Eugenie processes the asset data captured from the industrial IoT networks in
the form of a time series of sensor readings, which are then used to monitor the
asset condition remotely. Our machine learning models utilize a large amount of
data to learn the patterns corresponding to the behavior of the assets. These models
can then be used for different tasks like generating forecasting, rare events detection,
causality analysis, etc.
Eugenie utilizes a unique approach involving neural network architecture in a streaming
data pipeline for univariate and multivariate time-series data.