Machine Condition Monitoring using IoT Technology Workflow

Detect Anomaly

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The Detect Anomaly business workflow step is designed to identify unusual patterns or discrepancies in data that may indicate an issue within a process. This step utilizes advanced analytics and machine learning algorithms to detect anomalies that could be indicative of fraud, errors, or other problems. During this stage, the system analyzes data from various sources, including transactions, user interactions, and sensor readings. The detected anomalies are then prioritized based on their potential impact and severity, allowing the business to quickly respond to critical issues. The output of this step is a list of identified anomalies, along with suggested actions for remediation. This information is used by other workflow steps to trigger further investigation or corrective action, ensuring that problems are addressed in a timely and effective manner.