👉 The studied project focuses on developing an AI-driven predictive maintenance system for industrial machinery. This system utilizes machine learning algorithms to analyze real-time sensor data from equipment, identifying patterns and anomalies that indicate potential failures before they occur. By predicting maintenance needs proactively, the project aims to reduce downtime, lower repair costs, and enhance operational efficiency. The system integrates data from various sources, including IoT sensors, historical maintenance records, and environmental conditions, to provide actionable insights that enable timely interventions. This approach not only extends the lifespan of machinery but also optimizes resource allocation and improves overall safety in industrial settings.
