key operating parameters, and builds 3D monitoring profiles and digital twins of machines. Embedded artificial neural networks and deep learning models analyze this telemetry to detect early signs of degradation and generate automated failure warnings. The software is intended for manufacturing plants and other industrial operators seeking to minimize unplanned downtime, optimize spare-part replacement, and streamline maintenance planning. It integrates core technologies such as IoT data acquisition, predictive analytics, and digital twin modeling to support continuous, remote condition monitoring.