Data models related to the Environment. Includes data models for Weather, Environment & etc.

Standard ML Waste Management using CNNs for Waste Identification, RNNs and LSTMs for Waste Generation Prediction, and Reinforcement Learning for Route Optimization

Commander4j Production Recording and Labelling using EAN128 barcodes. Now includes Weight Checks, Waste Logging, Quality Control and much more. Supports mySQL, MS SQL Server and Oracle Databases. Java Swing Client and Javascript web pages for Zebra/Morotolla/Symbol wireless mobile computers.

Textile Ledger, A web application that incentivizes people to properly dispose of textile waste through crypto rewards.

WasteAI: Snap, Sort, Succeed || Waste Segregation

Waste AI: Snap, Sort, Succeed || Waste Segregation

platform for annotation of images, training an object detection model (fixed model, different datasets), running detection with pre-trained and in-app trained models, reviewing detection result on a georeferenced map. specialized for waste detection. management of legal landfills through input waste form and 3D point cloud scans.

From Waste to Feed | Insect Biotech Research Group

Personal website

🗑️ Wealden Bin Collection integration for Home Assistant retrieves and displays bin collection dates for the Wealden District Council area. This custom integration keeps track of refuse, recycling, and garden waste collection dates, allowing users to create automations for reminders or other actions.

Trash Object Detection & classification API based on YOLOv8

🗑️ Product lifecycles, waste management, and the impact of non-recyclable materials on garbage accumulation and disposal.

Muelli.app: The webbased application supports the citizens of "Landkreis Konstanz" in Germany to dispose the waste properly and to find the nearest recycling station.

The Project promising solution to revolutionize waste management. By leveraging IoT technology, it enables real-time monitoring, efficient resource allocation, and data-driven decision-making. also it has the potential to contribute significantly to environmental sustainability and improve the overall quality of waste management systems.

Jätekukko Omakukko API client

Waste-sorting made easy with AI

This project implements a custom CNN model for waste classification (battery, plastic, etc.) into 12 categories. Trained on image data, it achieves 80.03% accuracy.

Django-based web application designed to enhance efficiency in waste management

NNGC Front End React TypeScript Vite MUI