Vehicle Fleet Data Management - Efficiently Collecting Vehicle Telemetry with AWS IoT FleetWise
An explanation of collecting vehicle telemetry data with AWS IoT FleetWise. It introduces vehicle modeling, data filtering at the edge, and efficient data transfer to the cloud.
Challenges of Vehicle Data Collection
Connected cars generate large amounts of data every second from hundreds of sensors (speed, engine RPM, battery status, GPS position, acceleration, brake pressure, and so on). Sending this data from every vehicle to the cloud makes bandwidth costs and storage costs enormous. In addition, the signal definitions of a vehicle's CAN bus (Controller Area Network) differ by vehicle type and model, so standardizing the data is also a challenge. AWS IoT FleetWise (stopped accepting new customers on April 30, 2026) is a service specialized for collecting vehicle telemetry data. It provides signal standardization through vehicle models, intelligent data filtering at the edge, and efficient data transfer to the cloud.
Vehicle Models and Campaigns
A vehicle model is a schema that defines a vehicle's signal structure. You define the names, data types, and units of signals (speed, engine RPM, battery voltage, and so on) in the signal catalog, and assemble the hierarchical structure of the signals in the vehicle model. Signal definitions that conform to the VSS (Vehicle Signal Specification) standard are also supported. A campaign is a feature that defines the conditions and schedule for data collection. In addition to time-based collection (collecting all signals at 10-second intervals), you can define condition-based collection (only during hard braking, only when the battery level is low, only within a specific geographic area). The edge agent evaluates the conditions inside the vehicle and sends only the data that matches the conditions to the cloud, which leads to a reduction in bandwidth costs.
Data Storage and Analysis
Collected data is stored in S3 (for long-term storage of large volumes of data / batch analysis) or Timestream (for real-time queries / dashboards; Timestream for LiveAnalytics stopped accepting new customers on June 20, 2025). You can run SQL queries with Athena on data stored in S3 and use it for analyzing vehicle driving patterns, detecting signs of failure, and analyzing driver behavior. With the integration with SageMaker, you can also use it to build ML models with vehicle data (predictive maintenance, fuel efficiency optimization, training data for autonomous driving). Use cases include quality control at automakers (analyzing failure patterns of specific parts), operations optimization at fleet management companies (route optimization, fuel efficiency improvement), and telematics insurance at insurance companies (premium calculation based on driving behavior). Pricing is $0.60 per vehicle per month (US East (N. Virginia) Region, first 10,000 vehicles, per the calculation example on the AWS pricing page) plus usage-based charges for message processing (as of October 2026).
IoT FleetWise Pricing
IoT FleetWise pricing consists of the number of connected vehicles and the message volume. In addition to a connection fee of $0.60 per vehicle per month (per the calculation example on the pricing page, US East (N. Virginia) Region, first 10,000 vehicles), usage-based charges apply according to message volume (as of October 2026). Reducing the amount of data sent to the cloud with edge filtering is one of the effective cost optimization measures. For example, if you set up a campaign that sends data only during hard braking, you can reduce the data transfer volume compared with sending all the time. Choosing S3 as the storage destination costs less than Timestream and is suited to batch analysis.
Data Collection and Efficiency at the Edge
Vehicles produce huge amounts of sensor data, but sending all of it to the cloud makes communication volume and costs enormous. IoT FleetWise has a mechanism that selects data on the vehicle side (the edge) before sending it. With controls such as collecting data only when specific conditions are met and extracting only the signals you need, you can efficiently deliver only meaningful data to the cloud. For example, you can use it to collect only the surrounding data when an anomaly is detected. Smart filtering at the edge makes it possible to collect data from large vehicle fleets at a realistic cost.
Standardized Vehicle Modeling
Vehicles differ in sensor types and data formats depending on the manufacturer and vehicle type. If you handle this as is, each vehicle type needs its own processing, and management becomes complicated. IoT FleetWise defines the signals you want to collect as a standardized catalog and maps each vehicle's data to that common format. This allows you to handle data collected from diverse vehicle fleets in a unified form. When you add a new vehicle type, you can also map it to the common model and handle it. Data standardization becomes the foundation for consistently managing / analyzing a mixed vehicle fleet.
Using Analysis in the Cloud
Data aggregated from vehicles creates value when it is analyzed in the cloud. You can get a cross-cutting view of driving trends and vehicle conditions across the entire fleet. If you use each vehicle's data for predictive maintenance, which catches signs of failure and services vehicles before they break down, it leads to improved availability and cost reduction. If you collect quality-related data, you can also gain insights that help improve design and manufacturing. By bringing standardized data into an analytics platform and combining it with visualization and machine learning, you can support a wide range of decisions, from the operation of individual vehicles to the optimization of the entire fleet and product improvement.
Privacy and Security
Vehicle data may include information related to users' privacy, such as driving routes and driving behavior. For that reason, when collecting it, it is important to make clear which data you collect and for what purpose, and to obtain users' consent. You limit the data you collect to the scope needed for the purpose and avoid excessive collection. You protect the data with encryption and control who can access it. You also keep communication between vehicles and the cloud secure. While pursuing the value obtained from data, a design that protects users' rights and complies with applicable regulations is the prerequisite for trusted use of vehicle data.
Summary - Guidelines for Using IoT FleetWise
AWS IoT FleetWise is a service specialized for collecting vehicle telemetry data. Its main strengths are signal standardization through vehicle models, conditional data collection through campaigns, and bandwidth cost reduction through edge filtering. It is suited to automakers, fleet management companies, and insurance companies that are considering using connected car data.
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 FleetWise official page
- Amazon Timestream official page
- Amazon S3 official page
- AWS Documentation (official)
If this page and the official documentation disagree, treat the official documentation as authoritative.