This document is intended to guide you in the installation of the necessary tools and repository for start running Zephyr examples and development. Zephyr is a lightweight, open-source real-time operating system (RTOS) designed specifically for microcontrollers (MCUs) and other resource-constrained embedded devices. Unlike general-purpose operating systems, Zephyr is built to run on systems with limited memory, low power consumption, and strict real-time requirements. It provides the core software foundation that allows an MCU to run multiple tasks reliably, respond to events on time, and interact with hardware in a structured way.

This project implements a configurable secure encrypted Ethernet communication node with the transmission of a large data image.

Whether you're a student, hobbyist, or professional developer, the FRDM Development Platform by NXP is your gateway to building powerful embedded applications—quickly and affordably. In this beginner-friendly guide, you’ll learn: What FRDM boards are and how they compare to other NXP evaluation kits Who the platform is designed for How to buy and get started with your first board What’s new in the latest FRDM series featuring MCX microcontrollers and i.MX processors How the FRDM ecosystem supports your development with modular hardware, software tools, and ready-to-use code examples

Customer may want to debug FRDM-IMX93 with the SWD interface of Jtag. This doc give an introduction about how to do that. Hardware: FRDM-IMX93,J-link. 1.Rework FRDM-IMX93 board and get the VREF(1.8V) from TP707 for SWD, show as the following picture.     2. Remove the  R3017 and R3018 in the following picture.     3.Connect FRDM-IMX93 and PC through J-link as the following pictures.     4.Switch the sw1 to 1001 to the serial download of the M33, then run the J-link commander.   The command is as following: J-Link>device MIMX9352_M33 J-Link>speed 4000 Selecting 4000 kHz as target interface speed J-Link>si swd Selecting SWD as current target interface. J-Link>power on J-Link>connect   The full log is as following: SEGGER J-Link Commander V8.10 (Compiled Sep 26 2024 08:38:41) DLL version V8.10, compiled Sep 26 2024 08:37:48 Connecting to J-Link via USB...O.K. Firmware: J-Link V10 compiled Jan 30 2023 11:28:07 Hardware version: V10.10 J-Link uptime (since boot): N/A (Not supported by this model) S/N: 600109556 License(s): RDI, FlashBP, FlashDL, JFlash, GDB VTref=1.800V Type "connect" to establish a target connection, '?' for help J-Link>device MIMX9352_M33 J-Link>speed 4000 Selecting 4000 kHz as target interface speed J-Link>si swd Selecting SWD as current target interface. J-Link>power on J-Link>connect Device "MIMX9352_M33" selected. Connecting to target via SWD ConfigTargetSettings() start ConfigTargetSettings() end - Took 12us InitTarget() start InitTarget() end - Took 2.53ms Found SW-DP with ID 0x5BA02477 DPIDR: 0x5BA02477 CoreSight SoC-400 or earlier AP map detection skipped. Manually configured AP map found. AP[0]: AHB-AP (IDR: Not set, ADDR: 0x00000000) AP[1]: MEM-AP (IDR: Not set, ADDR: 0x00000000) AP[2]: MEM-AP (IDR: Not set, ADDR: 0x00000000) AP[3]: AHB-AP (IDR: Not set, ADDR: 0x00000000) AP[3]: Core found AP[3]: AHB-AP ROM base: 0xE00FF000 CPUID register: 0x411FD210. Implementer code: 0x41 (ARM) Feature set: Mainline Cache: No cache Found Cortex-M33 r1p0, Little endian. Cortex-M (ARMv8-M and later): The connected J-Link (S/N 600109556) uses an old firmware module that does not handle I/D-cache correctly. Proper debugging functionality cannot be guaranteed if cache is enabled FPUnit: 8 code (BP) slots and 0 literal slots Security extension: implemented Secure debug: enabled CoreSight components: ROMTbl[0] @ E00FF000 [0][0]: E000E000 CID B105900D PID 000BBD21 DEVARCH 47702A04 DEVTYPE 00 Cortex-M33 [0][1]: E0001000 CID B105900D PID 000BBD21 DEVARCH 47701A02 DEVTYPE 00 DWT [0][2]: E0002000 CID B105900D PID 000BBD21 DEVARCH 47701A03 DEVTYPE 00 FPB [0][3]: E0000000 CID B105900D PID 000BBD21 DEVARCH 47701A01 DEVTYPE 43 ITM [0][5]: E0041000 CID B105900D PID 002BBD21 DEVARCH 47724A13 DEVTYPE 13 ETM [0][6]: E0042000 CID B105900D PID 000BBD21 DEVARCH 47701A14 DEVTYPE 14 CSS600-CTI Memory zones: Zone: "Default" Description: Default access mode Cortex-M33 identified. J-Link>   5.You can also switch the sw1 to 0011 boot the A55 and stop at U-boot, then run the J-link commander The following is the command: J-Link>device MIMX9352_M33 J-Link>speed 4000 Selecting 4000 kHz as target interface speed J-Link>si swd Selecting SWD as current target interface. J-Link>power on J-Link>connect   The following is the full log: SEGGER J-Link Commander V8.10 (Compiled Sep 26 2024 08:38:41) DLL version V8.10, compiled Sep 26 2024 08:37:48 Connecting to J-Link via USB...O.K. Firmware: J-Link V10 compiled Jan 30 2023 11:28:07 Hardware version: V10.10 J-Link uptime (since boot): N/A (Not supported by this model) S/N: 600109556 License(s): RDI, FlashBP, FlashDL, JFlash, GDB VTref=1.806V Type "connect" to establish a target connection, '?' for help J-Link>device MIMX9352_M33 J-Link>speed 4000 Selecting 4000 kHz as target interface speed J-Link>si swd Selecting SWD as current target interface. J-Link>power on J-Link>connect Device "MIMX9352_M33" selected. Connecting to target via SWD ConfigTargetSettings() start ConfigTargetSettings() end - Took 27us InitTarget() start InitTarget() end - Took 3.89ms Found SW-DP with ID 0x5BA02477 DPIDR: 0x5BA02477 CoreSight SoC-400 or earlier AP map detection skipped. Manually configured AP map found. AP[0]: AHB-AP (IDR: Not set, ADDR: 0x00000000) AP[1]: MEM-AP (IDR: Not set, ADDR: 0x00000000) AP[2]: MEM-AP (IDR: Not set, ADDR: 0x00000000) AP[3]: AHB-AP (IDR: Not set, ADDR: 0x00000000) AP[3]: Core found AP[3]: AHB-AP ROM base: 0xE00FF000 CPUID register: 0x411FD210. Implementer code: 0x41 (ARM) Feature set: Mainline Cache: No cache Found Cortex-M33 r1p0, Little endian. Cortex-M (ARMv8-M and later): The connected J-Link (S/N 600109556) uses an old firmware module that does not handle I/D-cache correctly. Proper debugging functionality cannot be guaranteed if cache is enabled FPUnit: 8 code (BP) slots and 0 literal slots Security extension: implemented Secure debug: enabled CoreSight components: ROMTbl[0] @ E00FF000 [0][0]: E000E000 CID B105900D PID 000BBD21 DEVARCH 47702A04 DEVTYPE 00 Cortex-M33 [0][1]: E0001000 CID B105900D PID 000BBD21 DEVARCH 47701A02 DEVTYPE 00 DWT [0][2]: E0002000 CID B105900D PID 000BBD21 DEVARCH 47701A03 DEVTYPE 00 FPB [0][3]: E0000000 CID B105900D PID 000BBD21 DEVARCH 47701A01 DEVTYPE 43 ITM [0][5]: E0041000 CID B105900D PID 002BBD21 DEVARCH 47724A13 DEVTYPE 13 ETM [0][6]: E0042000 CID B105900D PID 000BBD21 DEVARCH 47701A14 DEVTYPE 14 CSS600-CTI Memory zones: Zone: "Default" Description: Default access mode Cortex-M33 identified. J-Link>device MIMX9352_A55_0 Disconnecting from J-Link...O.K. Device "MIMX9352_A55_0" selected. Connecting to target via SWD ConfigTargetSettings() start ConfigTargetSettings() end - Took 19us Found SW-DP with ID 0x5BA02477 DPIDR: 0x5BA02477 CoreSight SoC-400 or earlier AP map detection skipped. Manually configured AP map found. AP[0]: AHB-AP (IDR: Not set, ADDR: 0x00000000) AP[1]: APB-AP (IDR: Not set, ADDR: 0x00000000) AP[2]: MEM-AP (IDR: Not set, ADDR: 0x00000000) AP[3]: AHB-AP (IDR: Not set, ADDR: 0x00000000) Using preconfigured AP[1] as APB-AP AP[1]: APB-AP found DebugRegs + CTI manually specified. ROM table scan skipped. Cortex-A55 @ 0x80810000 (configured) CoreCTI @ 0x80820000 (configured) Debug architecture: ARMv8.2 6 code breakpoints, 4 data breakpoints Processor features: EL0 support: AArch64 + AArch32 EL1 support: AArch64 + AArch32 EL2 support: AArch64 + AArch32 EL3 support: AArch64 + AArch32 FPU support: Single + Double + Conversion + single arithmetic ARMv8-A/R: The connected J-Link (S/N 600109556) uses an old firmware module V0 with known problems / limitations. Add. info (CPU temp. halted) Current exception level: EL2 Exception level AArch usage: EL0: AArch32 EL1: AArch32 EL2: AArch64 EL3: AArch64 Non-secure status: Non-secure Cache info: Inner cache boundary: none LoU Uniprocessor: 0 LoC: 0 LoU Inner Shareable: 0 VMSAv8-64: Supports 48-bit VAs Memory zones: Zone: "Default" Description: Default access mode Zone: "AP0" Description: MEM-AP (AHB-AP) Zone: "AP1" Description: MEM-AP (APB-AP) Zone: "AP3" Description: MEM-AP (AHB-AP) Cortex-A55 identified. Memory zones: Zone: "Default" Description: Default access mode Zone: "AP0" Description: MEM-AP (AHB-AP) Zone: "AP1" Description: MEM-AP (APB-AP) Zone: "AP3" Description: MEM-AP (AHB-AP) J-Link>  

In this lab, you will learn how to: Bring up Wi-Fi interfaces. Run basic Wi-Fi scan Configure and bring up Wi-Fi STA mode using WPA_SUPPLICANT. Configure and bring up UDHCP server for dynamic IP assignment for associated client devices. Run UDHCP client to get dynamic IP address. Configure and bring up Wi-Fi AP mode using hostapd. Connect STA to external AP Connect AP to external STA Start ping  Wi-Fi Basic Hands-on Demo Guide  Community Support If you have questions regarding this training, please leave your comments in our Wireless MCU Community! here 

This document assumes FRDM-iMX91 board is flashed with a Linux image. For flashing instructions, refer to FRDM-MX93_Board_Flashing guide. Then, follow this document to download software applications to test Wi-Fi, Bluetooth, and 802.15.4 performance. Hardware Prerequisites Windows or Linux PC with 64-bit OS 2 spare USB ports on PC FRDM-iMX91 Development Board Bluetooth LE device: Mobile phone which can configured as central or peripheral Wi-Fi Access Point: Standalone or mobile hotspot Wi-Fi Station: Mobile phone used as a station OPENTHREAD: 1 Another OT enabled board   Required PC Software Serial Terminal program Setting for terminal: Baud rate:115200, Parity: none, Data bits: 8, Stop bits: 1 Windows:   PUTTY or teraterm  and USB Device driver  Linux:           Minicom (Command to download the tool : sudo apt-get install minicom)   Iperf Windows:    Download Iperf version 3.0.11 from here. Linux:            Download Debian package of IPerf 3.0.11 for Ubuntu 16.04 from here. $ wget https://iperf.fr/download/ubuntu/iperf3_3.0.11-1_amd64.deb   Install the package using the command below. $ sudo dpkg -i /path/to/package/iperf3_3.0.11-1_amd64.deb   Required Mobile Software Iperf Application (iperf 3) Android:                  HE.NET Network Tools on Google Play iOS:                HE.NET Network Tools on AppStore   nRF Connect Application Android:                   nRF Connect on Google Play iOS:               nRF Connect on App Store   Required EVK Software Linux BSP Image  Version: L6.6.52_2.2.0 Link: https://www.nxp.com/webapp/sps/download/license.jsp?colCode=L6.6.52_2.2.0_MX91&appType=file1&DOWNLOA...   To download the pre-built image, please refer to https://www.nxp.com/design/design-center/software/embedded-software/i-mx-software/embedded-linux-for...   hands-on Labs Lab1 - WIFI Basic Hands-on Lab2 - Bluetooth A2DP Source and Sink Profile Demo Lab3 - OpenThread  Hands-on Lab4- WiFi Bluetooth and OT COEX Demo   Community Support If you have questions regarding this training, please leave your comments in our Wireless MCU Community! here 

FRDM Training and Resources This article provide a guide of available resources for FRDM Development boards to help you to find and use available resources (Boards, Guides, Hands-On Trainings and more)

GoPoint   GoPoint is a user-friendly application that allows the user to launch preselected demonstrations included in the NXP provided BSP and follows the quarterly release roadmap for BSP How to launch GoPoint     GoPoint Demo On FRDM-IMX93 Board Since FRDM-IMX93 board’s BSP is based on standard BSP release, GoPoint is included in FRDM-IMX93 Yocto build by default. List of 9 demos available on FRDM-IMX93 Board: Image Classification Object Detection Selfie Segmenter i.MX Smart Fitness DMS (Driver Monitor System) ML Benchmark Video Test i.MX Smart Kitchen i.MX E-Bike VIT   Image Classification Demo Image classification is a ML task that attempts to comprehend an entire image as a whole. The goal is to classify the image by assigning it to a specific label. Typically, it refers to images in which only one object appears and is analyzed. This example is using NNStreamer.            Object Detection Demo Object detection is the ML task that detects instances of objects of a certain class within an image. A bounding box and a class label are found for each detected object. This example is using NNStreamer.        Selfie Segmenter Demo Selfie Segmenter showcases the ML capabilities of i.MX 93 by using the NPU to accelerate an instance segmentation model. This model lets you segment the portrait of a person and can be used to replace or modify the background of an image. This example is using NNStreamer.         i.MX Smart Fitness Demo i.MX Smart Fitness showcases the i.MX' Machine Learning capabilities by using an NPU to accelerate two Deep Learning vision-based models. Together, these models detect a person present in the scene and predict 33 3D-keypoints to generate a complete body landmark, known as pose estimation. From the pose estimation, the application tracks the 'squats' fitness exercise.          DMS (Driver Monitor System) Demo This application showcases the capability of implementing DMS on i.MX 93 platform, and the performance boost brought by Neural Processing Unit (NPU). DMS uses four ML models in total to achieve face detection, capturing face landmark and iris landmark, smoking detection and calling detection.         ML Benchmark Demo This example is based on benchmark_model tool in Tensorflow Lite framework, which allows to easily compare the performance of TensorFlow Lite models running on CPU (Cortex-A) and NPU.   Video Test Demo This is a simple demo that allows users to play back video captured on a camera or a test source. It’s based on gstreamer pipeline.            i.MX Smart Kitchen Demo i.MX Smart Kitchen showcases the Multimedia capabilities of i.MX to emulate an interactive kitchen through a GUI controlled by voice commands. The GUI is based on LVGL (Little Versatile Graphic Library) and NXP's Voice Intelligent Technology (VIT) supports the voice commands. Usage: Keyword + command       i.MX E-Bike VIT Demo i.MX E-Bike VIT showcases the Multimedia capabilities of i.MX to emulate an interactive ebike through a GUI controlled by voice commands. The GUI is based on LVGL (Little Versatile Graphic Library) and NXP's Voice Intelligent Technology (VIT) supports the voice commands. Usage: Keyword + command         Useful Link GoPoint User Guide: https://www.nxp.com/webapp/Download?colCode=GPNTUG GoPoint repo: https://github.com/nxp-imx-support/nxp-demo-experience-demos-list/tree/lf-6.6.36_2.1.0 (Including source code of demo: Selfie Segmenter, DMS, ML benchmark, Video test) Image Classification/Object Detection: https://github.com/nxp-imx/eiq-example/tree/lf-6.6.36_2.1.0 i.MX Smart Fitness: https://github.com/nxp-imx-support/imx-smart-fitness i.MX Smart Kitchen: https://github.com/nxp-imx-support/smart-kitchen i.MX E-Bike VIT: https://github.com/nxp-imx-support/imx-ebike-vit

FRDM-IMX93 Yocto Release - BSP  Based on i.MX SW 2024 Q3 release Linux kernel: 6.6.36_2.1.0 u-boot: 2024.04 Source: https://github.com/nxp-imx-support/meta-imx-frdm FRDM-IMX93 BSP changes: U-boot: Add basic support for FRDM-IMX93 Kernel: Add basic support for FRDM-IMX93 and add support for kinds of accessories GoPoint: Add FRDM-IMX93 support FRDM-IMX93 Yocto layer: Add Yocto layer for FRDM-IMX93 and integrate u-boot/kernel/GoPoint patches    FRDM-IMX93 accessories 7 inch Waveshare LCD: imx93-11x11-frdm-dsi.dtb 5 inch Tianma LCD: imx93-11x11-frdm-tianma-wvga-panel.dtb RPi-CAM-MIPI: imx93-11x11-frdm.dtb RPI-CAM-INTB: imx93-11x11-frdm-mt9m114.dtb MX93AUD-HAT or MX93AUD-HAT + 8MIC-RPI-MX8: imx93-11x11-frdm-aud-hat.dtb 8MIC-RPI-MX8: imx93-11x11-frdm-8mic.dtb   LCD Panel Vender Interface Size Resolution Support Touch Purchase Link dtb T050RDH03-HC Tianma 24 bit Parallel 5" 800 x 480 No Will launch with MX91 EVK in Dec'24 imx93-11x11-frdm-tianma-wvga-panel.dtb 7inch Capacitive Touch IPS Display for Raspberry Pi, with Protection Case, 1024×600, DSI Interface Waveshare MIPI DSI 7" 1024x600 Yes Click Here imx93-11x11-frdm-dsi.dtb Camera Vender Interface Size Resolution Sensor Purchase Link dtb RPI-CAM-MIPI onsemi MIPI CSI  1/4-inch 1M pixel, 1280H x 800V AR0144 Click Here imx93-11x11-frdm.dtb RPI-CAM-INTB 　 Parallel Camera 40pins 1/6-inch 1.26 Mpixel 1296H × 976V MT9M114 Will launch with MX91 EVK in Dec'24 imx93-11x11-frdm-mt9m114.dtb Audio Vender Interface Channel 　 　 Purchase Link dtb MX93AUD-HAT Cirrus 40pins 8 　 　 Click Here imx93-11x11-frdm-aud-hat.dtb 8MIC-RPI-MX8 NXP 40pins 8 　 　 Click Here imx93-11x11-frdm-8mic.dtb   FRDM-IMX93 Yocto Release Usage Download i.MX SW 2024 Q3 Release: $ repo init -u https://github.com/nxp-imx/imx-manifest -b imx-linux-scarthgap -m imx-6.6.36-2.1.0.xml $ repo sync Integrate FRDM-IMX93 layer into Yocto code base: $ cd ${MY_YOCTO}/sources $ git clone https://github.com/nxp-imx-support/meta-imx-frdm.git Yocto Project Setup: $ MACHINE=imx93frdm DISTRO=fsl-imx-xwayland source sources/meta-imx-frdm/tools/imx-frdm-setup.sh -b frdm-imx93 Build images: $ bitbake imx-image-full Flashing SD card image: $ zstdcat imx-image-full-imx93frdm.rootfs.wic.zst | sudo dd of=/dev/sdb bs=1M && sync Using uuu to burn image and rootfs to SD: $ uuu -b sd_all imx-image-full-imx93frdm.rootfs.wic.zst   FRDM-IMX93 Yocto Release – Matter support Based on i.MX Matter 2024 Q3 Usage: −Download i.MX SW 2024 Q3 Release; $ repo init -u https://github.com/nxp-imx/imx-manifest -b imx-linux-scarthgap -m imx-6.6.36-2.1.0.xml $ repo sync −Download i.MX Matter 2024 Q3; $ cd ${MY_YOCTO}/sources/meta-nxp-connectivity $ git remote update $ git checkout imx_matter_2024_q3 −Download FRDM-IMX93 Layer: $ cd ${MY_YOCTO}/sources $ git clone https://github.com/nxp-imx-support/meta-imx-frdm.git −Yocto Project Setup: $ MACHINE=imx93frdm-iwxxx-matter DISTRO=fsl-imx-xwayland source sources/meta-imx-frdm/tools/imx-frdm-matter-setup.sh bld-xwayland-imx93 −Build images: $ bitbake imx-image-multimedia     FRDM-MX93 Debian Release Debian is a free Operating System (OS), also known as Debian GNU/Linux. i.MX Debian Linux SDK distribution is a combination of NXP-provided kernel and boot loaders with a Debian distro user-space image. −Debian 12 −NXP packages are based i.MX SW Release 2024 Q3 i.MX Debian Linux SDK distribution uses Flexbuild to build system. −Debian-based RootFS; Debian Base (basic packages) Debian Server (more packages without GUI Desktop) Debian Desktop (with GNOME GUI Desktop) −Linux kernel; −BSP components; −various  applications (graphics, multimedia, networking, connectivity, security, and AI/ML); Source: https://github.com/NXP/flexbuild Introduction:  https://nxp.com/nxpdebian  Quick Start with Debian Flexbuild compiles and assembles the distro images as three parts: BSP firmware image Boot image RootFS image Creating an SD card on the Linux host Download flex-installer −$ wget http://www.nxp.com/lgfiles/sdk/lsdk2406/flex-installer −$ chmod +x flex-installer; sudo mv flex-installer /usr/bin Plug the SD card into the Linux host and install the images as below: −$ flex-installer -i pf -d /dev/sdb (format SD card) −$ flex-installer -i auto -d /dev/mmcblk1 -m imx93frdm (automatically download and install images) Plug the SD card into the i.MX board and install the extra packages as follows: −$ dhclient -i end0 (setup Ethernet network interface by DHCP or setting it manually) −$ date -s "22 Nov 2024 09:00:00" (setting correct system time is required) −$ debian-post-install-pkg desktop (install extra packages for GNOME GUI Desktop version) −or −$ debian-post-install-pkg server (install extra packages for Server version without GUI Desktop) −# After finishing the installation, run the reboot command to boot up the Debian Desktop/Server system.   Building Debian Images with Flexbuild Run the following commands for the first time to set up the build environment: −$ git clone https://github.com/nxp/flexbuild −$ cd flexbuild && . setup.env −#Continue to run commands below in case  you need to  build in Docker due to lack of Ubuntu 22.04 or Debian 12 host −$ bld docker (create or attach a docker container) −$ . setup.env   Flexbuild usage: −$ bld -m imx93frdm (build all images for imx93frdm) −$ bld uboot -m imx93frdm (compile u-boot image for imx93frdm) −$ bld linux (compile linux kernel for all arm64 i.MX machines) −$ bld bsp -m imx93frdm (generate BSP firmware) −$ bld boot (generate boot partition tarball including kernel, dtb, modules, distro bootscript for iMX machines) −$ bld multimedia (build multimedia components for i.MX platforms) −$ bld rfs -r debian:base (generate Debian base rootfs with base packages) −$ bld apps -r debian:server (compile apps against runtime dependencies of Debian server RootFS) −$ bld merge-apps -r debian:server (merge iMX-specific apps into target Debian server RootFS) −$ bld packrfs (pack and compress target rootfs)   Related Documentation   FRDM-IMX93 Documents: FRDM-IMX93 Quick Start Guide FRDM-IMX93 Board User Manual FRDM-IMX93 Software User Guide  More information about i.MX productions can be found at(http://www.nxp.com/imxlinux) i.MX Yocto Project User’s Guide​ i.MX Linux User’s Guide​ i.MX Linux Reference Manual​ i.MX Porting Guide Debian documents at http://www.nxp.com/nxpdebian i.MX Debian Linux SDK User Guide

  The RW61x is a highly integrated, low-power tri-radio wireless MCU with an integrated MCU and Wi-Fi ®  6 + Bluetooth ®  Low Energy (LE) 5.4 / 802.15.4 radios designed for a broad array of applications, including connected smart home devices, enterprise and industrial automation, smart accessories and smart energy. The RW612 MCU subsystem includes a 260 MHz Arm ®  Cortex ® -M33 core with Trustzone ™ -M, 1.2 MB on-chip SRAM and a high-bandwidth Quad SPI interface with an on-the-fly decryption engine for securely accessing off-chip XIP flash. The RW612 includes a full-featured 1x1 dual-band (2.4 GHz/5 GHz) 20 MHz Wi-Fi 6 (802.11ax) subsystem bringing higher throughput, better network efficiency, lower latency and improved range over previous generation Wi-Fi standards. The Bluetooth LE radio supports 2 Mbit/s high-speed data rate, long range and extended advertising. The on-chip 802.15.4 radio can support the latest Thread mesh networking protocol. In addition, the RW612 can support Matter over Wi-Fi or Matter over Thread offering a common, interoperable application layer across ecosystems and products. Hands-On Trainings Introduction to RW61x and FRDM-RW612 Quick introduction to RW61x family, module offering and FRDM-RW612 evaluation board FRDM-RW612 Out of the Box Experience Wi-Fi CLI (Command Line Interface) demo provides the user with a menu with different commands to explore the Wi-Fi capabilities of the FRDM RW612 board. When the board is powered on for the first time, the green RGB LED should be blinking indicating that the demo is loaded into the board. FRDM-RW612 Getting Started. Wi-Fi CLI on VS Code This lab guides you step by step on how to get started with FRD-RW612 board using Visual Studio Code  FRDM-RW612 BLE Sensors over Zephyr This demo shows the temperature from the i2c temperature sensor integrated in the board. This demo is based on Zephyr RTOS. The information can be monitored in the UART terminal or in the IoT Toolbox app. FRDM-RW612 Kitchen Timer using Low-cost LCD This lab shows how to modify a Kitchen Timer graphical application using LCD-PAR-S035 display Changing the date and button colors. The timer can also be viewed on a serial terminal.   Community Support If you have questions regarding this training or RW61x series, please leave your comments in our Wireless MCU Community! here 

  Introduction   This hands-on walks you through everything that happens before you ever write a line of application code: unboxing your FRDM i.MX 95 Pro board, getting acquainted with its layout and ports, powering it on, and confirming a healthy first boot from the on-board eMMC. By the time you are done, you will be comfortable using both the i.MX System Manager console and the Linux command line to confirm exactly what hardware you have in front of you. By the end you will be able to: Verify that the contents of your FRDM i.MX 95 Pro box are complete Get acquainted with the board, its peripherals, and ports Set up and boot the board for the first time Get familiar with the i.MX System Manager (SM) console and the Linux CLI Verify the board's hardware and resources using Linux commands Hardware & Prerequisites You need very little to get started: FRDM-IMX95-PRO board (the box) — in addition to the board itself, the box includes USB-C cables for power and debugging, mounting standoffs, the IW612 wireless module, and a documentation card linking to the product page and a getting-started tutorial. Power supply — a USB-C to USB-C cable is included in the box. For basic bring-up, any standard USB-C phone charger is sufficient. If your setup adds higher-power accessories (e.g., a display), use a 100 W-capable USB-C power adapter instead. PC host — a computer with a terminal / serial console program to connect to the board's debug port. That's it — no display or camera is required for this hands-on. Watch the Module Video Watch the full hands-on walkthrough below, then follow along on your own board.   Steps to Run the Hands-On Step 1: Explore the Board with Linux Commands Once the board has booted, open a terminal on the debug console and run the following commands to confirm the Linux environment and the hardware resources available to you. # 1) Linux version uname -a # 2) Storage devices lsblk # 3) Verify CPU numbers and architecture. lscpu # 4) SoC Id and Family cat /sys/devices/soc0/soc_id cat /sys/devices/soc0/family # 5) RAM memory available cat /proc/meminfo | head -20 # 6) network peripherals and addresses ip addr # 7) List Video Encoders and Decoders v4l2-ctl --list-devices # 8) GPU specs and capabilities vulkaninfo --summary # 9) Print available GPIOs gpioinfo Step 2: Explore the i.MX System Manager Console Next, switch to the i.MX System Manager (SM) console to inspect the board at the system level — Logical Machines, boot times, power rails, and clocks. # 1) System manager version, Board, Revision, Silicon etc info # 2) Logical Machines information lm info # 3) Boot time of each Logical machine btime # 4) Power status of each peripheral power.r # 5) Clocks status clock.r Troubleshooting Symptom What to check Power LED is on but there is no output on the console Check the Boot Mode switches (set them to eMMC) Power-cycle the board (turn it off and back on) after changing the Boot Mode switches Verify the serial console baud rate is set to 115200 Confirm the Debug port is connected to the host PC Open all the COM ports exposed by the board when the Debug port is connected to the host PC Conclusion In this hands-on, you: Verified the contents of your FRDM i.MX 95 Pro box Got acquainted with the board, its peripherals, and ports Set up and booted the board for the first time from eMMC Used the i.MX System Manager console and the Linux CLI to inspect the board Confirmed the board's hardware and resources via Linux commands If you have not already, watch the module video above for the full walkthrough, and check out the rest of the FRDM Training Hub for the next hands-on in the series.

  Introduction This hands-on walks you through bringing a display to life on the FRDM-IMX95-PRO board. You will flash a BSP image to an SD card, attach a Waveshare 7" DSI LCD, select the correct device tree in U-Boot, and then exercise the panel with brightness control, screen rotation, capacitive touch, and a live camera video pipeline. By the end you will have a fully working touch display and the core skills to configure DSI panels on i.MX 95. By the end of this hands-on you will be able to: Flash a BSP image to a microSD card using UUU in Serial Download mode. Connect the Waveshare 7" DSI display (FPC, power, and I2C) correctly. Select the matching device tree for the panel from the U-Boot prompt. Adjust and script the display backlight brightness. Rotate the screen through Weston's configuration. Verify capacitive touch with evtest . Stream live camera video to the panel with GStreamer. Hardware & Prerequisites FRDM-IMX95-PRO board. MicroSD card — 16 GB or larger. Waveshare 7" DSI LCD — 1024×600 IPS, 5-point capacitive touch. 22-pin FPC cable. Host PC with UUU installed. Watch the Module Video Watch the full hands-on walkthrough first to see each step performed on real hardware, then follow along on your own board using the steps below. Steps to Run the Hands-On 1. Enter Serial Download Mode Put the board into Serial Download Protocol (SDP) mode so the host can push the image, then connect it to your PC: Set boot switch SW1 = 1000 (Serial Download Protocol mode). Connect J7 USB-C to the host PC. Connect J22 USB-C to view debug output on the serial console. 2. Flash the BSP Image with UUU Run the following command on your host computer to flash the BSP boot image and full image to the SD card: # --- UUU --- # Run the following command on your host computer uuu.exe –b sd_all imx-boot-imx95-19x19-lpddr5-frdm-pro-sd.bin-flash_a55 imx-image-full-imx95evk.wic.zst 3. Switch to SD Boot Once flashing completes, reconfigure the board to boot from the SD card: Power off the board. Set boot switches SW3 and SW4 = 0011 (SD card boot). Turn on the board. 4. Connect the Display — FPC Cable Attach the 22-pin FPC cable between the board and the Waveshare panel, paying close attention to cable orientation on each end: Connect the 22-pin FPC to the board's MIPI-DSI connector — the stiffener side faces the board connector. Connect the other end to the Waveshare panel (15-pin side) — the conductive side faces the panel. 5. Connect the Display — Power & I2C The panel needs both power and an I2C connection for the display output to come up: Connect I2C via the J6 4-pin header. Connect 5V power to J17 (or any 5V connector). I2C must be connected for display output to work. 6. Change the Device Tree in U-Boot Watch the serial console during boot and press any key at the U-Boot countdown to reach the prompt: Hit any key to stop autoboot: 3 => (U-Boot prompt) At the U-Boot prompt, select the device tree for the Waveshare panel and boot: # --- U-Boot: select the device tree for the display --- fatls mmc 1 setenv fdtfile imx95-19x19-frdm-pro-waveshare-7inch-c-panel.dtb saveenv boot 7. Set & Check Backlight Brightness Once Linux is running on the board, the panel backlight is exposed through sysfs. The commands below set a brightness value and read the current and maximum allowed values. Valid range is 0 (off) up to max_brightness . Run these as root: # --- Linux on board --- # Run the following command on the board # Path to the backlight /sys/class/backlight/3-0045/ # Set brightness echo 128 > /sys/class/backlight/3-0045/brightness # Read the current value cat /sys/class/backlight/3-0045/brightness # Read the maximum allowed value cat /sys/class/backlight/3-0045/max_brightness 8. Fun Example — Breathing Backlight For a quick visual test, this small script ramps the backlight up and down continuously, giving a "breathing" effect. Save it as breathe.sh , make it executable, and run it as root. Press Ctrl+C to stop. # --- Linux --- # Breathing back light # Create and open the file vi breathe.sh # Write the following lines into the bash script BL=/sys/class/backlight/3-0045 MAX=$(cat "$BL/max_brightness") while true; do for ((i=0; i<=MAX; i++)); do echo "$i" > "$BL/brightness"; sleep 0.01; done for ((i=MAX; i>=0; i--)); do echo "$i" > "$BL/brightness"; sleep 0.01; done done # Change the permissions of the bash script chmod +x breathe.sh # Run the bash script ./breathe.sh 9. Rotate the Screen (Weston) Display orientation is controlled in Weston's configuration file. Edit weston.ini , add an [output] section with the desired transform, then restart the service: # --- Linux --- # On board # File path /etc/xdg/weston/weston.ini # Open the file vi /etc/xdg/weston/weston.ini # Add the following [output] name=DPI-1 transform=rotate-90 # Valid formats # normal - 0 degrees (default) # rotate-90 - 90 degrees clockwise # rotate-180 - upside down # rotate-270 - 270 degrees clockwise # Reboot or restart the service systemctl restart Weston # Check the status of the service systemctl status weston You can confirm the panel resolution and active modes with modetest : # --- Linux --- # Check the panel resolution modetest -c # list connectors & modes # full DRM/KMS overview modetest # Look for the DSI/DPI connector and confirm # 1024x600 is listed as an active mode 10. Test Capacitive Touch (evtest) Run evtest with no arguments to list the available input devices, then select the touch screen's event number to start capturing touch events: # --- Linux --- # Touch screen evtest # Run the evtest command evtest # It will list the available devices Available devices: /dev/input/event0: scmi_dev.11 /dev/input/event1: Goodix Capacitive TouchScreen Select the device event number [0-1]: 1 # Then it will run the evtest of the touch screen 11. Display Camera Video (GStreamer) Stream live camera video to the panel to verify both the camera and the display path in one go: # --- Linux --- # Gstreamer pipe line for webcam # Run the following command gst-launch-1.0 v4l2src device=/dev/video52 ! video/x-raw,width=640,height=480 ! Glimagesink # Pipeline breakdown # v4l2src device=/dev/video52 - capture from V4L2 node # video/x-raw,width=640,height=480 - raw 640x480 video # glimagesink - render on display via OpenGL Troubleshooting Symptom What to check No display output Check FPC orientation — the stiffener side must face the board connector. Ensure the I2C bus (J6) is connected; it is required for display output. fatls mmc 1 fails Verify the SD card is inserted. Confirm SW3 and SW4 = 0011 (SD boot mode). "No such file or directory" at the backlight path Confirm the node name with ls /sys/class/backlight/ . Touch not working after screen rotation Add a calibration_matrix for the touch device in weston.ini , or configure the touch coordinate transform via libinput. Conclusion In this hands-on you brought up a Waveshare 7" DSI display on the FRDM-IMX95-PRO board from a fresh SD card flash all the way to a working touch panel with live camera video. Key takeaways: Flashed a BSP image to the SD card with UUU and switched the board to SD boot. Connected the DSI panel correctly (FPC orientation, 5V power, and the required I2C link). Selected the matching device tree in U-Boot so the panel enumerates at 1024×600. Controlled backlight brightness, rotated the display in Weston, validated touch with evtest , and verified the camera path with GStreamer. Be sure to watch the module video above to see each step in action, and explore the rest of the FRDM-IMX95-PRO Training Hub for more hands-on modules.

  FRDM i.MX 95 Pro · Hands-On Series GoPoint — Running Pre-Built Demos September 2026  |  FRDM i.MX 95 Pro Hands-On Series   Introduction Discover what your FRDM i.MX 95 Pro can do — right out of the box. This hands-on walks you through the full range of pre-built demo categories available through GoPoint on the FRDM i.MX 95 Pro board. From neural processing and machine learning to GPU-accelerated graphics, each demo showcases the real-world capabilities of NXP's i.MX 95 application processor — no custom code required. The hands-on covers the following topics: Launching GoPoint on the Weston desktop Exploring the available demo categories (NPU, ML, GPU) Running NPU demos with the Ara240 module Running ML and GPU demos By the end of this hands-on, you will be able to: Navigate the GoPoint interface on Weston Identify the available demo categories (NPU, ML, and GPU) Launch and run pre-built demos on your FRDM i.MX 95 Pro board Understand the hardware requirements for each demo type   Hardware & Prerequisites Before starting, make sure you have the following items ready: Required Hardware FRDM-IMX95-PRO board (booted from eMMC) HDMI display Mouse Keyboard USB camera Ara240 module (required for NPU demos) Optional Hardware EXPI-OS08A20 camera module — covered in the separate EXPI-OS08A20 Camera + ISP Pipeline hands-on Note: The board must be booted from eMMC with the pre-loaded BSP image before launching GoPoint. Ensure your display is connected via HDMI before powering on.   Watch the Hands-On Video A complete video walkthrough accompanies this hands-on. It demonstrates every step shown below — from opening GoPoint on Weston to running NPU, ML, and GPU demos live on the board. Watch it alongside the written steps for the best learning experience.   Steps to Run the Hands-On Follow the steps below to explore GoPoint and run the pre-built demos on your board. Step 1 — Launch GoPoint on Weston After the board boots into the Weston desktop environment, locate the GoPoint application icon on the desktop or in the application launcher. Click it to open the GoPoint demo browser. GoPoint provides a graphical interface that organises all available demos by category, making it easy to browse and launch them without any command-line interaction. Step 2 — Explore the Demo Categories Once GoPoint is open, you will see the main demo category tiles. The three primary categories available on the FRDM i.MX 95 Pro are: NPU Demos — Neural Processing Unit demos that leverage the Ara240 module for hardware-accelerated AI inference ML Demos — Machine learning demos running on the i.MX 95 application processor GPU Demos — Graphics Processing Unit demos showcasing GPU-accelerated rendering and compute Browse each category to see the individual demos available. Each demo tile shows its name, a brief description, and any special hardware it requires. Step 3 — Run NPU Demos (Ara240 Required) NPU demos require the Ara240 module to be attached to the board. Select any NPU demo from the GoPoint interface and click Run. GoPoint will automatically load the required AI model and launch the demo. The Ara240 module handles the neural network inference, delivering real-time results on-screen. Note: If AI/ML models are not yet present on the board, run the fetch_models command first (see the Troubleshooting section below). Step 4 — Run ML Demos ML demos run directly on the i.MX 95 application processor and do not require the Ara240 module. Select an ML demo from the GoPoint interface and click Run. These demos cover a range of machine learning use cases including image classification, object detection, and more. Step 5 — Run GPU Demos GPU demos showcase the graphics and compute capabilities of the i.MX 95's integrated GPU. Select a GPU demo from the GoPoint interface and click Run. These demos include GPU-accelerated graphics rendering and visual effects that highlight the board's multimedia performance.   Troubleshooting If you encounter issues while running GoPoint demos, use the table below to identify the symptom and the recommended action. Symptom What to Check Missing AI/ML models — demo fails to start or reports missing model files Fetch the required models using the commands below. Use --list to see available models and --repo-id to fetch a specific one: # List available models fetch_models --list # Fetch a specific model by repository ID fetch_models --repo-id Cannot download software requirements — network or SSL errors during model download The board's system clock may be incorrect, causing certificate validation to fail. Set the correct date and time, then retry: # Set the system date (replace with current date/time) date -s "MM/DD/YYYY HH:MM:SS" Board freeze — the board becomes unresponsive during a demo Reboot the board: reboot Corrupt download — a demo crashes immediately or shows unexpected errors after model download Remove the Python virtual environment ( venv ) for the affected demo and re-run it so GoPoint recreates a clean environment. The venv directory is located inside the demo's working folder. # Remove the venv of the corresponding demo, then relaunch it from GoPoint   Conclusion In this hands-on you explored the GoPoint application on the FRDM i.MX 95 Pro board and ran pre-built demos across three hardware-accelerated categories: Launched and navigated the GoPoint interface on the Weston desktop Ran NPU demos using the Ara240 neural processing module Ran ML demos on the i.MX 95 application processor Ran GPU demos showcasing the board's graphics capabilities Learned how to fetch AI/ML models and resolve common setup issues For a full visual walkthrough, watch the video in the Watch the Hands-On Video section above. To continue your learning journey, visit the FRDM i.MX 95 Pro Training Hub for the complete series of hands-on modules covering camera pipelines, connectivity, security, and more.

FRDM i.MX 95 Pro Hands-On: ARA240 DNPU AI Accelerator FRDM i.MX 95 Pro Hands-On Training Series  |  September 2026   Introduction This hands-on walks you through the ARA240 DNPU AI Accelerator integrated with the FRDM i.MX 95 Pro development board. The ARA240 is an M.2-form-factor neural processing unit that connects over PCIe and dramatically expands the board's AI inference capability — from classic computer-vision pipelines to large language models (LLMs) and vision-language models (VLMs) — all powered by NXP's eIQ software stack.   Item Details Host Board FRDM i.MX 95 Pro AI Accelerator ARA240 DNPU (up to 2 modules) BSP L6.18.20-2.0.0 (precompiled, available on the NXP website) Interface PCIe via M.2 Key-M slots J24 / J25   By the end of this hands-on you will be able to: Verify that the ARA240 DNPU is correctly detected by the system. List, download, and run AI models (CNN, LLM, VLM) on the accelerator. Measure DNPU performance metrics using the provided shell utilities. Configure and start the eIQ AAF Connector service to expose a REST API for AI inference. Send chat-completion requests to a locally running LLM through the connector's web interface. Troubleshoot the most common setup issues.   Hardware & Prerequisites Gather the following before starting: Hardware FRDM-IMX95-PRO development board ARA240 DNPU module (one or two, depending on your use case) Keyboard (for direct board interaction) Host machine with a web browser (to access the connector API UI) Internet connection (required for model downloads) M.2 Connector Reference Connector Purpose J24 M.2 Key-M slot — ARA240 Module #1 J25 M.2 Key-M slot — ARA240 Module #2 J9 Fan power supply for the module in J24 J10 Fan power supply for the module in J25 Software BSP L6.18.20-2.0.0 — precompiled image available on the NXP website.   Watch the Hands-On Video The video below walks through the complete ARA240 DNPU setup and demo flow on the FRDM i.MX 95 Pro, covering device detection, model download, inference testing, NPU metrics, and the eIQ AAF Connector in action. Watch it alongside the step-by-step instructions in the next section.   Steps to Run the Hands-On All commands below are run directly on the FRDM i.MX 95 Pro board (via serial console or SSH). The eIQ utilities are pre-installed in the BSP image. Step 1 — Verify Device Detection After powering on the board with the ARA240 module seated in J24 (and/or J25), confirm the accelerator is recognized by the system: # Device Detection & Status chip_info.sh The script prints the detected DNPU chip information. If nothing is returned, check the M.2 seating and fan-power connectors (J9/J10). Step 2 — List Available Models Use the fetch_models utility to see which AI models are available for download: # List available models fetch_models --list The output shows model IDs for CNN, LLM, and VLM workloads that are compatible with the ARA240. Step 3 — Download a Model Download a model by its repository ID. The example below fetches a 7-billion-parameter instruction-tuned LLM: # Download a specific model (example: Qwen2.5 7B) fetch_models --repo-id nxp/Qwen2.5-7B-Instruct-Ara240 Models are stored under /usr/share/ in subdirectories named cnn , llm , or vlm depending on the model type. Step 4 — Run Inference Performance Tests Once a model is downloaded, benchmark its inference performance on the DNPU: # Running Inference Tests run_model_perf.sh Step 5 — Measure DNPU Metrics Capture real-time NPU utilization and performance counters: # Measuring DNPU Metrics ara2_metrics.sh Step 6 — Configure and Start the eIQ AAF Connector The eIQ AAF Connector exposes a REST API (OpenAI-compatible) so any HTTP client or web application can send inference requests to the ARA240. Follow these steps: # Check whether the connector service is already running systemctl status eiq-aaf-connector.service # Start the connector service (systemd-managed) systemctl start eiq-aaf-connector.service # Stop the connector service when done systemctl stop eiq-aaf-connector.service # Edit the connector configuration (model path, port, etc.) vi /usr/share/eiq/aaf-connector/server_config.json # Alternatively, start the connector manually (foreground) /usr/share/eiq/aaf-connector/venv/bin/connector --host 0.0.0.0 --port 8000 Once the connector is running, open the interactive API documentation in a browser on your host machine (replace <board-ip> with the board's actual IP address): # Open the connector Web API interface in a browser http://<board-ip>:8000/docs Step 7 — Send a Chat Completion Request With the connector running and a downloaded LLM, you can send an OpenAI-compatible chat completion request directly from the API docs page or via any HTTP client: # Example chat completion payload (POST to /v1/chat/completions) { "model": "Qwen2.5-7B-Instruct", "messages": [ { "role": "system", "content": "You are a helpful assistant" }, { "role": "user", "content": "hello, how are you?" } ] }   Troubleshooting Symptom What to Check chip_info.sh returns nothing / DNPU not detected Verify the ARA240 module is firmly seated in J24 or J25. Confirm the fan-power cable is connected to J9 (for J24) or J10 (for J25). Reboot the board after reseating. fetch_models --list fails or model download hangs Check internet connectivity: ping 8.8.8.8 If DNS resolution fails, set it manually: echo nameserver 8.8.8.8 > /etc/resolv.conf Model not found after download Verify the model landed in the correct directory: ls /usr/share/<cnn|llm|vlm>/ Certificate or TLS errors during model download The board's system clock may be wrong. Set the correct date and time: date --set="18 SEP 2026 13:00:00" Then retry the download. Connector service fails to start Check journalctl -u eiq-aaf-connector.service for error details. Ensure server_config.json points to a valid downloaded model path.   Conclusion In this hands-on you: Connected the ARA240 DNPU AI Accelerator to the FRDM i.MX 95 Pro via PCIe (M.2 Key-M). Verified device detection and explored available AI models using the eIQ command-line utilities. Downloaded and benchmarked a large language model on the DNPU. Measured real-time NPU performance metrics with ara2_metrics.sh . Configured and launched the eIQ AAF Connector to expose an OpenAI-compatible REST API. Sent a live chat-completion request to a locally running LLM — entirely on the edge. For a full visual walkthrough, watch the demo video above. Explore the rest of the FRDM i.MX 95 Pro Hands-On Training Hub for additional modules covering cameras, connectivity, multimedia, and more.

Getting Started Video:     This guide provides step-by-step instructions on how to verify successful communication and the runtime software environment to interface with the Ara240 module with the FRDM i.MX 95 Pro development board.   Out of the Box:   Get Familiar with the Ara240 Module   Ara240 Module [Back view] Ara240 Module [Top view]                   Connecting the M.2 Module   This section explains how to connect Ara240, a discrete module, to the FRDM i.MX 95 Pro development board. The instructions in the FRDM i.MX 95 Pro Getting Start Guide will walk you through the boot-up process for the pre-loaded Embedded Linux image on the board and how to connect the USB debug cable. For additional details, see the official FRDM i.MX 95 Pro Development Board documentation. References: FRDM i.MX 95 Pro Quick Start Guide FRDM i.MX 95 Pro Development Board product page  FRDM i.MX 95 Pro Getting started page Getting Started with ARA2-M2-16G-GT Follow the steps below to connect the Ara240 module to the FRDM i.MX 95 Pro development board:   Important: Ensure the board is powered off before making any connections. Insert the Ara240 module into the M.2 Key-M socket on the FRDM i.MX 95 Pro development board. Using the screw provided, secure the module. Connect the fan cable to the board’s fan header (refer to the FRDM i.MX 95 Pro board documentation for the exact header location).   "How to connect two Ara240 devices?"   The figure below illustrates the connection of Ara240 devices to the two M.2 Key-M slots on the FRDM i.MX 95 Pro development board. You can install one Ara240 device in either slot or connect two devices simultaneously by using both slots.     Connect the Ara240 to the FRDM i.MX 95 Pro development board.       Power on the Board   Follow the instructions to power on (boot) the board found in the Getting Started with FRDM-IMX95-Pro. After powering on, verify that the fan and green LED indicators Ara240 module are on are on.       Get the Software   This section will walk you through the Ara240 Runtime software development kit (SDK), a streamlined subset of the Ara240 SDK designed for rapid enablement and execution on NXP platforms. The Runtime SDK simplifies installation and configuration, enabling developers to quickly deploy and run AI/ML workloads on the Ara240 module with minimal effort.   Overview   Refer to Ara240 software release notes for details on the Ara240 software development kit (SDK) The Getting Started page for Ara240 only outlines usage on specific i.MX development platforms For any other platforms please reach out to your NXP representative for guidance.       Q2'26 BSP (L6.18.20-2.0.0) onwards runtime environment for i.MX 8MP and i.MX 95 boards is packed with Linux BSP.       Module Enumeration and Software Configuration   This section provides instructions to verify proper installation of Ara240 module and configuration of the Ara240 Runtime SDK on the FRDM i.MX 95 Pro development board. Verify Device Detection   Once the board has successfully booted, connect to the serial debug port to monitor system logs. To confirm that the Ara240 module is being detected by the board, run the following command: $ lspci | grep 1e58   Expected output: 0000:01:00.0 Processing accelerators: Device 1e58:0002 (rev 02)     Enable Ara240 device   For quick enablement, the Ara240 Runtime SDK starts at boot time. Refer to the Ara240 Runtime SDK documentation for detailed instructions and environment setup steps.   Q2'26 BSP (L6.18.20-2.0.0) onwards runtime environment for i.MX 8MP and i.MX 95 boards is packed with Linux BSP.       Developer Experience   This section provides an overview of Ara240 runtime software enablement using the FRDM i.MX 95 Pro development board. Verify Setup Environment   Use the following guidance on how to connect required devices. For most of the demos, you would need a camera, keyboard, mouse, internet connection and a HDMI display monitor. Setup preparation for FRDM i.MX 95 Pro board    NOTE: You might need to use a USB hub to connect keyboard, mouse and camera at the same time.   Runtime setup Description   Runtime SDK delivers a complete runtime environment that enables AI/ML acceleration on the Ara240 module. To run demo applications, ensure that the Ara240 bring-up process has been successfully completed and the system is ready for demo evaluation. Refer to the Runtime SDK documentation for detailed guidance on: Verifying correct installation of the Runtime SDK. Checking and updating the Ara240 firmware version. Validating proxy service bring-up status. Executing benchmark tests on Ara240. Following these steps ensures that the module is properly initialized and ready for use. Ara240 supports the execution of CNNs, LLMs, VLMs, and agentic frameworks, enabling advanced AI workloads to run directly on Ara240. For comprehensive examples and end-to-end workflow guidance, please refer to the Ara SDK documentation page.   Ara240 Demos   Henceforth Q2'26 Linux BSP, GoPoint can be launched to explore preselected Ara240 demonstrations included in the NXP provided Linux Board Support Package. User Guide: GPNTUG: GoPoint for i.MX Applications Processors User Guide   

From TinyML to advanced edge AI and GenAI, discover how to build intelligent systems directly on-device with FRDM, no cloud dependency required.

Not all MCX A devices expose the same combination of ADCs, SmartDMA, MAU, or connectivity interfaces—and choosing the wrong evaluation board can limit what you can prototype. This article provides a clear mapping between MCX A families and FRDM platforms, helping you align hardware capabilities with system requirements.

This MCXW72 training video talk about the Lifecycle state model, explain in detail the purpose, and security recommendations for each state.  Training shows the fuses involved in this process to advance lifecycle and enable the basic security features like Secure Boot and Secure Debug. Video also includes examples about how to use MCUXpresso Secure Provisioning Tool (SEC) to create Root of Trust Key Hash (RoTKTH) and SB3KDK Encryption key as well as hoe to active debug authentication before to move Lifecycle states.

Getting Started Video:   This guide provides step-by-step instructions on how to verify successful communication with the Ara240 module and the runtime software environment to interface  with the FRDM i.MX 95 development board.   Out of the Box   Get Familiar with the Ara240 Module   Ara240 Module [Top view] Ara240 Module [Back view]                Connecting the M.2 Module   This section explains how to connect Ara240, a discrete module, to the FRDM i.MX 95 development board. The instructions in the FRDM i.MX 95 Quick Start Guide will walk you through the boot-up process for the pre-loaded Embedded Linux image on the board and how to connect the USB debug cable. For additional details, see the official FRDM i.MX 95 Development Board documentation. References: FRDM i.MX 95 Quick Start Guide FRDM i.MX 95 Development Board product page FRDM i.MX 95 getting started page Getting Started with ARA2-M2-16G-GT Follow the steps below to connect the Ara240 module to the FRDM i.MX 95 development board: Important: Ensure the board is powered off before making any connections. Insert the Ara240 module into the M.2 Key-M socket on the FRDM i.MX 95 development board. Using the screw provided, secure the module. Connect the fan cable to the board’s fan header (refer to the FRDM i.MX 95 board documentation for the exact header location). Connect the Ara240 to the FRDM i.MX 95 development board.     Power on the Board   Follow the instructions to power on (boot) the board found in the Getting Started with FRDM-IMX95. After powering on, verify that the fan and green LED indicators Ara240 module are on are on.   Get the Software   This section will walk you through the Ara240 Runtime software development kit (SDK), a streamlined subset of the Ara240 SDK designed for rapid enablement and execution on NXP platforms. The Runtime SDK simplifies installation and configuration, enabling developers to quickly deploy and run AI/ML workloads on the Ara240 module with minimal effort. Overview   Refer to Ara240 software release notes for details on the Ara240 software development kit (SDK) The Getting Started page for Ara240 only outlines usage on specific i.MX development platforms For any other platforms please reach out to your NXP representative for guidance.   Module Enumeration and Software Configuration   This section provides instructions to verify proper installation of Ara240 module and configuration of the Ara240 Runtime SDK on the FRDM i.MX 95 development board. Verify Device Detection   Once the board has successfully booted, connect to the serial debug port to monitor system logs. To confirm that the Ara240 module is being detected by the board, run the following command: $ lspci | grep 1e58   Expected output: 0000:01:00.0 Processing accelerators: Device 1e58:0002 (rev 02)   Enable Ara240 device   For quick enablement, the Ara240 Runtime SDK starts at boot time. Refer to the Ara240 Runtime SDK documentation for detailed instructions and environment setup steps.   Developer Experience   This section provides an overview of Ara240 runtime software enablement using the FRDM i.MX 95 development board. Verify Setup Environment   Use the following guidance on how to connect required devices. For most of the demos, you would need a camera, keyboard, mouse, internet connection and a HDMI display monitor. Setup preparation for FRDM i.MX 95 board [Top view]   Setup preparation for FRDM i.MX 95 board [Back view]   NOTE: You might need to use a USB hub to connect keyboard, mouse and camera at the same time.   Runtime setup Description:   Runtime SDK delivers a complete runtime environment that enables AI/ML acceleration on the Ara240 module. To run demo applications, ensure that the Ara240 bring-up process has been successfully completed and the system is ready for demo evaluation. Refer to the Runtime SDK documentation for detailed guidance on: Verifying correct installation of the Runtime SDK. Checking and updating the Ara240 firmware version. Validating proxy service bring-up status. Executing benchmark tests on Ara240. Following these steps ensures that the module is properly initialized and ready for use. Ara240 supports the execution of CNNs, LLMs, VLMs, and agentic frameworks, enabling advanced AI workloads to run directly on Ara. For comprehensive examples and end-to-end workflow guidance, please refer to the Ara SDK documentation page.

Unlike MCXW 71 MCU, MCXW 72 supports an Open NBU. This means that NBU firmware source code is exposed to user. On MCXW 71 MCU, NBU firmware is NXP proprietary; it is not user customizable.