Real-time Insights to Action for Transportation

Innovation in transportation  is one step away if we are able to turn the torrent of networked sensor data into actionable insights. The proliferation of billions of connected transportation sensors, coupled with the power of in-memory analytics with Spark, makes this a reality.

Why InsightEdge?

Ingest and process streaming data from billions of sensors in real-time

  • Leverage real-time, horizontally scalable, lowlatency data grid to ingest sensor data from thousands of streams.
  • Analyze data-in-motion by applying correlation, predictive analytics and alerting models seamlessly.

Deploy sophisticated algorithms to predict failures, optimize routes and improve supply chain

  • Simulate network routes in real-time through inmemory data processing, cutting down simulation batch jobs from hours to seconds.
  • Predict failure of equipment, provide business users with field alerts by combining analytics results with transactional applications in the same clusterRDD/DataFrame API for an ultra-fast insight-to-action lifecycle.

Innovate on new revenue streams via extracting insights hidden in sensor data

  • Gain operational intelligence in real-time against live sensor data to optimize business outcomes.
  • Provide business users with full real-time visibility into the health and status of all edge and field components.

Use Cases

Flight Delay Prediction

Spark Streaming combined with Apache Kafka, which will simulate an endless and continuous data flow.

Taxi Price Surge

Real-time real-time analytics on a streaming geospatial data with InsightEdge Spark

Ready to give it a try?

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