How AWS IoT FleetWise works

The following sections provide an overview of AWS IoT FleetWise service components and how they interact.

After you read this introduction, see the Setting up AWS IoT FleetWise section to learn how to set up AWS IoT FleetWise.

Key concepts

AWS IoT FleetWise provides a vehicle modeling framework for you to model your vehicle and its sensors and actuators in the cloud. To enable the secure communication between your vehicle and the cloud, AWS IoT FleetWise also provides a reference implementation to help you develop Edge Agent software that that you can install in your vehicle. You can define data collection schemes in the cloud and deploy them to your vehicle. The Edge Agent software running in your vehicle uses data collection schemes to control what data to collect and when to transfer it to the cloud.

The following are the core concepts of AWS IoT FleetWise.

Signal

Signals are fundamental structures that you define to contain vehicle data and its metadata. A signal can be an attribute, a branch, a sensor, or an actuator. For example, you can create a sensor to receive in-vehicle temperature values, and to store its metadata, including a sensor name, a data type, and a unit. For more information, see Create and manage signal catalogs.

Attribute

Attributes represent static information that generally doesn't change, such as manufacturer and manufacturing date.

Branch

Branches represent signals in a nested structure. Branches demonstrate signal hierarchies. For example, the Vehicle branch has a child branch, Powertrain. The Powertrain branch has a child branch, combustionEngine. To locate the combustionEngine branch, use the Vehicle.Powertrain.combustionEngine expression.

Sensor

Sensor data reports the current state of the vehicle and change over time, as the state of the vehicle changes, such as fluid levels, temperatures, vibrations, or voltage.

Actuator

Actuator data reports the state of a vehicle device, such as motors, heaters, and door locks. Changing the state of a vehicle device can update actuator data. For example, you can define an actuator to represent the heater. The actuator receives new data when you turn on or off the heater.

Custom structure

A custom structure (also known as a struct) represents a complex or higher-order data structure. It facilitates logical binding or grouping of data that originates from the same source. A struct is used when data is read or written in an atomic operation, such as to represent a complex data type or higher-order shape.

A signal of struct type is defined in the signal catalog using a reference to a struct data type instead of a primitive data type. Structs can be used for all types of signals including sensors, attributes, actuators, and vision system data types. If a signal of struct type is sent or received, AWS IoT FleetWise expects all included items to have valid values, so all items are mandatory. For example, if a struct contains the items Vehicle.Camera.Image.height, Vehicle.Camera.Image.width, and Vehicle.Camera.Image.data – it's expected that the sent signal contains values for all of these items.

Note

Vision system data is in preview release and is subject to change.

Custom property

A custom property represents a member of the complex data structure. The data type of the property can be either primitive or another struct.

When representing a higher-order shape using a struct and custom property, the intended higher-order shape is always defined and visioned as a tree structure. The custom property is used to define all the leaf nodes while the struct is used to define all the non-leaf nodes.

Signal catalog

A signal catalog contains a collection of signals. Signals in a signal catalog can be used to model vehicles that use different protocols and data formats. For example, there are two cars made by different automakers: one uses the Control Area Network (CAN bus) protocol; the other one uses the On-board Diagnostics (OBD) protocol. You can define a sensor in the signal catalog to receive in-vehicle temperature values. This sensor can be used to represent the thermocouples in both cars. For more information, see Create and manage signal catalogs.

Vehicle model (model manifest)

Vehicle models are declarative structures that you can use to standardize the format of your vehicles and to define relationships between signals in the vehicles. Vehicle models enforce consistent information across multiple vehicles of the same type. You add signals to create vehicle models. For more information, see Create and manage vehicle models.

Decoder manifest

Decoder manifests contain decoding information for each signal in vehicle models. Sensors and actuators in vehicles transmit low-level messages (binary data). With decoder manifests, AWS IoT FleetWise is able to transform binary data into human-readable values. Every decoder manifest is associated with a vehicle model. For more information, see Create and manage decoder manifests.

Network interface

Contains information about the protocol that the in-vehicle network uses. AWS IoT FleetWise supports the following protocols.

Controller Area Network (CAN bus)

A protocol that defines how data is communicated between electronic control units (ECUs). ECUs can be the engine control unit, airbags, or the audio system.

On-board diagnostic (OBD) II

A further developed protocol that defines how self-diagnostic data is communicated between ECUs. It provides a number of standard diagnostic trouble codes (DTCs) that help identify what is wrong with your vehicle.

Vehicle middleware

The vehicle middleware defined as a type of network interface. Examples of vehicle middleware include Robot Operating System (ROS 2) and Scalable service-Oriented MiddlewarE over IP (SOME/IP).

Note

AWS IoT FleetWise supports ROS 2 middleware for vision system data.

Decoder signal

Provides detailed decoding information for a specific signal. Every signal specified in the vehicle model must be paired with a decoder signal. If the decoder manifest contains CAN network interfaces, it must contain CAN decoder signals. If the decoder manifest contains OBD network interfaces, it must contain OBD decoder signals.

The decoder manifest must contain message decoder signals if it also contains vehicle middleware interfaces.

Vehicle

A virtual representation of your physical vehicle, such a car or a truck. Vehicles are instances of vehicle models. Vehicles created from the same vehicle model inherit the same group of signals. Each vehicle corresponds to an AWS IoT thing.

Fleet

A fleet represents a group of vehicles. Before you can easily manage a fleet of vehicles, you must associate individual vehicles to a fleet.

Campaign

Contains data collection schemes. You define a campaign in the cloud and deploy it to a vehicle or fleet. Campaigns give the Edge Agent software instructions on how to select, collect, and transfer data to the cloud.

Data collection scheme

Data collection schemes give the Edge Agent software instructions on how to collect data. Currently, AWS IoT FleetWise supports the condition-based collection scheme and the time-based collection scheme.

Condition-based collection scheme

Use a logical expression to recognize what data to collect. The Edge Agent software collects data when the condition is met. For example, if the expression is $variable.myVehicle.InVehicleTemperature >35.0, the Edge Agent software collects temperature values that are greater than 35.0.

Time-based collection scheme

Specify a time period in milliseconds to define how often to collect data. For example, if the time period is 10,000 milliseconds, the Edge Agent software collects data once every 10 seconds.

Features of AWS IoT FleetWise

The following are the key features of AWS IoT FleetWise.

Vehicle modeling

Build virtual representations of your vehicles and apply a common format to organize vehicle signals. AWS IoT FleetWise supports Vehicle Signal Specification (VSS) that you can use to standardize vehicle signals.

Scheme-based data collection

Define schemes to transfer only high-value vehicle data to the cloud. You can define condition-based schemes to control what data to collect, such as data in-vehicle temperature values that are greater than 40 degrees. You can also define time-based schemes to control how often to collect data.

Edge Agent for AWS IoT FleetWise software

The Edge Agent software running in vehicles facilitates communication between vehicles and the cloud. While vehicles are connected to the cloud, the Edge Agent software continually receives data collection schemes and collects data accordingly.