OHealth

• OHealth specializes in diagnosing potential failures by analyzing machine attributes, operational conditions, and sensor data collected from the field.
• By leveraging historical sensor data, failure modes, component characteristics, operational parameters, past events, tags, and more, OHealth strives to provide faster and more accurate fault predictions.

• Fault prediction begins on the day of monitoring using rule-based algorithms readily available within the system.

• Through machine learning algorithms, OHealth continuously improves its predictions over time, with user labeling playing a crucial role in enhancing prediction performance.

• In addition to utilizing the existing fault libraries provided by WiserSense, OHealth can also integrate with external artificial intelligence systems for fault prediction purposes.