Merge pull request #3477 from anupras-mohapatra-arm/embedded-and-microcontrollers

Summaries and FAQs for first 20 embedded and microcontrollers LPs

Author: jasonrandrews

content/learning-paths/embedded-and-microcontrollers/advanced_soc/_index.md

@@ -15,11 +15,56 @@ learning_objectives:
 prerequisites:
     - Some familiarity with Verilog
     - Basic understanding of System on Chip design
-    - A 'Zybo Z7-10' development board 
+    - A 'Zybo Z7-10' development board
+
+# START generated_summary_faq
+generated_summary_faq:
+  template_version: summary-faq-v3
+  generated_at: '2026-07-08T15:18:26Z'
+  generator: ai
+  ai_assisted: true
+  ai_review_required: true
+  model: gpt-5
+  prompt_template: summary-faq-v3
+  source_hash: d8c48c293b2d316d5e68e18ab9e81157ad114a64cf2efa6951374a55d25238d6
+  summary_generated_at: '2026-07-08T15:18:26Z'
+  summary_source_hash: d8c48c293b2d316d5e68e18ab9e81157ad114a64cf2efa6951374a55d25238d6
+  faq_generated_at: '2026-07-08T15:18:26Z'
+  faq_source_hash: d8c48c293b2d316d5e68e18ab9e81157ad114a64cf2efa6951374a55d25238d6
+  summary: >-
+    You'll design and integrate a custom AXI4-Lite peripheral
+    with the ZYNQ Processing System on a Zybo Z7-10 board. First, you'll create a clean Vivado workspace. Then, you'll follow the **Create and Package New IP** flow to build the peripheral, and add external ports for LEDs and
+    switches with the shown bit widths. You'll create a block design that connects the peripheral to
+    the Cortex-A9–based processing system, followed by generating an HDL wrapper and a bitstream.
+    Using Vitis IDE, you'll write a bare-metal C program that reads switch inputs over AXI-Lite and drives LED outputs.
+    You'll see LEDs responding to switch states through the custom IP.
+  faqs:
+  - question: What should I check about the Vivado workspace path before creating the project?
+    answer: >-
+      Use a path with no spaces. A simple top-level directory such as `C:/Workspace` avoids path
+      issues.
+  - question: Which option should I select in the **Create and Package New IP** wizard?
+    answer: >-
+      Select **Create a new AXI4 peripheral**. This generates the template files for an AXI-compliant
+      custom IP block.
+  - question: How do I know the `led` and `sw` ports are configured correctly?
+    answer: >-
+      Confirm `led` is an output and `sw` is an input, each with the width shown in the steps (four
+      bits). They should appear as external ports in the block design and connect to your custom
+      peripheral.
+  - question: What should I do before generating the bitstream?
+    answer: >-
+      Create the HDL wrapper for `design1.bd` using the default options and save all changes. Then
+      proceed to generate the bitstream.
+  - question: What result should I expect when I run the C application in Vitis?
+    answer: >-
+      The LEDs change based on the state of the switches. Toggling a switch updates the corresponding
+      LED as defined by your application.
+# END generated_summary_faq
 
 author: Pareena Verma
 
-generate_summary_faq: true
+generate_summary_faq: false
 rerun_summary: false
 rerun_faqs: false
 

content/learning-paths/embedded-and-microcontrollers/alif-image-classification/_index.md

@@ -20,9 +20,57 @@ prerequisites:
     - A development machine running macOS on Apple Silicon with Visual Studio Code installed
     - An AWS account or access to an Arm-based cloud instance for native Arm compilation
 
+# START generated_summary_faq
+generated_summary_faq:
+  template_version: summary-faq-v3
+  generated_at: '2026-07-08T15:19:18Z'
+  generator: ai
+  ai_assisted: true
+  ai_review_required: true
+  model: gpt-5
+  prompt_template: summary-faq-v3
+  source_hash: 8585bb59efa67b3a92314e4382339fc5c0a14bb458931c0d98f2748379003857
+  summary_generated_at: '2026-07-08T15:19:18Z'
+  summary_source_hash: 8585bb59efa67b3a92314e4382339fc5c0a14bb458931c0d98f2748379003857
+  faq_generated_at: '2026-07-08T15:19:18Z'
+  faq_source_hash: 8585bb59efa67b3a92314e4382339fc5c0a14bb458931c0d98f2748379003857
+  summary: >-
+    You'll deploy a MobileNetV2 image classifier on the Alif Ensemble
+    E8 DevKit by compiling the model and runtime for the Ethos-U85 NPU, building a CMSIS project,
+    and running inference with SEGGER RTT output. First, you'll validate the board, debug probe, and flashing
+    workflow, then use an Arm-based cloud instance to produce ExecuTorch static libraries and
+    an Ethos-U85–targeted model. Next, you'll create an `mv2_runner` firmware project from the Blinky
+    template, add the provided application code that initializes the NPU and executes inference
+    on a test image, and integrate RTT for result reporting. Finally, you'll make memory layout
+    and linker updates so the model, runtime, and SRAM working set fit, enabling real-time classification
+    on the device.
+  faqs:
+  - question: Which core should I target when flashing and debugging the firmware?
+    answer: >-
+      Use the Cortex-M55 High-Performance (HP) core to orchestrate inference on the Ethos-U85.
+      The steps assume this core for building, flashing, and running the application.
+  - question: What artifacts should I expect after compiling on the Arm cloud instance?
+    answer: >-
+      You'll have ExecuTorch static libraries and a compiled MobileNetV2 model targeted for
+      the Ethos-U85. These outputs are linked into the `mv2_runner` firmware project.
+  - question: After duplicating the Blinky example, which project files need to be updated?
+    answer: >-
+      Rename `blinky.cproject.yml` to `mv2_runner.cproject.yml` and replace internal references from
+      `blinky` to `mv2_runner`. This establishes a new CMSIS project for the application.
+  - question: Where do I place the provided `main.cpp` and how do I verify it works?
+    answer: >-
+      Place `main.cpp` in the `mv2_runner` project directory as instructed. When you flash and run
+      the firmware, check the SEGGER RTT console for the printed classification result.
+  - question: What memory changes are required for the model and runtime to fit?
+    answer: >-
+      Increase MRAM allocation for the embedded model (about 3.7 MB) and code (around 800 KB),
+      and provision approximately 7.6 MB of SRAM for inference buffers. Update stack and heap sizes,
+      and the linker script in the CMSIS project accordingly.
+# END generated_summary_faq
+
 author: Gabriel Peterson
 
-generate_summary_faq: true
+generate_summary_faq: false
 rerun_summary: false
 rerun_faqs: false
 

content/learning-paths/embedded-and-microcontrollers/arduino-pico/_index.md

@@ -19,9 +19,57 @@ prerequisites:
     - A [PIR sensor](https://www.amazon.com/HiLetgo-HC-SR501-Infrared-Sensor-Arduino/dp/B07KZW86YR/ref=sr_1_3?keywords=pir+sensor&qid=1698432931&sr=8-3) for detecting motion
     - A [peizo-electric buzzer](https://www.amazon.com/mxuteuk-Electronic-Computers-Printers-Components/dp/B07VK1GJ9X/ref=sr_1_4?crid=2FAXYI17HZKDB&keywords=piezo+buzzer&qid=1698432968&sprefix=peizo%2Caps%2C148&sr=8-4) for signaling motion
 
+# START generated_summary_faq
+generated_summary_faq:
+  template_version: summary-faq-v3
+  generated_at: '2026-07-08T15:19:51Z'
+  generator: ai
+  ai_assisted: true
+  ai_review_required: true
+  model: gpt-5
+  prompt_template: summary-faq-v3
+  source_hash: 3ddb97eb97a4c7ede7951410086198ee793a9d452a79b607f211873971bd375d
+  summary_generated_at: '2026-07-08T15:19:51Z'
+  summary_source_hash: 3ddb97eb97a4c7ede7951410086198ee793a9d452a79b607f211873971bd375d
+  faq_generated_at: '2026-07-08T15:19:51Z'
+  faq_source_hash: 3ddb97eb97a4c7ede7951410086198ee793a9d452a79b607f211873971bd375d
+  summary: >-
+    You'll learn about embedded programming and build a motion detector with a Raspberry Pi Pico (RP2040, Cortex-M0+). First, you'll
+    compare application and embedded software stacks, then apply those differences by wiring a
+    passive infrared (PIR) sensor and a piezo buzzer to the Pico. Using the Arduino IDE, you'll
+    write a simple sketch that configures GPIO, registers an interrupt handler, and reacts to
+    external changes without polling. Finally, you'll deploy to bare metal on the Pico
+    and validate that motion events trigger the buzzer immediately, demonstrating how hardware
+    interrupts drive responsive behavior on a small Arm microcontroller.
+  faqs:
+  - question: Which board and port should I select in the Arduino IDE before uploading?
+    answer: >-
+      Select an RP2040-based board from the installed package and choose the USB/serial port associated
+      with the Raspberry Pi Pico. If the upload fails, recheck both the board and port selections.
+  - question: How should I wire the PIR sensor and buzzer to match the sketch?
+    answer: >-
+      Connect the PIR output to a digital input pin and the buzzer to a digital output pin with
+      a common ground. Make sure the pin numbers in your wiring match the pin definitions used
+      in the sketch.
+  - question: How do I know the interrupt is working instead of polling?
+    answer: >-
+      When motion occurs, the buzzer responds immediately without waiting for a timed loop. If
+      you see an instant reaction when the PIR output changes, the interrupt handler is being
+      invoked.
+  - question: What should I check if the buzzer never reacts to motion?
+    answer: >-
+      Verify power and common ground, confirm the selected GPIO pins match the sketch, and ensure
+      the input is configured for the PIR signal and the output drives the buzzer. Also recheck
+      that the correct RP2040 board and port are selected and that the upload completed successfully.
+  - question: Does this project use an RTOS?
+    answer: >-
+      No. The example runs on bare metal using Arduino tooling on the RP2040. Any RTOS stack references
+      are for context about typical Arm embedded architectures, not for this build.
+# END generated_summary_faq
+
 author: Michael Hall
 
-generate_summary_faq: true
+generate_summary_faq: false
 rerun_summary: false
 rerun_faqs: false
 

content/learning-paths/embedded-and-microcontrollers/armds/_index.md

@@ -14,9 +14,55 @@ learning_objectives:
 prerequisites:
     - Some familiarity with embedded programming is assumed
 
+# START generated_summary_faq
+generated_summary_faq:
+  template_version: summary-faq-v3
+  generated_at: '2026-07-08T15:20:26Z'
+  generator: ai
+  ai_assisted: true
+  ai_review_required: true
+  model: gpt-5
+  prompt_template: summary-faq-v3
+  source_hash: 0103f51d42c230dbe75ff5b78ac15a33dfd2f2c0f4906fb665a8dd681512d2e1
+  summary_generated_at: '2026-07-08T15:20:26Z'
+  summary_source_hash: 0103f51d42c230dbe75ff5b78ac15a33dfd2f2c0f4906fb665a8dd681512d2e1
+  faq_generated_at: '2026-07-08T15:20:26Z'
+  faq_source_hash: 0103f51d42c230dbe75ff5b78ac15a33dfd2f2c0f4906fb665a8dd681512d2e1
+  summary: >-
+    You'll launch Arm Development Studio, import and
+    build a supplied example, and debug it on a Cortex-M Fixed Virtual Platform (FVP) or
+    on hardware via a DSTREAM probe. Using the ready-to-use `startup_Cortex-M3_AC6_FVP.launch` configuration,
+    you'll inspect the debug settings and start a session that runs without target hardware
+    on an MPS2+-based Cortex-M3 (AN385) model. You'll also see where to adjust the project
+    to use a different Arm Compiler for Embedded version when required. By the end, you'll
+    build and execute under the IDE with a working debug connection on either an FVP or a supported
+    board.
+  faqs:
+  - question: How do I launch Arm Development Studio from the command line?
+    answer: >-
+      Run `armds_ide` from a terminal to open the IDE.
+  - question: What should I do when the workspace configuration pane appears?
+    answer: >-
+      Click **Finish** to accept the default setup. The workspace is the base directory where the
+      IDE stores your projects and build output.
+  - question: Do I need target hardware to run the example?
+    answer: >-
+      No. Use the provided Fixed Virtual Platforms to execute and debug the example without hardware.
+      If hardware is available, you can run it on a board using a DSTREAM debug probe.
+  - question: Where is the FVP debug configuration for the example?
+    answer: >-
+      Open `startup_Cortex-M3_AC6_FVP.launch` in the project folder. Double-click the file to inspect
+      the predefined settings before starting a debug session.
+  - question: How do I select a different Arm Compiler for Embedded version for the project?
+    answer: >-
+      Install the required compiler version using the Arm Compiler for Embedded install guide.
+      Then open **Project > Properties** and change the compiler used by the project in the build
+      settings.
+# END generated_summary_faq
+
 author: Ronan Synnott
 
-generate_summary_faq: true
+generate_summary_faq: false
 rerun_summary: false
 rerun_faqs: false
 
@@ -56,4 +102,3 @@ weight: 1                       # _index.md always has weight of 1 to order corr
 layout: "learningpathall"       # All files under learning paths have this same wrapper
 learning_path_main_page: "yes"  # This should be surfaced when looking for related content. Only set for _index.md of learning path content.
 ---
-

content/learning-paths/embedded-and-microcontrollers/asm/_index.md

@@ -4,9 +4,55 @@ title: Write Arm Assembler functions
 minutes_to_complete: 60
 description: Learn how to write mixed C and assembly programs for Cortex-M microcontrollers using Keil MDK, following Arm Procedure Call Standard conventions.
 
+# START generated_summary_faq
+generated_summary_faq:
+  template_version: summary-faq-v3
+  generated_at: '2026-07-08T15:21:04Z'
+  generator: ai
+  ai_assisted: true
+  ai_review_required: true
+  model: gpt-5
+  prompt_template: summary-faq-v3
+  source_hash: 24245102b7b6cefd0d4f67fbfaff1fb27c913de33665929ec3cb15293a1b3b51
+  summary_generated_at: '2026-07-08T15:21:04Z'
+  summary_source_hash: 24245102b7b6cefd0d4f67fbfaff1fb27c913de33665929ec3cb15293a1b3b51
+  faq_generated_at: '2026-07-08T15:21:04Z'
+  faq_source_hash: 24245102b7b6cefd0d4f67fbfaff1fb27c913de33665929ec3cb15293a1b3b51
+  summary: >-
+    You'll build a small mixed C and assembly program for
+    Cortex-M using Keil MDK. First, you'll set up a project in either Keil Studio (VS Code) or μVision for
+    the `ARMCM4` target, add CMSIS core and startup components where required, and configure the
+    Cortex-M4 Fixed Virtual Platform as the debug target. Then, you'll write
+    two assembly subroutines for string copy and capitalization, called from a C `main()` function,
+    while following the Arm Procedure Call Standard. By stepping through the program in the debugger,
+    you'll observe register use and memory updates and verify that the destination buffer reflects
+    the copied and capitalized string.
+  faqs:
+  - question: Do I need a physical board to run the examples?
+    answer: >-
+      No. The steps use the Cortex-M4 Fixed Virtual Platform provided with MDK, so you can run
+      and debug without hardware.
+  - question: Which target device should I select when creating the project?
+    answer: >-
+      Select **ARMCM4** as the target device. This applies to both Keil Studio (VS Code) and μVision.
+  - question: How do I configure debugging to use the Fixed Virtual Platform in μVision?
+    answer: >-
+      Open **Options for Target**, go to the **Debug** tab, and select **Models Cortex-M Debugger**. Use this
+      configuration to run on the Cortex-M4 FVP.
+  - question: Which components do I add when setting up the μVision project?
+    answer: >-
+      Add **CMSIS > Core and Device > Startup** when prompted for software components. This prepares
+      the project for the ARMCM4 device and startup sequence.
+  - question: What result should I expect when the C and assembly functions run correctly?
+    answer: >-
+      The destination buffer contains a copy of the source string, and the capitalization routine
+      updates characters as intended. Step through the code to observe register usage and memory
+      changes that match these operations.
+# END generated_summary_faq
+
 author: Ronan Synnott
 
-generate_summary_faq: true
+generate_summary_faq: false
 rerun_summary: false
 rerun_faqs: false
 
@@ -46,4 +92,3 @@ layout: "learningpathall"       # All files under learning paths have this same
 learning_path_main_page: "yes"  # Indicates this should be surfaced when looking for related content. Only set for _index.md of learning path content.
 # ================================================================================
 ---
-

content/learning-paths/embedded-and-microcontrollers/avh_balena/_index.md

@@ -18,9 +18,51 @@ prerequisites:
     - A Linux machine with root access
     - Some familiarity with embedded Linux
 
+# START generated_summary_faq
+generated_summary_faq:
+  template_version: summary-faq-v3
+  generated_at: '2026-07-08T15:21:56Z'
+  generator: ai
+  ai_assisted: true
+  ai_review_required: true
+  model: gpt-5
+  prompt_template: summary-faq-v3
+  source_hash: 983afd3fcc565266c8f12588086e36d736540e23d0e748c94b5d2a45ab53d6ab
+  summary_generated_at: '2026-07-08T15:21:56Z'
+  summary_source_hash: 983afd3fcc565266c8f12588086e36d736540e23d0e748c94b5d2a45ab53d6ab
+  faq_generated_at: '2026-07-08T15:21:56Z'
+  faq_source_hash: 983afd3fcc565266c8f12588086e36d736540e23d0e748c94b5d2a45ab53d6ab
+  summary: >-
+    You'll prepare a BalenaOS image for Arm Virtual Hardware,
+    provisioning a virtual Raspberry Pi 4, and deploy a pre-built application from Balena Hub.
+    First, you'll create a Balena Cloud account and fleet to organize deployments. Then, you'll start an Arm Virtual
+    Hardware device and upload the custom BalenaOS firmware. With the device running, you'll navigate
+    from the Balena Cloud dashboard to Balena Hub and select a ready-made application to deploy.
+    You'll then deploy an example app that uses the `balena-app` Grafana dashboard to visualize the device state, providing
+    a quick way to validate that the virtual Raspberry Pi 4 is up, connected, and receiving an
+    application from Balena Cloud.
+  faqs:
+  - question: What device type should I select in Arm Virtual Hardware?
+    answer: >-
+      Choose **Raspberry Pi 4** when creating the device in Arm Virtual Hardware.
+  - question: Which firmware option and file do I use when creating the AVH device?
+    answer: >-
+      Use the **Upload your own firmware** option and select the `balenaos_rpi4b.zip` file.
+  - question: How do I access Balena Hub from the Balena Cloud dashboard?
+    answer: >-
+      Click the **Balena Hub** button in the top right corner of the Balena Cloud dashboard.
+  - question: Which example application should I deploy from Balena Hub?
+    answer: >-
+      Open **Apps** on Balena Hub and search for `balena-app`. This example provides a Grafana dashboard.
+  - question: What result should I expect after deploying the Grafana example?
+    answer: >-
+      The Grafana dashboard displays the state of your BalenaOS device, confirming that the application
+      deployed to the virtual Raspberry Pi 4.
+# END generated_summary_faq
+
 author: Michael Hall
 
-generate_summary_faq: true
+generate_summary_faq: false
 rerun_summary: false
 rerun_faqs: false