[!NOTE]
AWS IoT FleetWise will no longer be open to new customers starting on April 30, 2026.
Explore the
Guidance for Connected Mobility on AWS
on how to build a solution with capabilities similar to AWS IoT FleetWise alongside the Reference
Implementation for AWS IoT FleetWise (“FWE”),
AWS IoT FleetWise is a service that makes it easy for Automotive OEMs, Fleet operators, Independent
Software vendors (ISVs) to collect, store, organize, and monitor data from vehicles at scale. The
Reference Implementation for AWS IoT FleetWise (“FWE”) provides C++ libraries that can be run with
simulated vehicle data on certain supported vehicle hardware or that can help you develop an Edge
Agent to run an application on your vehicle that integrates with AWS IoT FleetWise. You can then use
AWS IoT FleetWise’s to process the collected data, gain insights about the vehicle’s health and use
the service’s visual interface to help diagnose and troubleshoot potential issues with your
vehicles. Furthermore, AWS IoT FleetWise’s capability to collect ECU data and store them on cloud
databases enables you to utilize different AWS services (Analytics Services, ML, etc.) to develop
novel use-cases that augment your existing vehicle functionality. In particular, AWS IoT FleetWise
can leverage fleet data (Big Data) and enable you to develop use cases that create business value,
for example: improve electric vehicle range estimation, optimized battery life charging, optimized
vehicle routing, etc. AWS IoT FleetWise can be extended to utilize cloud computing capabilities for
use-cases such as helping to improve pet/child detection, Driver Monitoring System applications,
Predictive Diagnostics, electric vehicle’s battery cells outlier detection, etc. You can use the
included sample C++ application to learn more about the FWE, develop an Edge Agent for your use case
and test interactions before integration.
[!IMPORTANT]
As provided in the AWS IoT FleetWise Service Terms, you
are solely responsible for your Edge Agent, including ensuring that your Edge Agent and any
updates and modifications to it are deployed and maintained safely and securely in any vehicles.
AWS IoT FleetWise Architecture
AWS IoT FleetWise is an AWS service that enables automakers and fleet operators to collect, store,
organize, and monitor data from vehicles. Automakers need the ability to connect remotely to their
fleet of vehicles and collect vehicle ECU/sensor data. AWS IoT FleetWise can be used by OEM
engineers and data scientists to build vehicle models that can be used to build custom data
collection schemes. These data collection schemes enables the OEM to optimize the data collection
process by defining what signals to collect, how often to collect them, and most importantly the
trigger conditions (“events”) that enable the collection process.
Customers can define the data collection schemes to trigger based on a schedule or on specific
conditions such as, but not limited to: 1. Ambient temperature dropping to below 0 degree or 2.
Vehicle crosses state lines or 3. Active diagnostic trouble codes. These conditions are sent to the
vehicle through a set of documents called data collection schemes. In summary, your Edge Agent
collects the data of interest according to the data collection schemes and decoding rules as
specified by the OEM on the AWS IoT FleetWise Console.
The following diagram illustrates a high-level architecture of the system.
FWE receives two documents:
Decoder Manifest - this document describes how signals are collected from the vehicle, and will
include details such as, but not limited to: Bus ID, network name, decoding information, etc.
Data Collection Schemes - this document describes what signals to collect. It also describes
the condition logic that defines the enablement of the trigger logic that allows these signals to
be collected, for example, when Vehicle Speed > 100 km/Hr and Driver Seatbelt is Off and Ambient
Temperature < 0 degree C.
FWE Deployment & Supported Platforms
The functional flexibility of FWE and its use of dynamic memory allocation means that it cannot
reside in the real-time safety vehicle ECUs. FWE must also be connected to the internet and
preferably has access to a “good” portion of vehicle ECU data. OEMs have the flexibility to decide
where they can deploy their Edge Agent binary. Possible options include (if present):
FWE was built and tested on 64-bit architectures. It has been tested on both ARM and X86 multicore
based machines, with a Linux Kernel version of 5.4 and above. The kernel module for ISO-TP
(can-isotp) would need to be installed in addition for Kernels below 5.10.
FWE was also tested on an EC2 Instance with the following details:
AMI name: ubuntu-jammy-22.04-amd64-server-20241205
AWS IoT FleetWise Client-Server Communication
FWE depends on the AWS SDK for C++ to send and receive data
from and to AWS IoT FleetWise Server. All data sent to the AWS IoT FleetWise server is sent over an
encrypted
TLS connection using
MQTT, which is designed to make it secure by default while in transit. FWE uses MQTT quality of
service one (QoS = 1).
Reference Implementation for AWS IoT FleetWise
AWS IoT FleetWise now supports:
examples.AWS IoT FleetWise is a service that makes it easy for Automotive OEMs, Fleet operators, Independent Software vendors (ISVs) to collect, store, organize, and monitor data from vehicles at scale. The Reference Implementation for AWS IoT FleetWise (“FWE”) provides C++ libraries that can be run with simulated vehicle data on certain supported vehicle hardware or that can help you develop an Edge Agent to run an application on your vehicle that integrates with AWS IoT FleetWise. You can then use AWS IoT FleetWise’s to process the collected data, gain insights about the vehicle’s health and use the service’s visual interface to help diagnose and troubleshoot potential issues with your vehicles. Furthermore, AWS IoT FleetWise’s capability to collect ECU data and store them on cloud databases enables you to utilize different AWS services (Analytics Services, ML, etc.) to develop novel use-cases that augment your existing vehicle functionality. In particular, AWS IoT FleetWise can leverage fleet data (Big Data) and enable you to develop use cases that create business value, for example: improve electric vehicle range estimation, optimized battery life charging, optimized vehicle routing, etc. AWS IoT FleetWise can be extended to utilize cloud computing capabilities for use-cases such as helping to improve pet/child detection, Driver Monitoring System applications, Predictive Diagnostics, electric vehicle’s battery cells outlier detection, etc. You can use the included sample C++ application to learn more about the FWE, develop an Edge Agent for your use case and test interactions before integration.
AWS IoT FleetWise Architecture
AWS IoT FleetWise is an AWS service that enables automakers and fleet operators to collect, store, organize, and monitor data from vehicles. Automakers need the ability to connect remotely to their fleet of vehicles and collect vehicle ECU/sensor data. AWS IoT FleetWise can be used by OEM engineers and data scientists to build vehicle models that can be used to build custom data collection schemes. These data collection schemes enables the OEM to optimize the data collection process by defining what signals to collect, how often to collect them, and most importantly the trigger conditions (“events”) that enable the collection process.
Customers can define the data collection schemes to trigger based on a schedule or on specific conditions such as, but not limited to: 1. Ambient temperature dropping to below 0 degree or 2. Vehicle crosses state lines or 3. Active diagnostic trouble codes. These conditions are sent to the vehicle through a set of documents called data collection schemes. In summary, your Edge Agent collects the data of interest according to the data collection schemes and decoding rules as specified by the OEM on the AWS IoT FleetWise Console.
The following diagram illustrates a high-level architecture of the system.
FWE receives two documents:
Decoder Manifest - this document describes how signals are collected from the vehicle, and will include details such as, but not limited to: Bus ID, network name, decoding information, etc.
Data Collection Schemes - this document describes what signals to collect. It also describes the condition logic that defines the enablement of the trigger logic that allows these signals to be collected, for example, when Vehicle Speed > 100 km/Hr and Driver Seatbelt is Off and Ambient Temperature < 0 degree C.
FWE Deployment & Supported Platforms
The functional flexibility of FWE and its use of dynamic memory allocation means that it cannot reside in the real-time safety vehicle ECUs. FWE must also be connected to the internet and preferably has access to a “good” portion of vehicle ECU data. OEMs have the flexibility to decide where they can deploy their Edge Agent binary. Possible options include (if present):
FWE was built and tested on 64-bit architectures. It has been tested on both ARM and X86 multicore based machines, with a Linux Kernel version of 5.4 and above. The kernel module for ISO-TP (
can-isotp) would need to be installed in addition for Kernels below 5.10.FWE was also tested on an EC2 Instance with the following details:
AWS IoT FleetWise Client-Server Communication
FWE depends on the AWS SDK for C++ to send and receive data from and to AWS IoT FleetWise Server. All data sent to the AWS IoT FleetWise server is sent over an encrypted TLS connection using MQTT, which is designed to make it secure by default while in transit. FWE uses MQTT quality of service one (QoS = 1).
Security
See SECURITY for more information
License Summary and Build Dependencies
FWE depends on the following open source libraries. Refer to the corresponding links for more information.
Optional: The following dependencies are only required when the option
FWE_FEATURE_GREENGRASSV2is enabled.Optional: The following dependencies are only required when the option
FWE_FEATURE_VISION_SYSTEM_DATAis enabled.Optional: The following dependencies are only required when the option
FWE_FEATURE_ROS2is enabled.Optional: The following dependencies are only required when the option
FWE_FEATURE_SOMEIPis enabled.Optional: The following dependencies are only required when the option
FWE_FEATURE_STORE_AND_FORWARDis enabled.Optional: The following dependencies are only required when the option
FWE_FEATURE_CPYTHONis enabled.Optional: The following dependencies are only required when the option
FWE_FEATURE_MICROPYTHONis enabled.See LICENSE for more information.
Getting Help
Contact AWS Support if you have any technical questions about FWE.
Metrics
See Metrics for details, which Edge specific metrics exist and how they can be accessed.
Resources
The following documents provide more information about FWE.
The following documents provide more information about the cloud component of AWS IoT FleetWise.