ECOSCAN:AI Powered Waste Detection System

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Inspiration

With the rising problem of improper waste disposal and environmental pollution, we wanted to create an AI-powered solution that helps users easily classify waste and find sustainable alternatives. Our goal is to promote responsible waste management and recycling through technology.

What it does

ECOSCAN is an AI-powered waste detection system that:

Identifies waste types using deep learning. Determines whether an item is recyclable or non-recyclable. Suggests eco-friendly alternatives to reduce waste impact. Helps users make informed decisions about waste disposal.

How we built it

Frontend: Built with React and Next.js and TailwindCSS for a seamless and interactive user experience. Backend: Developed using Python with FastAPI, Openai & deepAi for handling AI model predictions and data processing. AI Model: Trained using PyTorch and ResNet50 on a curated dataset for accurate waste classification.

Deployment: Frontend hosted on Netlify. Backend API deployed using Render/Vercel/AWS (or your chosen platform). Model hosted on Google Colab/AWS Lambda for cloud inference.

Challenges we ran into

Dependency Issues: Faced issues installing torchvision, causing delays in AI model integration. Data Imbalance: Some waste categories had fewer images, requiring weighted sampling to improve classification accuracy. Train The Model: Pretrain Model do not send good accuracy so i have to train or you can say fine chune the model to get better accuracy Deployment Hurdles: Integrating the backend with the frontend and ensuring smooth API communication.

Accomplishments that we're proud of

Successfully trained a highly accurate waste classification model. Implemented a real-time AI-powered waste detection system. Designed an intuitive UI/UX to enhance user experience. Built a fully functional AI-powered waste management platform from scratch!

What we learned

Deep learning model optimization for better inference speed. Overcoming dependency conflicts and package management in Python. Efficient API integration between Next.js and FastAPI. Importance of user-friendly design for impactful AI-driven solutions.

What's next for ECOSCAN:AI Powered Waste Detection System

Mobile App Integration 📱 for easy waste detection on the go. Improved Model Accuracy by expanding the dataset and refining training techniques. Multi-Language Support to reach a global audience. Gamification & Rewards to encourage responsible waste management. Blockchain Integration for tracking and rewarding sustainable practices. 🚀 Join us in making the world a cleaner, greener place! 🌍♻️

Built With

• deepai
• fastapi
• mongodb
• next
• openai
• python
• pytorch
• react
• tailwindcss
• tenserflow
• typescript