SUSTAINEDAWAY

Scan. Verify. Choose Sustainable.

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Inspiration# Project Story – SustainedAway

About the Project

SustainedAway was inspired by a simple but recurring problem we observed in everyday life: although people want to choose sustainable and eco-friendly products, they rarely have the right information at the moment of purchase. Most products carry labels such as eco, green, or natural, but these claims are often unclear, inconsistent, or misleading. This gap between sustainability awareness and actual purchasing decisions motivated us to build a system that provides instant, reliable sustainability insights exactly when decisions are made.

SustainedAway is an AI-powered web and mobile platform that enables users to scan a product or a shopping bill and instantly receive sustainability scores, environmental and health impact insights, store ratings, location-based heatmaps, and anonymous community feedback. The goal of the project is to reduce greenwashing, promote transparency, and empower consumers to make responsible choices effortlessly.

What We Learned

Through this project, we learned that sustainability is not just a technical problem but also a behavioral one. Even well-intentioned consumers often make unsustainable choices due to lack of clarity and time constraints. We also learned how AI systems must be designed carefully to present complex insights in a simple, understandable manner.

From a technical perspective, we gained hands-on experience in:

  • Designing AI-assisted decision-support systems
  • Integrating frontend, backend, and cloud services
  • Handling unstructured inputs such as images and bills
  • Visualizing data using maps and heatmaps
  • Building scalable, modular system architectures

Equally important, we learned how to collaborate as a team, manage time under constraints, and iterate quickly based on feedback.

How We Built the Project

SustainedAway was developed as a modular, scalable system. The frontend was built using React to provide a clean and intuitive user interface. Users can upload product images or bills through the application. The backend integrates Node.js and Python, where the AI logic processes input data and extracts sustainability-related insights using the Gemini API.

We used Firebase Authentication for secure user access and Firebase Firestore as the primary database to store product data, user interactions, and community reviews. Mapbox / Leaflet was used to implement location-based store ratings and sustainability heatmaps, while Cloudinary handled media storage for uploaded images.

The system follows a rule-based evaluation layer to ensure consistency and fairness in sustainability scoring. Anonymous community feedback, termed Sustainavoice, was designed to encourage honest reviews without identity bias.

Challenges Faced

One of the major challenges was designing sustainability scoring logic that is both meaningful and easy for users to understand. Translating complex sustainability factors into a simple score without oversimplifying required multiple iterations.

Another challenge was integrating multiple technologies—AI services, mapping tools, authentication, and cloud storage—into a single, seamless workflow. Performance optimization and ensuring smooth user experience during real-time analysis were also critical concerns.

Additionally, presenting sustainability insights in a way that influences user behavior without overwhelming them was a key design challenge. Balancing technical depth with usability was a continuous learning process throughout the project.

Conclusion

SustainedAway represents our effort to bridge the gap between sustainability awareness and real-world action. By combining AI, community-driven transparency, and real-time decision support, the project demonstrates how technology can play a meaningful role in promoting responsible consumption. This experience has strengthened our technical skills, problem-solving abilities, and understanding of sustainability-driven innovation.

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