Anomaly detection is a critical element of recognizing abnormal behavior. To accurately identify anomalies, it is essential to understand what is considered normal. Structured and normalized data allows algorithms, such as machine learning, to learn the typical behavior of each data metric. Custom anomalies provide greater configurability for your equipment. Custom anomalies enable you to set alerts for any NQRL condition and adjust and optimize thresholds.
They also use the same advanced adjustment settings as static alerts, so you can ensure that your team only receives notifications about important anomalies. For instance, a car engine may have 20 sensors that generate 20 different signals such as rotation, fuel pressure, rolling, etc. Individually, these readings may not indicate any problems at the system level, but when taken together they can provide an indication of the engine's state. When the interaction of these signals deviates from the usual range, multivariate anomaly detection can detect the anomaly like an experienced expert. AI models can be trained and customized using your data to meet the unique needs of your company.
With the new Anomaly Detector APIs, developers can easily integrate multivariate time series anomaly detection capabilities into predictive maintenance solutions, AIOps monitoring solutions for complex business software, or business intelligence tools. The power of AI-driven anomaly detection lies in its ability to detect patterns in data that are too complex for humans to recognize. By leveraging AI-driven anomaly detection, businesses can quickly identify and address potential issues before they become costly problems. AI-driven anomaly detection can also be used to identify opportunities for improvement in existing processes or systems. For example, AI-driven anomaly detection can be used to identify areas where processes are inefficient or where there are opportunities for cost savings. AI-driven anomaly detection is a powerful tool that can help businesses stay ahead of potential issues and maximize efficiency.
By leveraging custom AI models and Anomaly Detector APIs, businesses can quickly identify and address potential issues before they become costly problems. With AI-driven anomaly detection, businesses can unlock the power of AI to enhance their operations and maximize their efficiency.
