Inspiration
Climate change, increasing carbon emissions, and the lack of awareness about sustainable living inspired us to build EcoTracker. We realized that many people want to adopt eco-friendly habits but do not have a simple way to measure their daily environmental impact. Our goal is to make sustainability easy, measurable, and rewarding.
What it does
EcoTracker is an AI-powered sustainability platform that helps users track eco-friendly habits, calculate their carbon footprint, monitor an Eco Score, and receive personalized recommendations to reduce their environmental impact. It also predicts future carbon emissions based on user behavior and motivates users through progress tracking, badges, and rewards.
How we built it
We developed EcoTracker as a web application using HTML, CSS, JavaScript, Bootstrap, Spring Boot, and MySQL. The backend processes user activities, calculates carbon footprints using standard emission factors, and stores the data securely. AI-based logic is used to generate personalized recommendations and future carbon footprint predictions, while interactive dashboards visualize the user's progress.
Challenges we ran into
The biggest challenge was designing an accurate carbon footprint calculation model using publicly available emission factors while keeping the application simple and user-friendly. We also worked on providing meaningful recommendations based on user activities.
Accomplishments that we're proud of
We successfully built a platform that combines habit tracking, carbon footprint calculation, AI-powered recommendations, future impact prediction, and an interactive dashboard into a single solution. We are proud of creating a practical solution that encourages sustainable living.
What we learned
This project helped us understand sustainability, carbon emission estimation, AI integration, full-stack web development, database management, and user-centered design. It also strengthened our teamwork and problem-solving skills.
What's next for EcoTracker
Our future plans include integrating IoT sensors for real-time monitoring, adding image-based waste classification, introducing community leaderboards and NGO partnerships, and launching a mobile application. We also plan to improve prediction accuracy using advanced machine learning models and expand EcoTracker for schools, colleges, workplaces, and smart cities.
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