Used YOLOv8 extensively.

1. People Counting (count&track pedestrians, optimize pedestrian crossings)

2. Pothole Detection (Identifying road defects, preventive maintenance)

3. Traffic Light Detection

4. Vehicle Speed Detection (identify traffic congestion points, aids signal adjustments etc)

5. Lane-Specific Vehicle Counting (manage bottlenecks)

6. Lane-Wise Vehicle Tracking (flags wrong-way vehichles, identifys vehicle types)

Code 💻 | Docs 📄

Qualified Internally in my college for a National Hackathon. Our problem statement was for a Steel Manufacturing Plant in India.

Computer Vision | OpenCV | Figma | OCR | React

Developed an interactive dashboard for
Rashtriya Ispat Nigam Limited, Visakhapatnam Steel Plant

We performed OCR on the handwritten digits on the sides of the ladels, used IoT sensors to track the ladle and finally sent this information to a React Dashboard to enable analytics and improve the operational efficiency of the Steel Plant

Video Presentation: 

https://youtu.be/bU3Zb2ylDVY?si=6yXorjSNEOMcDfOz

Created a model that detects your face and sends the metadata to the lab’s server via an API for logging purposes.

DLib | Tensorflow | OpenCV | PyCharm | RestAPI’s | CMS

Transitioned away from the Bar-Code scanning attendance system towards the face-recognition attendance system.

Code 💻 | Docs 📄