Automated anomaly precursor detection

An anomaly precursor detection system, comprising:

• a data receiving circuit configured to receive time series data from a plurality of sensors in substantially real-time;
• a storage circuit configured to store the time series data from the plurality of sensors received via the data receiving circuit;
• a processor device configured to implement:
• a data organizing routine configured to organize time series data into an input data structure stored in memory blocks, the input data structure maintaining an association between instances identified in the time series data and respective sensors,
• a data analysis routine configured to analyze the input data, using a trained neural network that preserves associations between respective sensors and time series data, to identify a precursor event candidate based on a learned relationship between instances and respective sensors,
• an anomaly identification routine configured to identify an impending anomaly candidate from a database of historical anomalies, the impending anomaly candidate being identified based on the precursor event candidate, and
• an alert subsystem configured to generate an alert indicating an impending anomaly event, the alert identifying a type of the impending anomaly event based on the database of historical anomalies.

A non-transitory computer readable storage medium comprising a computer readable program for anomaly precursor detection, wherein the computer readable program, when executed by a processor device, causes the processor device to perform the method of:

• organizing time series data into an input data structure stored in memory blocks, the input data structure maintaining an association between instances identified in the time series data and respective sensors;
• analyzing the input data, using a trained neural network that preserves associations between respective sensors and time series data, to identify a precursor event candidate based on a learned relationship between instances and respective sensors;
• identifying an impending anomaly candidate from a database of historical anomalies, the impending anomaly candidate being identified based on the precursor event candidate;
• and
• generating an alert indicating an impending anomaly event, the alert identifying a type of the impending anomaly event based on the database of historical anomalies.