smart electricity monthly bill predictor

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💡 Inspiration

Rising electricity costs and unpredictable monthly bills make it difficult for households to manage their expenses. Many people only realize high consumption after receiving their bill. We wanted to create a smart solution that predicts electricity bills in advance, helping users plan and reduce energy usage effectively.

⚙️ What it does

The Smart Electricity Monthly Bill Predictor estimates a user’s upcoming electricity bill based on:

Past consumption data Appliance usage patterns Seasonal variations

It provides:

📊 Monthly bill predictions ⚡ Energy usage insights 💰 Cost-saving suggestions 🛠️ How we built it Frontend: Built using simple UI (Streamlit / Web App) for easy user interaction Backend: Python for data processing Model: Machine Learning algorithms (like Linear Regression) to predict future bills Data Handling: Historical electricity usage data used for training Visualization: Graphs to show usage trends and predictions 🚧 Challenges we ran into Collecting and cleaning accurate electricity usage data Handling irregular consumption patterns Improving prediction accuracy for different households Making the interface simple for non-technical users 🏆 Accomplishments that we're proud of Built a working prediction model with good accuracy Created a user-friendly interface Successfully combined AI with real-life problem solving Helped users understand and control electricity expenses 📚 What we learned Practical application of Machine Learning in real-world problems Importance of clean and relevant data How user experience impacts adoption of technology Team collaboration and problem-solving under constraints 🔮 What's next for Smart Electricity Monthly Bill Predictor 📱 Mobile app integration 🔌 Real-time data from smart meters 🤖 Advanced AI models for better accuracy 🌱 Personalized energy-saving recommendations 🌍 Integration with smart home systems

Built With

• dart
• flutter
• supabase
• vscode