Intel > Case Studies > A Smarter Brain for Your Train…

A Smarter Brain for Your Train…

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Technology Category
  • Processors & Edge Intelligence - Embedded & Edge Computers
Applicable Industries
  • Transportation
Applicable Functions
  • Logistics & Transportation
Use Cases
  • Edge Computing & Edge Intelligence
The Challenge

Have you ever felt overloaded by too much sensory input? The results can be problematic, even risky if you’re driving at the time. The same holds true for trains, ships, oil rigs, and many other industrial assets. The data processing challenges on these complex machines are growing rapidly as the number of sensors increases; yet so are the opportunities to transform operations by using all the available data effectively. A modern locomotive, for example, has as many as 200 sensors generating more than a billion data points per second.

About The Customer
With recent enhancements to the GoLINC mobile data center, GE and Intel are filling a critical gap in the Industrial Internet. They believe this open platform will help fuel analytics-driven innovation across many industries.
The Customer
GE Digital
The Solution

Through fast analysis, the torrent of data from these sensors can help monitor locomotive health in real-time so dispatchers and power planners can make better, faster decisions to improve utilization and mission outcomes. The data can also be used to predict on-board problems and make quick adjustments, such as reducing speed so a train can make it home before a critical part fails.

Data Collected
Asset Utilization, Fault Detection, Speed, Vehicle diagnostics , Vibration
Operational Impact
  • [Management Effectiveness - Data Analysis]
    Smarter, faster decision making
  • [Cost Reduction - Data Management]
    Efficient, low-cost data transmission.
  • [Efficiency Improvement - Management]
    Simpler and more efficient management.
Quantitative Benefit
  • Operators can detect and respond to issues instantly, before they escalate into more serious problems.

  • High-volume data transfers are performed at stations to take advantage of fast, low-cost Wi-Fi connections. Given the size of the data sets, the savings can be substantial.

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