Apache IoTDB for Intelligent Transportation — Architecture, Core Capabilities, and Industry Fit

The Data Infrastructure Problem Layer Often Overlooked When intelligent transportation is discussed, the focus typically falls on autonomous vehicles, smart signaling, and real-time routing. Rarely does attention turn to the data infrastructure layer that quietly sustains these systems— continuously ingesting millions of sensor readings per second , compacting years of telemetry into manageable storage, and serving operational queries in milliseconds while transportation systems operate at full speed. Yet in production environments, this invisible layer often determines whether an intelligent transportation platform scales successfully. Consider the data reality: A modern metro system operating 300 trains can generate ~414 billion data points per day A connected vehicle platform managing 1.6 million vehicles can produce ~20 TB of new telemetry every 24 hours These are not traditional data warehousing workloads. They are high-cardinality, high-velocity time-series problems that require