Developed a Predictive Maintenance System for industrial equipment using advanced machine learning and computer vision techniques. The system analyzes real-time sensor data and visual inputs to detect early signs of wear, failure, or malfunction, enabling timely interventions. This solution helps reduce downtime, extend equipment lifespan, and optimize maintenance schedules, resulting in significant cost savings and improved operational efficiency for manufacturing and industrial sectors.