Situational/Operational Awareness

New generation Big Data and Machine Learning Situational Awareness

Big Data and Machine Learning is enabling a new generation of Situational Awareness capabilities for government and commercial organizations. By increasing sensitivity to subtle indicators, these techniques can help identify developing situations early, improving operational efficiencies and responsiveness. Transforming data into actionable intelligence will help organizations see the big picture and bring clarity to complex scenarios.

Specific applications include:

  • Supply chain management with increasingly resilient shipping and warehouse logistics.
  • Command and control.
  • Disaster management and recovery in and out of the data center.
  • Everyday monitoring of market influencers – e.g., weather patterns likely to impact key crop yields.

More data can yield additional clarity on a situation in less time, separating critical response situations from false alarms. This enables fast, compliant recommendations of the appropriate SOP or early identification of new situations for which there is no established SOP.

BigR.io can help operationalize both established and newly-proven technologies to most effectively and reliably utilize a broader set of data inputs and indicators to most effectively capitalize on situational opportunities and avoid developing risks.

  • Big Data and Machine Learning technologies to address large fixed and streaming data sources such as social media or IoT sensor streams.
  • Data fusion technologies such as the BigR.io-developed Aardvark.
  • Integration with traditional Business Intelligence (BI) and Enterprise Resource Planning (ERP) systems.
  • Visualization for rapid awareness and action.

Project Capsule:

Our team worked with a public health agency to develop the Situational and Tactical Awareness Tool for their region. This project utilized Aardvark and other technologies to aggregate near-real-time operational data from regional and state-level organizations including:

  • Hospitals
  • First Responders
  • Emergency Management Agency

This aggregated view allowed coordinated routing and logistics during a large-scale emergency that may otherwise have overwhelmed any single hospital and laid the groundwork for syndromic surveillance — early detection of disease outbreaks or other widespread chemical or biological contaminations.

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