The EMBERS architecture for streaming predictive analytics
A Doyle, G Katz, K Summers… - … conference on big …, 2014 - ieeexplore.ieee.org
2014 IEEE international conference on big data (big data), 2014•ieeexplore.ieee.org
Developed under the IARPA Open Source Initiative program, EMBERS (Early Model Based
Event Recognition using Surrogates) is a large-scale Big-Data analytics system for
forecasting significant societal events, such as civil unrest incidents and disease outbreaks
on the basis of continuous, automated analysis of large volumes of publicly available data. It
has been operational since November of 2012, delivering approximately 50 predictions
each day. EMBERS is built on a streaming, scalable, share-nothing architecture and is …
Event Recognition using Surrogates) is a large-scale Big-Data analytics system for
forecasting significant societal events, such as civil unrest incidents and disease outbreaks
on the basis of continuous, automated analysis of large volumes of publicly available data. It
has been operational since November of 2012, delivering approximately 50 predictions
each day. EMBERS is built on a streaming, scalable, share-nothing architecture and is …
Developed under the IARPA Open Source Initiative program, EMBERS (Early Model Based Event Recognition using Surrogates) is a large-scale Big-Data analytics system for forecasting significant societal events, such as civil unrest incidents and disease outbreaks on the basis of continuous, automated analysis of large volumes of publicly available data. It has been operational since November of 2012, delivering approximately 50 predictions each day. EMBERS is built on a streaming, scalable, share-nothing architecture and is deployed on Amazon Web Services (AWS).
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