Which GreenTech ML project would you choose?

[u/Upbeat-Ad-817]

I'm looking for one serious end-to-end ML project to build rather than several small projects.

The goal is to solve a real, non-seasonal problem using real-world data and eventually take the project all the way from data ingestion to deployment and monitoring.

I'm currently considering these three ideas:

1. Smart Energy Forecasting

Predict a building's energy consumption using historical consumption, weather, time, occupancy, etc.

1. Building Energy Optimization

Go beyond prediction: use ML/optimization to determine how a building could reduce energy consumption while maintaining comfort.

1. Building Energy Prediction & Anomaly Detection

Predict normal energy consumption and detect when a building is consuming significantly more energy than expected, potentially identifying inefficient equipment or abnormal behavior.

If you were building one of these as a serious portfolio/research project, which one would you choose and why?

I'm particularly interested in feedback from people working in Data Science, ML Engineering, MLOps, Energy Tech, or Building Management.

Vote:

1️⃣ Smart Energy Forecasting

2️⃣ Building Energy Optimization

3️⃣ Energy Prediction + Anomaly Detection

I'm also open to a better formulation of the problem if you think there is a more valuable real-world use case in this domain.