PennyPlan

Inspiration

PennyPlan was inspired by the need for better budgeting tools in grocery shopping. Many people struggle to stick to their budgets, and the rising cost of groceries makes it essential to find ways to save money while shopping

What it does

PennyPlan helps users budget effectively while grocery shopping by allowing them to: Add Up Costs: Users can input prices of items in real-time as they shop, ensuring they stay within their budget. Scan Items: The app can scan items by their price tag to quickly retrieve prices and details about products Price Matching: PennyPlan helps users find better prices for items by comparing prices across different stores, ensuring they always get the best deal

How we built it

We developed PennyPlan by integrating YOLOv7 with Optical Character Recognition (OCR) technology to recognize text from price tags, making it easy to retrieve and match prices from various grocery stores. The app uses web scraping, powered by Selenium, to collect real-time data from grocery stores' online catalogs for price comparison. The backend was built using Python, while the frontend was designed with HTML, CSS, and JavaScript, ensuring a responsive and user-friendly experience.

Challenges we ran into

Data Collection: Gathering accurate pricing data from various grocery stores proved to be challenging, especially for real-time price matching. Combining various components that run on different platforms and dependencies. Limited knowledge of React and Flask to create a fully functional UI.

What we learned

The importance of user feedback in shaping app features and functionality. How to efficiently scrape and manage data from various sources for accurate price comparisons. How to apply machine learning to object recognition that leads to text recognition. How to create a full-stack web app with data flow