Our project focuses on the comprehensive management and visualization of energy consumption data through a multi-faceted approach, integrating hardware, software, and data analysis techniques. We want to help empower users with a comprehensive toolset to monitor, analyze, and optimize their energy consumption. By collecting and visualizing real-time and historical data, implementing predictive modeling, and facilitating quick response through alerts, our project aims to enhance energy efficiency, reduce costs, and contribute to a more sustainable energy future. We were able to generate a dataset containing values such as current, voltage, active power and reactive power.
System Architecture
The project's objectives are
- Programming the Arduino to take analog Current and voltage values as input.
- To visualize graphically using Python the current, voltage and power consumption from household appliances.
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To use the ARIMA model(and try to compare the same with an LSTM neural network) to predict power consumption using time-series analysis.
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Making a website to display the readings and results to the user.
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Send telegram alerts to the user in case of anomalies in power consumption.
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Allow user access to history of consumption of energy.
Alert sent on Telegram upon Anomaly Detection in the Kaggle Dataset
Alert sent on Telegram upon Anomaly Detection in Our dataset
