Anomaly Detection


Anomaly Detection is a broad term which covers a large number of use cases, generally refers to the activity of identifying unusual observations. We can use algorithms like isolation forest or local outlier factor to identify anomalies, but here we talk specifically about the detection of anomalies in IoT devices which generate time series data. This is extremely valuable because it allows to avoid or at least mitigate the damages. The goal is to prevent this from happening by early discovering future anomalies.


AI, Cognitive, Data Analyitics, Industry 4.0, IoT


Agrifood, Defence & Aerospace, Healthcare, Logistic & Transportation, Manufacturing, Waste & recycling
Azienda: Synapps