Built a data processing pipeline for home energy optimization in Phoenix Arizona where summers exceed 115F and efficient HVAC management saves 15-18% on electricity bills.

The pipeline:

• Reads temperature sensor data every 30 seconds from 6 sensors
• • Calculates rolling averages and detects anomalies
• • Generates pre-cooling schedules based on weather forecast API
• • Outputs control signals to the thermostat via MQTT
    Key challenge was processing real-time sensor streams efficiently on a low-power Intel N100 mini PC. Memory-efficient data structures matter when you have 6 sensors × 2 readings/minute × 24 hours of rolling data.

The anomaly detection caught a failing HVAC capacitor early. Energy draw was 15% higher than the learned baseline for 3 consecutive days.

More context — detailed walkthrough on Dev.to:
https://dev.to/ollijones/smart-plugs-and-peak-hour-ac-management-a-desert-dwellers-guide-2ja5

Anyone else building home automation data pipelines?

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