AI-Powered Energy Forecasting for Smarter Indian Homes was inspired by the rising inefficiency in energy consumption across Indian households. Our solution uses AI to predict short-term energy demand, detect anomalies, and optimize electricity usage for greener, more sustainable homes. We built it by collecting historical consumption data, training IBM’s Time Series Foundation Models for accurate predictions, and developing real-time forecasting dashboards with anomaly alerts. Challenges included handling incomplete data and ensuring model accuracy for the unique needs of Indian homes. We're proud of our success in predicting energy demand and providing actionable insights to users. Through this project, we learned the importance of clean data and user-centric design. Moving forward, we aim to scale this solution to commercial buildings, integrate IoT for real-time adjustments, and enhance renewable energy integration.
Built With
- ai
- awss3
- chartjs
- cloudservices
- datavisualization
- docker
- energyforecasting
- flask
- flask**-for-the-backend-api
- github
- github**-for-version-control
- google-colab**-for-collaborative-development
- googlecolab
- heroku
- heroku**-for-deployment
- ibm-watson-studio**-and-**aws-s3**-for-cloud-services
- ibmwatsonstudio
- javascript
- javascript-(react.js)**-for-the-frontend-dashboard
- keras
- machine-learning
- mongodb
- mongodb**-and-**postgresql**-for-data-storage
- plotly
- plotly/chart.js**-for-visualizations
- postgresql
- python
- react
- tensorflow
- tensorflow/keras**-for-ai-model-training
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