How to operate the buzzer in the desired behavior after machine learning

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#1

#include <kimyoungmoon-project-1_inference.h>
#include <Arduino_LSM9DS1.h>

#define CONVERT_G_TO_MS2 9.80665f

static bool debug_nn = false; // Set this to true to see e.g. features generated from the raw signal

void setup()
{
// put your setup code here, to run once:
Serial.begin(115200);
Serial.println(“Edge Impulse Inferencing Demo”);

if (!IMU.begin()) {
    ei_printf("Failed to initialize IMU!\r\n");
}
else {
    ei_printf("IMU initialized\r\n");
}

if (EI_CLASSIFIER_RAW_SAMPLES_PER_FRAME != 3) {
    ei_printf("ERR: EI_CLASSIFIER_RAW_SAMPLES_PER_FRAME should be equal to 3 (the 3 sensor axes)\n");
    return;
}

}

void ei_printf(const char *format, …) {
static char print_buf[1024] = { 0 };

va_list args;
va_start(args, format);
int r = vsnprintf(print_buf, sizeof(print_buf), format, args);
va_end(args);

if (r > 0) {
Serial.write(print_buf);
}
}

void loop()
{
ei_printf("\nStarting inferencing in 2 seconds…\n");

delay(2000);

ei_printf("Sampling...\n");

// Allocate a buffer here for the values we'll read from the IMU
float buffer[EI_CLASSIFIER_DSP_INPUT_FRAME_SIZE] = { 0 };

for (size_t ix = 0; ix < EI_CLASSIFIER_DSP_INPUT_FRAME_SIZE; ix += 3) {
    // Determine the next tick (and then sleep later)
    uint64_t next_tick = micros() + (EI_CLASSIFIER_INTERVAL_MS * 1000);

    IMU.readAcceleration(buffer[ix], buffer[ix + 1], buffer[ix + 2]);

    buffer[ix + 0] *= CONVERT_G_TO_MS2;
    buffer[ix + 1] *= CONVERT_G_TO_MS2;
    buffer[ix + 2] *= CONVERT_G_TO_MS2;

    delayMicroseconds(next_tick - micros());
}

// Turn the raw buffer in a signal which we can the classify
signal_t signal;
int err = numpy::signal_from_buffer(buffer, EI_CLASSIFIER_DSP_INPUT_FRAME_SIZE, &signal);
if (err != 0) {
    ei_printf("Failed to create signal from buffer (%d)\n", err);
    return;
}

// Run the classifier
ei_impulse_result_t result = { 0 };

err = run_classifier(&signal, &result, debug_nn);
if (err != EI_IMPULSE_OK) {
    ei_printf("ERR: Failed to run classifier (%d)\n", err);
    return;
}

// print the predictions
ei_printf("Predictions ");
ei_printf("(DSP: %d ms., Classification: %d ms., Anomaly: %d ms.)",
    result.timing.dsp, result.timing.classification, result.timing.anomaly);
ei_printf(": \n");
for (size_t ix = 0; ix < EI_CLASSIFIER_LABEL_COUNT; ix++) {
    ei_printf("    %s: %.5f\n", result.classification[ix].label, result.classification[ix].value);
}

#if EI_CLASSIFIER_HAS_ANOMALY == 1
ei_printf(" anomaly score: %.3f\n", result.anomaly);
#endif
}

#if !defined(EI_CLASSIFIER_SENSOR) || EI_CLASSIFIER_SENSOR != EI_CLASSIFIER_SENSOR_ACCELEROMETER
#error “Invalid model for current sensor”
#endif

I want to know how to operate the buzzer in the desired motion after machine learning.

#2

Hi @KIMYOUNGMOON,

Can you provide more details about your project? Which buzzer are you referring to?

Aurelien

#3

If you detect the vibration of the 3D printer and detect a defect, the buzzer may sound.

The buzzer I use is Passive Buzzer.

#4

You can write your buzzer code after printing the predictions. The result.classification array contains the predicted values, you could add an if statement based on a threshold to activate the buzzer for instance.

Aurelien

1 Like
#5

Oh, thank you.
Could you write an example if you have time?
I don’t quite understand.

#6

You can do something like this when “yourlabel” is detected with a prediction confidence more than 70%:

for (size_t ix = 0; ix < EI_CLASSIFIER_LABEL_COUNT; ix++) {
    ei_printf("    %s: %.5f\n", result.classification[ix].label, result.classification[ix].value);
    if (result.classification[ix].label == "yourlabel" && result.classification[ix].value > 0.7) {
        // Add buzzer code here
    }
}
#7

Hello!

I do not have a passive buzzer but I guess you could right something similar to this code (change the #define buzzerPin according to your GPIO pinout):

#define buzzerPin 7
#define anomaly_threshold 0.5

void setup() {

  pinMode(buzzerPin,OUTPUT);

}

And then add something similar to this in your code:


 err = run_classifier(&signal, &result, debug_nn);
 if (err != EI_IMPULSE_OK) {
    ei_printf("ERR: Failed to run classifier (%d)\n", err);
    return;
 }
 if(result.anomaly > anomaly_threshold){
    ei_printf(" anomaly score: %.3f\n", result.anomaly);
    digitalWrite(buzzerPin, HIGH);
 }

Regards,

1 Like
#8

Oh, thank you. :slight_smile:
What does yourlable mean?

#9

yourlabel in @aurel suggestion means “your label” (it can up, down, idle_state or whatever your decided to call your labels in the studio) :wink:

Regards

#10

I don’t know well, can you show me one example?

#11

Hello @KIMYOUNGMOON,

Unfortunately, I do not have the hardware to test and to provide you the exact piece of code that will work for you.

Regards,

Louis

#12

Can you give me an example from the code I wrote?

#13

You have to solve :slight_smile: Thank you.

#14

Hi @KIMYOUNGMOON,

This is more an Arduino related question. Which buzzer and library are you using? I would suggest to look at the Arduino forum if you need help on programming using their IDE.

Aurelien

1 Like