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Smart Meter Data Pipeline with Analytics Dashboard

Approx. component budget: Rs. 1,500 - 5,000

Objective

Show how raw device data becomes clear information, and how well a simple model can forecast home energy use.

What you will build

A pipeline that collects electricity readings from a meter or a simulator, stores them, cleans them, forecasts the next day's use and shows bills and unusual usage on a dashboard.

Results you can expect

• Forecast error (MAPE) for next-day usage
• Detection of injected abnormal readings
• Pipeline throughput
• And a bill comparison with the actual meter bill

What you will learn

Time-series data, data cleaning, forecasting, storage choices, and dashboards.

Tools and notes

Python, MQTT, InfluxDB or PostgreSQL, Grafana, Prophet or scikit-learn, ESP32 with a PZEM sensor or a public smart-meter dataset.

Resume points from this project

• Built and tested Smart Meter Data Pipeline with Analytics Dashboard; objective: show how raw device data becomes clear information, and how well a simple model can forecast home energy use.
• Measured and analysed forecast error (MAPE) for next-day usage and detection of injected abnormal readings; wrote the report and presented the results in a viva. Add your own numbers: [x].

Replace [x] with your own measured results. Write only what you really did.

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