Inside RecycloAI's Machine Learning





When we set out to build RecycloAI, one of the biggest challenges - and most exciting opportunities - was developing a machine learning model capable of identifying waste types from user-submitted images.

Here’s a look into how we approached this challenge.

 

  Problem We’re Solving

Improper waste disposal is a massive contributor to environmental degradation. Our goal was to create a system that could:

  • Accurately classify waste types like plastics, metals, organic, e-waste, etc.

  • Offer disposal or recycling instructions based on the result

  • Work fast enough to give real-time or near-instant feedback

     

    The Model Behind RecycloAI

We used a custom-trained YOLOv8 classification model, fine-tuned using a labeled dataset of waste images. The model was trained to recognize various categories, including: plastic, paper, glass and more. We trained the model using PyTorch and Ultralytics' YOLOv8 framework in Google Colab.

  

  Training Pipeline

Here’s a simplified version of our workflow:

  1. Dataset Preparation

    • Collected and manually sorted images into folders (by class)

    • Ensured a balanced dataset for fair training

    • Augmented data to prevent overfitting

  2. Model Training

    • Used YOLOv8-cls with torchvision transformations

    • Trained over several epochs with evaluation on validation data

    • Exported to TorchScript format for fast inference

  3. Deployment

    • Integrated the model in a FastAPI backend

    • Frontend (built in React + TypeScript) sends image - backend returns prediction

    • Based on result, the UI displays disposal instructions



 Challenges Faced

  • Training imbalance in early versions led to misclassification

  • Model needed retraining after tuning epochs, resizing images

  • Hosting model and managing API speed under limited hardware



 Final Thoughts

Building the machine learning side of RecycloAI taught me more than just coding - it taught me how to engineer solutions with purpose. The journey from data collection to deployment was full of learning curves, but the impact we aim for - cleaner environments, informed communities - keeps us moving.

Stay tuned for more updates, or reach out if you're passionate about AI, sustainability, or collaboration!










Comments

Post a Comment

Popular posts from this blog

Introducing RecycloAI: Smarter Recycling with AI-Powered Waste Recognition

 Smarter Recycling Starts Here:     Introducing RecycloAI A large portion of waste is not recycled at all . Bin contamination, confusion about materials, and lack of real-time guidance are just a few of the challenges that undermine effective recycling. As a result, millions of tons of potentially recyclable materials end up in landfills and oceans each year. That’s where RecycloAI comes in—an AI-powered solution that helps users identify and sort waste in seconds, boosting recycling accuracy and supporting a more circular economy.     The Problem "Waste is piling up—and we’re sorting it wrong." Every year, vast amounts of recyclable materials are lost due to improper sorting. Individuals want to recycle but often don’t know how (e.g., “Is this plastic #5 or #7?” ). Organizations face growing pressure to meet sustainability targets and avoid costly contamination fees. The result? A global recycling system overwhelmed by confusion and inefficiency...
Read more

♻️RecycloAI - Using AI to Drive Smarter Waste Disposal

Image
    Over the past few months, I’ve had the chance to work on a project that not only sharpened my technical skills but also opened my eyes to how tech can address real-world challenges. Introducing RecycloAI - an intelligent, AI-powered waste classification tool designed to help users identify different waste types and receive custom disposal or recycling instructions. 🧠 What is RecycloAI? RecycloAI is a web application that uses an AI trained model to recognize waste types from images - including plastics, metals, and more. Once a user uploads or captures an image of waste, the app analyzes it and suggests the best disposal method: recycle, compost, or dispose off. The goal is to reduce landfill waste by promoting smarter, more ...
Read more