An intelligent assistant that learns your daily travel habits to suggest the best routes, modes of transport, and timings—while considering traffic, cost, and environmental impact.

Optimizes your commute with personalized, real-time mobility recommendations.

Trains on open traffic‑speed datasets to predict congestion by hour.

Forecast urban traffic levels to aid commuters.

Assesses routes, traffic, and driver habits to suggest fuel-saving practices.

 Helps logistics and delivery services cut costs and emissions.

Our project is a physics/ML-based projectile motion inference calculator in which an ML model can predict the path of a projectile launched at a certain velocity and angle.

It's a physics inference project where time-position data is given, and every other aspect, such as initial angle, launch velocity, and drag coefficient, is predicted, and a graph is made.

Analyzes sensor data from vehicles to predict maintenance needs.

 Reduces breakdowns by identifying faults before they become critical.

An AI-powered system that monitors vehicle health across fleets using sensor data, predicting maintenance needs, optimizing repair schedules, and reducing downtime.

Ensures safer, more efficient transport operations with proactive maintenance intelligence.

Help ride‑share drivers anticipate high‑demand zones.

Time‑series clustering on pickup data to predict surge areas.

Forecast open parking spots in urban areas.

Regression on historical occupancy data to predict future availability.