Sustain-a-Buy

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Sustainable Alternatives recommedation
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Inspiration

With the increasing impact of consumerism on climate change, we wanted to make sustainable shopping effortless. Many consumers want to make eco-friendly choices but lack the tools to assess the environmental impact of their purchases. We were inspired to bridge this gap by creating a Chrome extension that provides real-time sustainability insights while users shop on Amazon.

What it does

Sustain-a-Buy analyzes the carbon footprint of products on Amazon and suggests greener alternatives. When a user views a product, the extension extracts key details such as materials, production methods, and shipping information. It then estimates the CO₂ emissions and sustainability score using AI and sustainability databases. If a more eco-friendly alternative exists, Sustain-a-Buy presents users with better options, helping them make more informed, sustainable choices.

How we built it

Technologies Used: React, Tailwind CSS (for the frontend), and JavaScript for Chrome extension functionality. Data Processing: We use Google Gemini AI and web scraping tools to estimate carbon footprints. Amazon Product Extraction: The extension scrapes product details directly from Amazon or uses the Amazon Product Advertising API when available. AI-Powered Recommendations: We leverage large language models like Gemini to predict and calculate sustainability scores and predict alternatives. UI/UX Design: The extension seamlessly integrates into the Amazon shopping experience, providing real-time insights without disrupting the user’s browsing.

Challenges we ran into

Amazon Integration: Scraping data from Amazon comes with limitations, and using their API required handling rate limits and authentication. Ensuring User-Friendly Design: We had to balance providing in-depth sustainability insights without overwhelming the user with too much information. Mixing all our code together: Merging our code together was very difficult as we originally worked on different features in different ways and tried to combine that.

Accomplishments that we're proud of

Successfully integrating sustainability insights into Amazon without disrupting the user experience. Building a functional prototype that provides real-time carbon footprint estimates and greener alternatives. Creating an AI-powered recommendation system that helps users make more sustainable choices. Overcoming technical challenges to make sustainability data accessible in a simple and actionable way.

What we learned

The complexities of analyzing product sustainability and the importance of reliable data sources. How to build a Chrome extension that interacts dynamically with an e-commerce website. The challenges of balancing real-time data processing with performance optimization. How user behavior impacts sustainability decisions and the importance of clear, actionable insights. Utilize AI to help you changes the game FAST.

What's next for Sustain-a-Buy

User Customization: Allowing users to set sustainability preferences (e.g., prioritizing recycled materials or low-carbon shipping). Multi-Platform Support: Expanding beyond Amazon to other e-commerce sites like Walmart and eBay. Enhanced AI Predictions: Using machine learning to improve the accuracy of carbon footprint estimates and refine alternative recommendations. Gamification & Incentives: Rewarding users for making sustainable choices through badges or partnerships with eco-friendly brands. Keeping track of sustainabe purchases on an external website accompanying the extension that will give monthly analytics.