a scalable Event HUB to collect data
SenteticSense can extracts data directly from your database or enterprise asset management system. SenteticSense works with any equipment-connected sensors and requires only a few to activate machine learning.
A Machine Learning predictive engine
SenteticSense use existing historical data to identify unseen anomalies, predict future faults, classify assets based on operational behavior, rank individual assets performance in homogeneous groups, provide maintenance, scheduling tasks based on priority classes, optimize periodical maintenance activities.
A RESTful API for data integration
SenteticSense extract non trivial correlation between operating condition and assets behaviors. Our predictive engine analyzes and builds a forecasting model of operating condition, compares real time data to the predicted condition and notifies OSS if there is an anomaly condition.
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Optimization for Deep learning highlights in 2017 https://t.co/R5P4SHeJ1J
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles https://t.co/RJqdWIuAQ0