Over-the-air (OTA) integration: Renesas RZ/G2L and Yocto 3.1 Dunfell

This blog guides embedded hardware designers and developers who want to deploy and manage secure OTA software updates to a fleet of embedded devices, leveraging Renesas RZ/G2L and Yocto 3.1 Dunfell integrations.

Renesas%20Integration

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Human machine interfaces (HMIs) and display systems in industrial and building automation, security panels, point of sale (POS) systems, door phones, and IoT edge devices, such as a network gateway or an edge server, require secure and robust over-the-air (OTA) software updates. For these use cases, integrating OTA updates with Renesas RZ/G2L and Yocto 3.1 Dunfell is a common requirement.

This blog guides embedded hardware designers and developers who want to deploy and manage secure OTA software updates to a fleet of embedded devices, leveraging Renesas RZ/G2L and Yocto 3.1 Dunfell integrations.

Renesas RZ/G2L microprocessor

The Renesas RZ/G2L microprocessor includes a dual-core Cortex-A55 (1.2 GHz) CPU, 16-bit DDR3L / DDR4 interface, 3D graphics engine with Arm Mali-G31, and video codec (H.264). With various interfaces, including camera input, display output, USB 2.0, and gigabit ethernet, the Renesas RZ/G2L microprocessor is ideal for applications such as entry-class industrial human-machine interfaces (HMIs) and embedded devices with video capabilities.

The Renesas RZ/G2L is built on high-performance CPU cores with various accelerators and peripheral functions. The RZ/G2L provides high speed, real-time control; high speed (maximum 600MHz) 32-bit Cortex-R CPU core and large tightly-coupled memory (TCM) realize deterministic real-time response. The RZ/G2L also supports embedded Vision AI for industrial-grade heat and power efficiency, delivering high-speed AI inference at low power consumption. The RZ/G2L also supports an HMI for drawing capabilities, camera input, and audio input for WVGA, WXGA, and 2D graphics are supported based on RZ/A. There are also built-in 3D drawing and full HD video codec functions based on RZ/G.

With Renesas RZ/G2L, engineers can easily implement high-resolution HMI and embedded AI solutions, as well as real-time control and industrial ethernet connectivity.

Use cases for Renesas RZ/G2L

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The Renesas RZ family of 32-bit and 64-bit microprocessors (MPUs) are designed to enable solutions that Renesas believes are required for the smart societies of the future. Through high-performance CPU cores and various accelerators and peripheral functions, embedded engineers and developers can implement high-resolution HMI, embedded vision, embedded AI, real-time control, and industrial ethernet connectivity.

RZ/G2L is a general-purpose MPU for Vision AI, HMI, and IoT Edge applications.

Reference integration: Mender OTA, Renesas RZ/G2L, and Yocto 3.1 Dunfell

Note: Mender has been verified to work on a Renesas RZ/G2L board, including U-Boot-based boards, for which the Mender integration checklisthas also been verified. The Renesas Verified Linux Package (VLP) works with the whole RZ/G2 and RZ/V2 family of MPUs. This reference integration can also be used to run other MPUs in the family as well.

The integration tutorial provides the following:

  • Prerequisites: Requirements to build a Yocto image for this OTA integration.
  • Build configuration: Instructions on how to set up the Yocto build environment, change the configuration, and build the image.
  • Renesas board setup: Steps to setting up the Renesas RZ/G2L evaluation kit for booting and Renesas toolset for flashing.
  • SD card preparation: Guide to partitioning, validating, formatting, and copying files to the microSD card.
  • U-boot setup: Basic U-boot setup to boot the board.
  • Additional references and test results

Ready to try it yourself? Check out the step-by-step integration guide on Mender Hub.

Not a Mender user? Start your free trial today. Test Mender Enterprise and the Renesas integration (or one of the many others) for 12 months on up to 10 devices.

A special thanks to Stefan Ungerechts, principal engineer at Renesas, for inspiring this important integration for embedded AI applications.

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