On Demand: Data Centricity and Edge Decision Management: The IIoT Architecture for Intelligent Transportation Systems

Originally aired December 13, 2018

In today’s era of connected everything, intelligent transportation systems are poised to change how people live. Real-time information on traffic, road conditions, parking availability and more help to reduce congestion and create safer, more efficient commuting.

These data-driven connected systems create petabytes of data that must be rapidly processed and reacted to, in order to enable smarter decision making at the edge. 

Intelligent transportation requires a distributed architecture which eliminates single points of failure and ensures highly-reliable automation at or near locations and events of interest. The architecture must enable a robust bi-directional data flow of information from IoT sensors to targeted recipients. Architecting your system based on a framework created for autonomous systems will address these challenges as well as reduce risk and provide a faster path to safety certification.

Join technical experts from RTI, iSAHA and Phizzle for a live demonstration and to learn: 

  • Current challenges for intelligent transportation systems 
  • How a distributed approach using a databus for data in motion addresses the real-world challenges of autonomous vehicles and Integrated Corridor Management
  • Best practices in managing extreme data volume with an intelligent connectivity framework for edge computing 
  • How to bridge the cloud-to-edge continuum for intelligent transportation systems.