Predictive Condition Monitoring

Real-time, adaptive monitoring for physical machine and process anomalies that require no human intervention or understanding of underlying data Securely reads and upcycles physical machine data from existing OT systems, IoT platforms, devices, and sensors. An anomaly detection engine that self-configures and calibrates its behavioural analysis to best fit any physical machine and process, regardless of data type, frequency, or context.

Researcher
Dr. Ryan Heartfield, Sadaiyandi Ramadoss
Researcher