EcoSpend! is a fintech-inspired application created during TartanHacks2025 by two Dartmouth and two CMU students that empowers users to monitor and reduce their carbon footprint by analyzing purchase receipts. Utilizing AI-driven receipt parsing and SQL-based analytics, the platform provides real-time estimates of carbon emissions and calculates offset costs, promoting eco-conscious spending habits.
- AI-Powered Receipt Analysis: Upload receipts to extract purchase details using Google's Gemini AI.
- Carbon Emission Calculation: Estimate total CO₂ emissions based on product categories, materials, and transportation impact.
- Offset Cost Estimation: Calculate the cost to neutralize emissions using up-to-date carbon credit pricing.
- User Accounts & History Tracking: Secure login system with password hashing and a history of past carbon scores.
- SQL-Based Data Analytics: Aggregate carbon impact over time, view trends, and compare footprints across users.
- Minimalistic Fintech UI: Built with Streamlit, featuring a forest-inspired design for clarity and ease of use.
- Time-Series Data Visualization: Track carbon footprint trends over time with interactive charts.
- Frontend: Streamlit (Gradio-style UI)
- Backend: Python, OpenAI Gemini API
- Database: SQL (Scalable user authentication, carbon history tracking, and data storage for future analytics)
- AI Model: Google Gemini-1.5 Flash for receipt processing
- Data Visualization: Matplotlib & Pandas for trend analysis
First, clone the github repository. Then, setup a (virtual) python environment. Then follow the steps below.
pip install google-generativeai python-dotenv streamlit pillow matplotlib flask werkzeugpython3 -m streamlit run login.pyYou should see a local URL (something like "http://localhost:8501"). Open the URL in your web browser.
Contact: vtoolsid@andrew.cmu.edu, neil.bhavikatti.28@dartmouth.edu, jx.28@dartmouth.edu, bnajibmo@andrew.cmu.edu