Arduino crashing when declaring global variables for BLE

Hi

Using Arduino Nano Sense 33 BLE

I am doing a motion detection machine learning project.I am trying to output my models prediction via bluetooth. My model code works perfectly until I begin to add the bluetooth global variables need at the top… these are

BLEService skateService(“180F”);
BLEUnsignedCharCharacteristic skateTrickChar(“2A19”,BLERead | BLENotify);

When i declare these in setup the code runs without crashing but the bluetooth can no longer work as these global variables are needed later on.

why does adding these global variables make my code crash?!

/*
  IMU Classifier
  This example uses the on-board IMU to start reading acceleration and gyroscope
  data from on-board IMU, once enough samples are read, it then uses a
  TensorFlow Lite (Micro) model to try to classify the movement as a known gesture.
  Note: The direct use of C/C++ pointers, namespaces, and dynamic memory is generally
        discouraged in Arduino examples, and in the future the TensorFlowLite library
        might change to make the sketch simpler.
  The circuit:
  - Arduino Nano 33 BLE or Arduino Nano 33 BLE Sense board.
  Created by Don Coleman, Sandeep Mistry
  Modified by Dominic Pajak, Sandeep Mistry
  This example code is in the public domain.
*/

#include <ArduinoBLE.h>

BLEService skateService("180F");
BLEUnsignedCharCharacteristic skateTrickChar("2A19",BLERead | BLENotify);

#include <Arduino_LSM9DS1.h>

#include <TensorFlowLite.h>
#include <tensorflow/lite/micro/all_ops_resolver.h>
#include <tensorflow/lite/micro/micro_error_reporter.h>
#include <tensorflow/lite/micro/micro_interpreter.h>
#include <tensorflow/lite/schema/schema_generated.h>
#include <tensorflow/lite/version.h>

#include "model3.h"

const float accelerationThreshold = 4.5; // threshold of significant in G's
const int numSamples = 119;

int samplesRead = numSamples;
int prevPred = 0;
int trick = 0;
float predictedValue = 0;
int oldBatteryLevel = 0;  // last battery level reading from analog input
long previousMillis = 0;  // last time the battery level was checked, in ms

// global variables used for TensorFlow Lite (Micro)
tflite::MicroErrorReporter tflErrorReporter;

// pull in all the TFLM ops, you can remove this line and
// only pull in the TFLM ops you need, if would like to reduce
// the compiled size of the sketch.
tflite::AllOpsResolver tflOpsResolver;

const tflite::Model* tflModel = nullptr;
tflite::MicroInterpreter* tflInterpreter = nullptr;
TfLiteTensor* tflInputTensor = nullptr;
TfLiteTensor* tflOutputTensor = nullptr;

// Create a static memory buffer for TFLM, the size may need to
// be adjusted based on the model you are using
constexpr int tensorArenaSize = 8 * 1024;
byte tensorArena[tensorArenaSize];

// array to map gesture index to a name
const char* GESTURES[] = {
  "heelflip",
  "kickflip",
  "other"
};

#define NUM_GESTURES (sizeof(GESTURES) / sizeof(GESTURES[0]))



//// BLE Battery Level Characteristic
//BLEUnsignedCharCharacteristic skateTrickChar("2A19",  // standard 16-bit characteristic UUID
//    BLERead | BLENotify); // remote clients will be able to get notifications if this characteristic changes

void setup() {
  Serial.begin(9600);
  while (!Serial);

  if (!BLE.begin()) {
    Serial.println("starting BLE failed!");

    while (1);
  }
  
  BLE.setLocalName("Trick Detector");
  BLE.setAdvertisedService(skateService); // add the service UUID
  skateService.addCharacteristic(skateTrickChar); // add the battery level characteristic
  BLE.addService(skateService); // Add the battery service
  skateTrickChar.writeValue(oldBatteryLevel); // set initial value for this characteristic

  // initialize the IMU
  if (!IMU.begin()) {
    Serial.println("Failed to initialize IMU!");
    while (1);
  }

  // print out the samples rates of the IMUs
  Serial.print("Accelerometer sample rate = ");
  Serial.print(IMU.accelerationSampleRate());
  Serial.println(" Hz");
  Serial.print("Gyroscope sample rate = ");
  Serial.print(IMU.gyroscopeSampleRate());
  Serial.println(" Hz");

  Serial.println();

  // get the TFL representation of the model byte array
  tflModel = tflite::GetModel(model);
  if (tflModel->version() != TFLITE_SCHEMA_VERSION) {
    Serial.println("Model schema mismatch!");
    while (1);
  }

  // Create an interpreter to run the model
  tflInterpreter = new tflite::MicroInterpreter(tflModel, tflOpsResolver, tensorArena, tensorArenaSize, &tflErrorReporter);

  // Allocate memory for the model's input and output tensors
  tflInterpreter->AllocateTensors();

  // Get pointers for the model's input and output tensors
  tflInputTensor = tflInterpreter->input(0);
  tflOutputTensor = tflInterpreter->output(0);

  BLE.advertise();

  Serial.println("Bluetooth device active, waiting for connections...");
}

void loop() {
  float aX, aY, aZ, gX, gY, gZ;

  // wait for significant motion
  while (samplesRead == numSamples) {
    if (IMU.accelerationAvailable()) {
      // read the acceleration data
      IMU.readAcceleration(aX, aY, aZ);

      // sum up the absolutes
      float aSum = fabs(aX) + fabs(aY) + fabs(aZ);

      // check if it's above the threshold
      if (aSum >= accelerationThreshold) {
        // reset the sample read count
        samplesRead = 0;
        break;
      }
    }
  }

  // check if the all the required samples have been read since
  // the last time the significant motion was detected
  while (samplesRead < numSamples) {
    // check if new acceleration AND gyroscope data is available
    if (IMU.accelerationAvailable() && IMU.gyroscopeAvailable()) {
      // read the acceleration and gyroscope data
      IMU.readAcceleration(aX, aY, aZ);
      IMU.readGyroscope(gX, gY, gZ);

      // normalize the IMU data between 0 to 1 and store in the model's
      // input tensor
      tflInputTensor->data.f[samplesRead * 6 + 0] = (aX + 4.0) / 8.0;
      tflInputTensor->data.f[samplesRead * 6 + 1] = (aY + 4.0) / 8.0;
      tflInputTensor->data.f[samplesRead * 6 + 2] = (aZ + 4.0) / 8.0;
      tflInputTensor->data.f[samplesRead * 6 + 3] = (gX + 2000.0) / 4000.0;
      tflInputTensor->data.f[samplesRead * 6 + 4] = (gY + 2000.0) / 4000.0;
      tflInputTensor->data.f[samplesRead * 6 + 5] = (gZ + 2000.0) / 4000.0;

      samplesRead++;

      if (samplesRead == numSamples) {
        // Run inferencing
        TfLiteStatus invokeStatus = tflInterpreter->Invoke();
        if (invokeStatus != kTfLiteOk) {
          Serial.println("Invoke failed!");
          while (1);
          return;
        }

        // Loop through the output tensor values from the model
        for (int i = 0; i < NUM_GESTURES; i++) {
           
           predictedValue = tflOutputTensor->data.f[i];


          if ( prevPred < predictedValue) {
            prevPred = predictedValue;
            trick = i;
          }



          
          Serial.print(GESTURES[i]);
          Serial.print(": ");
          Serial.println(tflOutputTensor->data.f[i], 6);
        }
        Serial.println();
        bluetooth();
      }
    }
  }
}
void bluetooth() {
  // wait for a BLE central
  BLEDevice central = BLE.central();

  // if a central is connected to the peripheral:
  if (central) {
    Serial.print("Connected to central: ");
    // print the central's BT address:
    Serial.println(central.address());
    // turn on the LED to indicate the connection:
    digitalWrite(LED_BUILTIN, HIGH);

    // check the battery level every 200ms
    // while the central is connected:
    while (central.connected()) {
      long currentMillis = millis();
      // if 200ms have passed, check the battery level:
      if (currentMillis - previousMillis >= 200) {
        previousMillis = currentMillis;
        updateBatteryLevel();
      }
    }
    // when the central disconnects, turn off the LED:
    digitalWrite(LED_BUILTIN, LOW);
    Serial.print("Disconnected from central: ");
    Serial.println(central.address());
  }
}

void updateBatteryLevel() {
  /* Read the current voltage level on the A0 analog input pin.
     This is used here to simulate the charge level of a battery.
  */
  int battery = analogRead(A0);
  int batteryLevel = map(battery, 0, 1023, 0, 100);

  if (batteryLevel != oldBatteryLevel) {      // if the battery level has changed
    
    Serial.print("Battery Level % is now: "); // print it
    Serial.println(batteryLevel);
    skateTrickChar.writeValue(batteryLevel);  // and update the battery level characteristic
    oldBatteryLevel = batteryLevel;           // save the level for next comparison
  }
}

Describe the actual problem and post error messages. “Crash” doesn’t convey any useful information.