Home Azure Telematics Solutions Automotive Data Ingestion Blueprint

Automotive Data Ingestion Blueprint

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Architecture overview of the components for this scenario

This example scenario builds a real-time data ingestion and processing pipeline to ingest and process messages from IoT devices (in general sensors) into a big data analytic platform in Azure. Vehicle telematics ingestion and processing platforms are the key to create connected car solutions. This specific scenario is motivated by the car telematics ingestion and processing systems. However, the design patterns are relevant for many industries using sensors to manage and monitor complex systems in industries such as smart buildings, communications, manufacturing, retail, and healthcare.

This example demonstrates a real-time data ingestion and processing pipeline for messages from IoT devices installed in vehicles. Thousands and millions of messages (or events) are generated by the IoT devices and sensors. By capturing and analyzing these messages, we can decipher valuable insights and take appropriate actions. For example, with cars equipped telematics devices, if we can capture the device (IoT) messages in real time, we would be able to monitor the live location of vehicles, plan optimized routes, provide assistance to drivers, and support telematics-related industries such as auto insurance.

For this example demonstration, imagine a car manufacturing company that wants to create a real-time system to ingest and process messages from telematics devices. The company’s goals include:

  • Ingest and store data in real time from vehicles sensors and devices.
  • Analyze the messages to understand vehicle location, and other information emitted through different types of sensors (such as engine-related sensors and environment-related sensors).
  • Store the data after analysis for other downstream processing to provide actionable insights (For example, in accident scenarios, insurance agencies may be interested to know what happened during an accident etc.)

Relevant use cases

Other relevant use cases include:

  • Vehicle maintenance reminders and alerting.
  • Location-based services for the vehicle passengers (that is, SOS).
  • Autonomous (self-driving) vehicles.

https://docs.microsoft.com/bs-cyrl-ba/azure/architecture/example-scenario/data/realtime-analytics-vehicle-iot?view=azurermps-4.4.1

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