Mission Mode 5
Power to Predict: LINEAR REGRESSION
STORY
—
Liam always admired his dad — a city engineer who kept the power grid running smoothly. One evening, while reviewing schematics, his dad explained how each subline powers homes, hospitals, and traffic systems, and that misallocation causes waste or outages. Captain T joined them as TRIOE, the city's data-powered superhero, appeared to help analyze real-time energy patterns using cloud-powered linear regression.
30:00 / 30:00
Mission Objectives
Complete the AI workflow: upload data, select linear regression model, and test predictions for energy optimization.
Upload a file
Choose an AI model
Run and test
Choose Appropriate Model
Test Model (Hardcoded)
Adjust values and test energy predictions
Predicted Savings
Run test to see potential savings
Optimal temperature range: Not calculated yet
Test value: Click "Test" button to run prediction
Data
Energy Dataset
Comprehensive analysis of energy patterns across different facility zones. View or download the dataset for detailed insights.
Upload Data
Drag & drop your Excel file here
or
Excel files (.xlsx) only
Max file size: 10MB
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Serial Monitor
Python 3.9.0 (default, Oct 9 2020, 15:07:54)
[GCC 9.3.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
Waiting for test execution...
Click the "Test" button to run the linear regression analysis.
