AWS IoT FleetWise
A fully managed service that efficiently collects, transforms, and transfers driving data and vehicle signals from connected cars to the cloud for analysis
Overview
AWS IoT FleetWise is a fully managed service that enables automakers and fleet operators to efficiently collect vehicle signal data from connected cars and transfer it to the cloud. It converts raw data from in-vehicle network protocols such as CAN bus and OBD-II into standardized formats for cloud transmission. Data modeling based on Vehicle Signal Specification (VSS) enables unified data structure analysis regardless of vehicle make or model. Intelligent edge-side data filtering transfers only necessary data, dramatically reducing communication costs and enabling data collection from fleets of millions of vehicles.
Vehicle Data Modeling and Signal Catalog
AWS states that AWS IoT FleetWise is no longer open to new customers and that existing customers can continue using the service (as of October 2026). FleetWise's core capability is vehicle signal data modeling. The Signal Catalog defines all signals available from vehicles (engine RPM, vehicle speed, battery voltage, tire pressure, etc.), and Vehicle Models map these to per-model configurations. Signals are managed hierarchically in a tree structure conforming to the VSS (Vehicle Signal Specification) standard, uniquely identified by paths like Vehicle.Powertrain.Engine.Speed. Data type, unit, minimum, and maximum values can be defined per signal. Signals common across multiple models (vehicle speed, GPS coordinates, etc.) need only be defined once in the Signal Catalog and reused, requiring only model-specific signal additions when onboarding new vehicle types. This standardized data model facilitates cross-model analysis and benchmark comparisons.
Intelligent Edge Data Collection
The Edge Agent is software installed in the vehicle, and AWS IoT FleetWise provides a reference implementation to help develop it. The Edge Agent reads signals from in-vehicle networks such as the CAN bus. The Campaign feature defines data collection conditions, enabling event-driven collection of only necessary data - such as "10 seconds of data before and after hard braking" or "a snapshot when battery voltage drops below threshold." Collection schemes include time-based periodic collection and condition-based event collection. With the campaign spoolingMode set to TO_DISK, the Edge Agent temporarily stores data in the vehicle while it is not connected to the cloud and automatically transfers it once the connection is reestablished (default OFF as of October 2026).
Large-Scale Fleet Operations and Data Utilization Patterns
A campaign is deployed to a single vehicle or to a fleet (a group of vehicles), and one operational approach is to roll out in stages to fleets grouped by region or model year. Each campaign sends collected data to one destination: an MQTT topic, S3, or Timestream. Data stored in S3 can be analyzed with SQL in Athena, and Timestream is a time series database for storing and analyzing vehicle data. Representative data utilization patterns include predictive maintenance (detecting component degradation trends for pre-failure replacement), driving behavior analysis (calculating safety scores from hard acceleration/deceleration frequency), and OTA update effectiveness verification (comparing fuel efficiency before and after software updates). Another option is a pipeline connecting FleetWise data to SageMaker for building anomaly detection models.
References (Official AWS Resources)
The primary sources for this page are the official AWS website and documentation. Check the official pages below for the latest specifications and pricing.
- AWS IoT Core official page
- Amazon Timestream official page
- Amazon SageMaker official page
- AWS Documentation (official)
If this page and the official documentation disagree, treat the official documentation as authoritative.