Your climate investigation caught the City Council's attention. Now they want to tackle the city's built environment — the homes, offices, and public buildings that account for roughly 40% of energy use in most cities. That's where AI can make the biggest difference:
Use AI to find the most energy-wasteful buildings in the city — before anyone has to inspect them by hand.
Before we design an AI solution, let's understand why we need one.
Here are your city's buildings. Which ones are wasting energy?
To predict which buildings waste energy without visiting them, your AI system needs specific data inputs. In AI, these inputs are called "features" — think of them as clues that help the AI make predictions.
Select the 3 best clues for predicting building energy use:
Total building size in square metres
How hot or cold it gets where the building is
Altitude above sea level
Person or company who owns the building
How many stories tall the building is
When the building was constructed
Should your AI system compare buildings by total energy used, or energy per square metre?
How much energy the whole building uses
Energy score that accounts for building size
Now that you've designed your AI system, you need data that matches your plan — enough real building records for it to learn patterns.
We'll search a public database of real building energy records from the National Renewable Energy Laboratory (NREL).
🎓 Answer both to unlock your results:
Why can't cities just send inspectors to every building?
What does EUI measure?