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Reference Implementation for AWS IoT FleetWise
https://aws.amazon.com/iot-fleetwise/
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Reference Implementation for AWS IoT FleetWise

:robot: AWS IoT FleetWise now supports ROS2 for collecting vision system data.
:information_source: To quickly get started, jump to the Jupyter Notebook demo and collect camera data from a CARLA vehicle simulation.

:information_source: To quickly get started with telematics data collection, jump to the Edge Agent Developer Guide, the Android Guide, or the Raspberry Pi Tutorial.

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:

  1. 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.

  2. 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):

  1. Vehicle Gateway such as the NXP S32G and Renesas R-Car S4
  2. Vehicle Head-Unit
  3. Vehicle's High Performance Computer
  4. Telecommunication Control Unit

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 zero (QoS = 0).

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_GREENGRASSV2 is enabled.

Optional: The following dependencies are only required when the option FWE_FEATURE_VISION_SYSTEM_DATA is enabled.

Optional: The following dependencies are only required when the option FWE_FEATURE_ROS2 is 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.

  1. Change Log provides a summary of feature enhancements, updates, and resolved and known issues.
  2. Offboarding and Data Deletion provides a summary of the steps needed on the client side to offboard from the service.
  3. Edge Agent Developer Guide provides step-by-step instructions for building and running your Edge Agent.

The following documents provide more information about the cloud component of AWS IoT FleetWise.

  1. AWS IoT FleetWise API Reference describes all the API operations for FleetWise