Challenge:Developing and maintaining a “smart” solution without the need for a dedicated data science team on site to incorporate machine learning. Automated pattern recognition and analytics functionalities.
 
Obstacles to overcome:No two assets are identical, which requires a generalized machine learning software still able to capture individual anomalies to a high enough degree of precision and accuracy.
 
Solution:Purpose-built application for use in asset-intensive use cases.
 
Advantages: 
Drag-and-drop dashboards for real-time visualization of metrics like temperature, output current, torque trim, position, velocity, etc.
Machine learning capabilities, including automatic model training, parameter tuning, automatic anomaly detection, and individual asset-level models for maximum detection accuracy.
Customizable rules to trigger real-time SMS and email alerts about anomalies 24 hours a day.
Key performance indicator (KPI) monitoring
Inherent, industry-accepted security standards for device and system connectivity.