AUTOMOTIVE & MOBILITY

Connected Vehicle Telemetry Platform

Built an event-driven IoT telemetry architecture streaming 1.8 billion daily data points from 120,000+ connected vehicles with sub-5 second P99 end-to-end latency.

1.8B Events/Day120K Vehicles< 5s p99 Latency
Key Takeaways
- AWS IoT Core and Apache Flink stream processing ingested 21,000 events/second with sub-500ms safety alert routing.
- Delta Lake on Amazon S3 stores 2.8 PB of vehicle telemetry with time-travel query support for predictive warranty analytics.
- Real-time driver safety scoring enabled fleet operators to reduce high-risk driving incidents by 44%.

The Challenge

An automotive OEM collecting telemetry from 120,000 vehicles used a legacy batch processing pipeline with 6-hour data latency. Emergency collision and airbag alerts were delayed by hours, preventing real-time roadside emergency assistance.

Architecture & Technical Approach

  • MQTT Telemetry Ingestion: AWS IoT Core authenticates vehicles via X.509 certificates and publishes events into Amazon Kinesis streams.
  • Real-Time Stream Processing: Apache Flink processes event streams, routing critical safety triggers to emergency dispatch in under 500ms.
  • Delta Lake Lakehouse: Stores compressed telemetry on S3 for Spark SQL analytics, battery degradation modeling, and warranty validation.

Quantitative Benchmarks & Results

Platform CapabilityLegacy 6-Hour BatchStreaming Delta LakehouseReliability Lift
Safety Alert Dispatch Latency3.0 Hours (Batch)< 0.5 Seconds (Real-Time)Instant Emergency Action
P99 End-to-End Ingestion Latency6 to 10 Hours< 5.0 SecondsNear Real-Time Fleet State
Fleet Capacity Scalability80,000 Vehicles1,000,000+ Vehicles12.5x Scale Headroom
Ingestion Data BacklogChronic Daily DelaysZero BacklogContinuous Real-Time Ingest

Production Reliability & Lessons Learned

Partitioning Kinesis streams strictly by vehicle chassis ID preserved per-vehicle sensor event ordering without requiring expensive distributed database locks.