applications: machine_learning: Add configuration for nRF54L15 DK

Adds configuration files for nRF54L15 support.
Support for simulated signals only.

Signed-off-by: Marcin Jelinski <[email protected]>

Author: maje-emb

applications/machine_learning/app_desc.rst

@@ -34,6 +34,9 @@ By default, the following sensors are used by the application:
 * nRF5340 DK - Simulated sensor (:ref:`sensor_sim`).
   The simulated sensor generates predefined waves as acceleration.
   This development kit does not have a built-in accelerometer.
+* nRF54L15 DK - Simulated sensor (:ref:`sensor_sim`).
+  The simulated sensor generates predefined waves as acceleration.
+  This development kit does not have a built-in accelerometer.
 * nRF54H20 DK - The development kit does not have a built-in accelerometer.
   However, it supports the following configurations:
 
@@ -52,6 +55,7 @@ By default, the following transports are used:
 * Thingy:53 uses :ref:`nus_service_readme`.
 * The nRF52840 DK uses :ref:`zephyr:uart_api`.
 * The nRF5340 DK uses :ref:`zephyr:uart_api`.
+* The nRF54L15 DK uses :ref:`zephyr:uart_api`.
 * The nRF54H20 DK uses :ref:`nus_service_readme`.
 
 Machine learning model
@@ -72,7 +76,7 @@ By default, the application uses pre-trained machine learning models deployed in
   * ``tap`` - The device is tapped while placed on a flat surface.
 
   Unknown gestures, such as shaking the device, are recognized as anomalies.
-* Both the nRF52840 DK and the nRF5340 DK use the `nRF Connect SDK simulated sensor machine learning model`_.
+* The nRF52840, nRF5340 and nRF54L15 DKs use the `nRF Connect SDK simulated sensor machine learning model`_.
   The model uses simulated sensor data to recognize the following simulated wave types:
 
   * ``sine``
@@ -232,6 +236,11 @@ By default, the following buttons are used by the application:
       * **Button 1** switches between data forwarding and running a machine learning model.
       * **Button 3** changes the signal generated by the simulated sensor.
 
+   .. group-tab:: nRF54L15 DK
+
+      * **Button 0** switches between data forwarding and running a machine learning model.
+      * **Button 2** changes the signal generated by the simulated sensor.
+
    .. group-tab:: nRF54H20 DK
 
       **Button 0** button switches between data forwarding and running the machine learning model.
@@ -266,30 +275,51 @@ By default, the application uses the following LED effects:
          The LED effect is overridden on the next successful detection.
       * If the device forwards data, the LED color turns red and uses the following blinking patterns:
 
-         * LED blinks slowly if it is not connected.
-         * LED blinks with an average frequency if it is connected but is not actively forwarding data.
-         * LED blinks rapidly if it is connected and is actively forwarding data.
+         * Blinks slowly if it is not connected.
+         * Blinks with an average frequency if it is connected but is not actively forwarding data.
+         * Blinks rapidly if it is connected and is actively forwarding data.
 
    .. group-tab:: nRF52840 and nRF5340 DKs
 
       Both nRF5340 DK and nRF52840 DK use monochromatic LEDs to display the application state.
-      The **LED1** displays the application state, and the **LED2** displays the signal generated by the simulated sensor.
+      The **LED1** displays the application state and the **LED2** displays the signal generated by the simulated sensor.
 
       * If the device is returning the machine learning prediction results, the **LED1** blinks for a predefined number of times and then turns off for a period of time.
         Then the sequence is repeated.
         The machine learning result is represented by the number of blinks:
 
-         * ``sine`` - 1 blink
-         * ``triangle`` - 2 blinks
-         * ``square`` - 3 blinks
-         * ``idle`` - 4 blinks
+         * ``sine`` - one blink
+         * ``triangle`` - two blinks
+         * ``square`` - three blinks
+         * ``idle`` - four blinks
 
          If the machine learning model is running but has not detected anything yet or has detected an anomaly, the **LED1** is breathing.
       * If the device forwards data, the **LED1** has the following blinking patterns:
 
-         * LED blinks slowly if it is not connected.
-         * LED blinks with an average frequency if it is connected but is not actively forwarding data.
-         * LED blinks rapidly if it is connected and is actively forwarding data.
+         * Blinks slowly if it is not connected.
+         * Blinks with an average frequency if it is connected but is not actively forwarding data.
+         * Blinks rapidly if it is connected and is actively forwarding data.
+
+   .. group-tab:: nRF54L15 DK
+
+      The nRF54L15 DK uses monochromatic LEDs to display the application state.
+      The **LED1** displays the application state and the **LED3** displays the signal generated by the simulated sensor.
+
+      * If the device is returning the machine learning prediction results, the **LED1** blinks for a predefined number of times and then turns off for a period of time.
+        Then the sequence is repeated.
+        The machine learning result is represented by the number of blinks:
+
+         * ``sine`` - one blink
+         * ``triangle`` - two blinks
+         * ``square`` - three blinks
+         * ``idle`` - four blinks
+
+         If the machine learning model is running but has not detected anything yet or has detected an anomaly, the **LED1** is breathing.
+      * If the device forwards data, the **LED1** has the following blinking patterns:
+
+         * Blinks slowly if it is not connected.
+         * Blinks with an average frequency if it is connected but is not actively forwarding data.
+         * Blinks rapidly if it is connected and is actively forwarding data.
 
    .. group-tab:: nRF54H20 DK
       nRF54H20 DK uses monochromatic LEDs to display the application state.
@@ -306,9 +336,9 @@ By default, the application uses the following LED effects:
          If the machine learning model is running, but it has not detected anything yet or the ``idle`` state is detected, **LED0**, **LED1**, and **LED2**, keep blinking.
       * If the device forwards data, **LED0**, **LED1** and **LED2** has the following blinking patterns:
 
-         * LED blinks slowly if it is not connected.
-         * LED blinks with an average frequency if it is connected, but is not actively forwarding data.
-         * LED blinks rapidly if it is connected and is actively forwarding data.
+         * Blinks slowly if it is not connected.
+         * Blinks with an average frequency if it is connected, but is not actively forwarding data.
+         * Blinks rapidly if it is connected and is actively forwarding data.
 
 .. _nrf_machine_learning_app_configuration:
 
@@ -525,14 +555,14 @@ After programming the application, perform the following steps to test the nRF M
 
 1. Turn on the development kit.
    The application starts in a mode that runs the machine learning model.
-   Initially, **LED2** displays the LED effect representing ``sine`` wave (1 blink), and **LED1** is breathing, because the signal was not yet recognized by the machine learning model.
+   Initially, **LED2** displays the LED effect representing ``sine`` wave (one blink), and **LED1** is breathing, because the signal was not yet recognized by the machine learning model.
    After a brief delay, the machine learning model recognizes the simulated signal.
    **LED1** and **LED2** display the same LED effect.
 #. Press **Button 3** to change the generated acceleration signal.
    Right after the signal change, the effects displayed by LEDs are different.
-   After a brief delay, the machine learning model recognizes the ``triangle`` wave, and the same effect (2 blinks) is displayed by both LEDs.
+   After a brief delay, the machine learning model recognizes the ``triangle`` wave, and the same effect (two blinks) is displayed by both LEDs.
 #. Press **Button 3** to again change the generated acceleration signal.
-   The ``square`` wave (3 blinks) is displayed only by the **LED2**.
+   The ``square`` wave (three blinks) is displayed only by the **LED2**.
    This signal is marked as an anomaly by the machine learning model, and **LED1** starts breathing.
 #. Press and hold **Button 1** for more than five seconds to switch to the data forwarding mode.
    After the mode is switched, **LED1** starts to blink rapidly.
@@ -545,6 +575,33 @@ After programming the application, perform the following steps to test the nRF M
 Optionally, you can also connect to the device using `Edge Impulse's data forwarder`_ and forward data to `Edge Impulse studio`_ (after logging in).
 See `Forwarding data to Edge Impulse studio`_ for details.
 
+Testing with the nRF54L15 DK
+---------------------------------------
+
+After programming the application, perform the following steps to test the nRF Machine Learning application on the DK:
+
+1. Turn on the development kit.
+   The application starts in a mode that runs the machine learning model.
+   Initially, **LED3** displays the LED effect representing ``sine`` wave (one blink), and **LED1** is breathing, because the signal was not yet recognized by the machine learning model.
+   After a brief delay, the machine learning model recognizes the simulated signal.
+   **LED1** and **LED3** display the same LED effect.
+#. Press **Button 2** to change the generated acceleration signal.
+   Right after the signal change, the effects displayed by LEDs are different.
+   After a brief delay, the machine learning model recognizes the ``triangle`` wave, and the same effect (two blinks) is displayed by both LEDs.
+#. Press **Button 2** to again change the generated acceleration signal.
+   The ``square`` wave (three blinks) is displayed only by the **LED3**.
+   This signal is marked as an anomaly by the machine learning model, and **LED1** starts breathing.
+#. Press and hold **Button 0** for more than five seconds to switch to the data forwarding mode.
+   After the mode is switched, **LED1** starts to blink rapidly.
+#. Connect to the development kit with a terminal emulator (for example, `nRF Connect Serial Terminal`_).
+   See :ref:`test_and_optimize` for the required settings.
+#. Observe the sensor readouts represented as comma-separated values.
+   Every line represents a single sensor readout.
+#. Turn off the terminal emulator to ensure that only one program has access to the data on UART.
+
+Optionally, you can also connect to the device using `Edge Impulse's data forwarder`_ and forward data to `Edge Impulse studio`_ (after logging in).
+See `Forwarding data to Edge Impulse studio`_ for details.
+
 Testing with the nRF54H20 DK
 -----------------------------
 

applications/machine_learning/configuration/nrf54l15dk_nrf54l15_cpuapp/app.overlay

@@ -0,0 +1,87 @@
+/ {
+	chosen {
+		ncs,ml-app-ei-data-forwarder-uart = &uart20;
+		zephyr,console = &uart30;
+
+	};
+
+	sensor_sim: sensor-sim {
+		compatible = "nordic,sensor-sim";
+		acc-signal = "wave";
+	};
+
+	/* Redefine pwmleds to fit CAF requirements. */
+	/delete-node/ pwmleds;
+
+	pwmleds1 {
+		compatible = "pwm-leds";
+		status = "okay";
+
+		pwm_led1: led_pwm_1 {
+			status = "okay";
+			pwms = <&pwm20 0 PWM_MSEC(20) PWM_POLARITY_NORMAL>;
+			label = "State LED";
+		};
+	};
+
+	pwmleds3 {
+		compatible = "pwm-leds";
+		status = "okay";
+
+		pwm_led3: led_pwm_3 {
+			status = "okay";
+			pwms = <&pwm21 0 PWM_MSEC(20) PWM_POLARITY_NORMAL>;
+			label = "Simulated signal LED";
+		};
+	};
+};
+
+&uart30 {
+	status = "okay";
+};
+
+&uart20 {
+	status = "okay";
+};
+
+&pwm20 {
+	status = "okay";
+	pinctrl-0 = <&pwm20_default_alt>;
+	pinctrl-1 = <&pwm20_sleep_alt>;
+	pinctrl-names = "default", "sleep";
+};
+
+&pwm21 {
+	status = "okay";
+	pinctrl-0 = <&pwm21_default_alt>;
+	pinctrl-1 = <&pwm21_sleep_alt>;
+	pinctrl-names = "default", "sleep";
+};
+
+&pinctrl {
+	pwm20_default_alt: pwm20_default_alt {
+		group1 {
+			psels = <NRF_PSEL(PWM_OUT0, 1, 10)>;
+		};
+	};
+
+	pwm20_sleep_alt: pwm20_sleep_alt {
+		group1 {
+			psels = <NRF_PSEL(PWM_OUT0, 1, 10)>;
+			low-power-enable;
+		};
+	};
+
+	pwm21_default_alt: pwm21_default_alt {
+		group1 {
+			psels = <NRF_PSEL(PWM_OUT0, 1, 14)>;
+		};
+	};
+
+	pwm21_sleep_alt: pwm21_sleep_alt {
+		group1 {
+			psels = <NRF_PSEL(PWM_OUT0, 1, 14)>;
+			low-power-enable;
+		};
+	};
+};

applications/machine_learning/configuration/nrf54l15dk_nrf54l15_cpuapp/buttons_def.h

@@ -0,0 +1,25 @@
+/*
+ * Copyright (c) 2024 Nordic Semiconductor ASA
+ *
+ * SPDX-License-Identifier: LicenseRef-Nordic-5-Clause
+ */
+
+#include <caf/gpio_pins.h>
+
+/* This configuration file is included only once from buttons module and holds
+ * information about pins forming keyboard matrix.
+ */
+
+/* This structure enforces the header file is included only once in the build.
+ * Violating this requirement triggers a multiple definition error at link time.
+ */
+const struct {} buttons_def_include_once;
+
+static const struct gpio_pin col[] = {};
+
+static const struct gpio_pin row[] = {
+	{ .port = 1, .pin = DT_GPIO_PIN(DT_NODELABEL(button0), gpios) },
+	{ .port = 1, .pin = DT_GPIO_PIN(DT_NODELABEL(button1), gpios) },
+	{ .port = 1, .pin = DT_GPIO_PIN(DT_NODELABEL(button2), gpios) },
+	{ .port = 0, .pin = DT_GPIO_PIN(DT_NODELABEL(button3), gpios) },
+};

applications/machine_learning/configuration/nrf54l15dk_nrf54l15_cpuapp/click_detector_def.h

@@ -0,0 +1,24 @@
+/*
+ * Copyright (c) 2024 Nordic Semiconductor ASA
+ *
+ * SPDX-License-Identifier: LicenseRef-Nordic-5-Clause
+ */
+
+#include <zephyr/kernel.h>
+#include <caf/click_detector.h>
+
+/* This configuration file is included only once from click_detector module
+ * and holds information about click detector configuration.
+ */
+
+/* This structure enforces the header file is included only once in the build.
+ * Violating this requirement triggers a multiple definition error at link time.
+ */
+const struct {} click_detector_def_include_once;
+
+static const struct click_detector_config click_detector_config[] = {
+	{
+		.key_id = CONFIG_ML_APP_MODE_CONTROL_BUTTON_ID,
+		.consume_button_event = true,
+	},
+};

applications/machine_learning/configuration/nrf54l15dk_nrf54l15_cpuapp/led_state_def.h

@@ -0,0 +1,62 @@
+/*
+ * Copyright (c) 2024 Nordic Semiconductor ASA
+ *
+ * SPDX-License-Identifier: LicenseRef-Nordic-5-Clause
+ */
+
+#include <caf/led_effect.h>
+#include "led_state.h"
+#include "ei_data_forwarder_event.h"
+
+/* This configuration file is included only once from led_state module and holds
+ * information about LED effects associated with data forwarder states and machine
+ * learning results.
+ */
+
+/* This structure enforces the header file is included only once in the build.
+ * Violating this requirement triggers a multiple definition error at link time.
+ */
+const struct {} led_state_def_include_once;
+
+
+/* Map function to LED ID */
+static const uint8_t led_map[] = {
+	[LED_ID_ML_STATE] = 0,
+	[LED_ID_SENSOR_SIM] = 1
+};
+
+static const struct led_effect ei_data_forwarder_led_effects[] = {
+	[EI_DATA_FORWARDER_STATE_DISCONNECTED]	=
+		LED_EFFECT_LED_BLINK(2000, LED_COLOR(100, 100, 100)),
+	[EI_DATA_FORWARDER_STATE_CONNECTED]	=
+		LED_EFFECT_LED_BLINK(500, LED_COLOR(100, 100, 100)),
+	[EI_DATA_FORWARDER_STATE_TRANSMITTING]	=
+		LED_EFFECT_LED_BLINK(50, LED_COLOR(100, 100, 100)),
+};
+
+static const struct ml_result_led_effect ml_result_led_effects[] = {
+	{
+		.label = NULL,
+		.effect = LED_EFFECT_LED_BREATH(500, LED_COLOR(100, 100, 100)),
+	},
+	{
+		.label = ANOMALY_LABEL,
+		.effect = LED_EFFECT_LED_BREATH(250, LED_COLOR(100, 100, 100)),
+	},
+	{
+		.label = "sine",
+		.effect = LED_EFFECT_LED_CLOCK(1, LED_COLOR(100, 100, 100)),
+	},
+	{
+		.label = "triangle",
+		.effect = LED_EFFECT_LED_CLOCK(2, LED_COLOR(100, 100, 100)),
+	},
+	{
+		.label = "square",
+		.effect = LED_EFFECT_LED_CLOCK(3, LED_COLOR(100, 100, 100)),
+	},
+	{
+		.label = "idle",
+		.effect = LED_EFFECT_LED_CLOCK(4, LED_COLOR(100, 100, 100)),
+	},
+};