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What is Anomaly Detection For IoT Time-Series Data - A Survey about?
This article surveys anomaly detection methods for IoT time-series data, highlighting the challenges and complexities involved due to the rapid expansion of IoT. It discusses various types of anomalies, such as point, contextual, and collective anomalies, and their applications across different domains including industrial IoT, smart energy, and smart cities. The review aims to identify current challenges and potential research opportunities in the field of anomaly detection for IoT systems.
- Author
- Raden J. Udik Esbiantoro
- Language
- EN