AIRoads

PROBLEM STATEMENT:

Bengaluru, a city with rich culture and heritage and amazing food. It is also known as the third slowest city in the world (based on data by TomTom traffic index). Traffic causes some serious issues like:

1) Delay in ambulance, prevents patients from getting proper treatment on time and sometimes can even cause death.

2) Delay in delivery of goods can cause delay in public projects, this can also lead losses and slower economic growth of the country .

3) Employees not being able to reach office on time, causing them to get fired.

4) School and college students end up reaching late for their classes, causing them to miss out on classes and causing backlogs.

OUR PROPOSAL:

1) Using the IBM MAX object detection model to detect number of vehicles and fine tune them to optimize changing traffic signals accordingly. 2) We use IBM MAX and MAX scene classifier models on satellite images to help the government make proper decision as to where to construct roads and how to distribute the traffic. 3) We will use DeepSeek R1 model to logically predict the traffic conditions and flow. 3) We will us Bangalore's Traffic Pulse (on Kaggle) dataset to fine tune the models.