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Enterprise IoT

home/Reference/Enterprise IoT
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  • What is Internet of Things
  •  IoT Architecture, Components And Stack View
    •   Device Layer
      • Sensors
      • Actuators and Prototype devices
    •   Communication Layer and Communication Strategy
      • Communication Protocols
      • Application Protocols
      • Industry Protocols
    • Core Platform Layer
    • Analytics Platform Layer
    • Cognitive Platform Layer
    • Solutions Layer
    • IoT Security And Management
  •  Application Of IoT In Manufacturing
    •   Monitoring & Utilization
      • Asset Management
      • Instrumentation
      • Handle Connectivity
      • Perform Monitoring
    • Condition Based Maintenance
    • Predictive Maintenance
    • Optimization
    • Connecting ‘Connected Solutions‘
    • IoT Strategy for Connected Car Use Case
    • IoT Strategy for Connected Home Application
  •  Building Application With Microsoft IoT Platform
    •   Azure IoT Implementation Overview
      • Building Machine Learning Models
      • Integrating Machine Learning Models with Real-time Flow
  •  Building Application With IBM IoT Platform
    • Connected Elevator Solution Using IBM IoT Stack
  •  Building Application With Amazon IoT Platform
    • Connected Car Solution Using Amazon IoT
  •  Building Application With GE Predix IoT Platform
    • Connected Elevator Solution Using Predix IoT Stack
  • Building Application With Open Source IoT Stack
  • IoT Cloud Provider Comparison Chart

Integrating Machine Learning Models with Real-time Flow

navveen

Integrating Machine Learning Models with Real-time Flow

Once our machine learning model is ready, as the last step we integrate the machine learning model with the runtime flow as shown below.

We added one more event handler to the existing flow, which calls our predictive model Azure ML service through the API. Based on the response, if maintenance is required the event handler invokes an external request to maintenance workflow system to initiate a work order for repair. The integration of driver behavior analysis is pretty much the same and in this case, the output goes to mobile and the web instead of a maintenance request.

This complete the Azure IoT implementation

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  • IoT Cloud Provider Comparison Chart
  • Building Application With Open Source IoT Stack
  • Connected Elevator Solution Using Predix IoT Stack
  • Building Application With GE Predix IoT Platform
  • Connected Car Solution Using Amazon IoT
  • Building Application With Amazon IoT Platform
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