EcoSort - AI-Powered Waste Classification for Global Impact

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  EcoSort

Inspiration

The global waste crisis inspired EcoSort. With growing pollution, limited recycling, and confusion over waste sorting, EcoSort aims to simplify recycling decisions and drive positive environmental impact. By harnessing AI, we make eco-friendly choices accessible to everyone.

What it does

EcoSort uses AI to identify recyclable items from images, empowering users to sort waste correctly. Its analytics dashboard shows users their contributions toward reducing waste and tracks global progress in real time.

How we built it

EcoSort was developed using HTML, CSS, and JavaScript. We integrated OpenAI’s GPT-3 and GPT-4 Vision models to classify waste from images. The analytics feature calculates and displays cumulative impact across users.

Challenges we ran into

Challenges included ensuring accuracy in image recognition, managing data privacy, and optimizing the model’s performance to handle diverse waste items. Integrating the dashboard analytics also required careful design to be intuitive and impactful.

Accomplishments that we're proud of

We’re proud to have created an AI-driven tool that makes a real-world difference in recycling education. Achieving a functional and impactful analytics dashboard to engage users and encourage ongoing use was a big milestone.

What we learned

We learned the complexities of AI-based image classification, the importance of intuitive UI for broad accessibility, and the value of real-time data tracking to motivate global environmental action.

What's next for EcoSort - AI-Powered Waste Classification for Global Impact

Next, we’ll add functionality to detect microplastics in water, helping address a critical pollution issue. Future expansions may also include partnerships with environmental organizations for broader reach.

Built With

• css
• css3
• gpt
• html
• html5
• javascript
• openai