School project · EE4211
Carpark Availability Prediction
Applied ML models to 5 months of real carpark data to predict availability near hawker centres, visualised as an interactive heatmap.
The problem
Drivers near busy hawker centres often circle for parking with no visibility into which nearby carparks are likely to be full at a given time of day.
What I did
Part of a 4-person team. Collected live carpark data via public APIs over 5 months, cleaned and structured it for model training, compared multiple ML approaches, and built a heatmap visualisation for carparks within 200m of hawker centres in Northern Singapore.
Outcome
Demonstrated that historical occupancy patterns are strong predictors of future availability. The heatmap proof-of-concept made the results immediately interpretable.