WASTE SEGREGATION - AIML Project

Overview

This project leverages Artificial Intelligence and Machine Learning (AIML) technologies to address the critical issue of waste segregation. By developing intelligent systems that can automatically classify and segregate waste using image recognition, we aim to promote efficient waste management and environmental conservation.

Features

1. Waste Classification: Machine learning models to classify waste into categories such as recyclable, organic using images

Technologies Used

1. Programming Languages: Python
2. Machine Learning Frameworks: TensorFlow

Dataset

The project will utilize datasets from various sources, including:

1. Public datasets on different types of waste images.
2. Custom datasets created through image collection and labeling.
3. Data from waste management facilities.

Usage

1. Data Collection: Gather images of different types of waste.
2. Data Preprocessing: Clean and preprocess the images for analysis.
3. Model Training: Train machine learning models on the preprocessed images.
4. Save the model.
5. Evaluate the model accuracy.
6. Use the model for classifying more images of trash.