Intunebaselines by Wolkenman.nl

An MLOps pipeline for real-time industrial safety detection using YOLOv8, achieving 88.90% mAP_50 accuracy. Automates data ingestion, validation, and evaluation with MLflow, and integrates CI/CD for deployment on AWS using Docker, ensuring scalability, efficient updates, and robust safety compliance.

AI-powered computer vision system for real-time workplace safety monitoring. Detects people and PPE compliance (helmets, vests) using YOLO models with intelligent tracking and MP4 output.

OSHA-compliant Electrical Safety Training summary and certification covering PPE, arc flash hazards, and protection devices. (2025)

🦺 PPE Compliance Monitor Pro with Integrated Attendance System - Ultra-fast AI-powered workplace safety monitoring with comprehensive face recognition-based attendance tracking, real-time cancellation, and professional results analysis.

🔒 Lock Out Tag Out (LOTO) Management System - Professional Equipment Protection Frontend | Modern React application with multi-language support for managing lockout/tagout procedures

DEVELOPING AN AI-MACHINE LEARNING TOOL FOR WORKPLACE SAFETY

🛡️ A comprehensive web application built with Next.js for conducting systematic risk evaluations and root cause analysis. Features multi-step forms for project data collection, potential hazard assessment, immediate and basic cause identification, and corrective action planning.

🛡️ Protect AI outputs with JoySafety, an open-source framework ensuring content security and compliance for enterprise applications.

A real-time PPE detection model using YOLOv8 to identify safety helmets and vests for workplace monitoring.