Adaptive Monitoring

Adaptive monitoring focuses on dynamically adjusting monitoring strategies to efficiently detect anomalies and concept drift in evolving systems, optimizing resource utilization while maintaining accuracy. Current research emphasizes developing online learning methods, such as collaborative learning algorithms and probabilistic forecasting models, to handle dependencies between monitored processes and quantify uncertainties in dynamic environments. This field is crucial for various applications, including healthcare, industrial process control, and cybersecurity, enabling timely interventions and improved system resilience by efficiently detecting critical events in resource-constrained settings.