Anomaly Detection with IoT | Ira Cohen, Founder & Chief Data Scientist, Anodot | #IoTFounders E026
Ira Cohen, co-founder and Chief Data Scientist of Anodot, explains how his company uses autonomous machine learning to detect anomalies in time-series data for Industrial IoT and business monitoring. He details the shift from static thresholds to dynamic pattern recognition, citing use cases in automotive manufacturing and large-scale printing to illustrate predictive maintenance and quality control. Cohen also discusses the challenges of implementing AI analytics at scale, including the need for organizational process changes and the importance of user-friendly interfaces for non-technical executives.