Inspiration

With increasing concerns about climate change, we realized that most people are unaware of how their daily habits contribute to their carbon footprint. At the same time, productivity tools and AI assistants are widely used but rarely connected to sustainability. This inspired us to build a solution that combines both — helping users stay productive while making environmentally conscious decisions.

What it does

Ecobot is an AI-powered assistant that helps users manage daily tasks while tracking and analyzing their carbon footprint. It provides real-time insights, calculates a carbon score based on user activities, and suggests personalized, eco-friendly alternatives. By integrating productivity with sustainability, the app encourages users to adopt greener habits effortlessly.

How we built it

We built the application using a full-stack architecture. The frontend was developed using modern web technologies, while the backend was powered by Node.js with REST APIs. PostgreSQL was used to store user data and activity logs. We integrated AI capabilities to analyze user behavior and generate smart recommendations. The application is designed to be scalable and deployable on cloud platforms.

Challenges we ran into

One of the main challenges was designing an accurate yet simple carbon footprint calculation model that users can easily understand. We also faced difficulties in integrating AI-driven recommendations in a meaningful way rather than just providing generic suggestions. Ensuring smooth communication between the frontend, backend, and database in a limited time was another challenge.

Accomplishments that we're proud of

We successfully built a working prototype that combines AI, productivity, and sustainability into one platform. We are especially proud of the personalized recommendation system and the carbon scoring feature, which provide real value to users.

What we learned

Through this project, we learned how to design scalable full-stack applications, integrate AI into real-world use cases, and think critically about user experience and environmental impact. We also improved our teamwork and problem-solving skills under time constraints.

What's next for Ecobot

We plan to enhance the accuracy of carbon tracking by integrating external APIs, add voice assistant capabilities, and improve personalization using advanced machine learning models. Our long-term vision is to turn Ecobot into a comprehensive platform for sustainable living.

Built With

• express.js
• html
• javascript
• node.js
• openai-api-(if-used)
• postgresql
• python
• react-(or-your-frontend)
• rest-apis
• vercel