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P

I am working on an object detection since 2 weeks. I have started the project by a testing object using edge impulse to create the library based on this object but when i compile the code i have an error
That's the code
#include <Parvesdomino-project-IPT_inferencing.h> #include "edge-impulse-sdk/dsp/image/image.hpp" #include "esp_camera.h" // Select camera model - find more camera models in camera_pins.h file here // https://github.com/espressif/arduino-esp32/blob/master/libraries/ESP32/examples/Camera/CameraWebServer/camera_pins.h //#define CAMERA_MODEL_ESP_EYE // Has PSRAM #define CAMERA_MODEL_AI_THINKER // Has PSRAM #if defined(CAMERA_MODEL_ESP_EYE) #define PWDN_GPIO_NUM -1 #define RESET_GPIO_NUM -1 #define XCLK_GPIO_NUM 4 #define SIOD_GPIO_NUM 18 #define SIOC_GPIO_NUM 23 #define Y9_GPIO_NUM 36 #define Y8_GPIO_NUM 37 #define Y7_GPIO_NUM 38 #define Y6_GPIO_NUM 39 #define Y5_GPIO_NUM 35 #define Y4_GPIO_NUM 14 #define Y3_GPIO_NUM 13 #define Y2_GPIO_NUM 34 #define VSYNC_GPIO_NUM 5 #define HREF_GPIO_NUM 27 #define PCLK_GPIO_NUM 25 #elif defined(CAMERA_MODEL_AI_THINKER) #define PWDN_GPIO_NUM 32 #define RESET_GPIO_NUM -1 #define XCLK_GPIO_NUM 0 #define SIOD_GPIO_NUM 26 #define SIOC_GPIO_NUM 27 #define Y9_GPIO_NUM 35 #define Y8_GPIO_NUM 34 #define Y7_GPIO_NUM 39 #define Y6_GPIO_NUM 36 #define Y5_GPIO_NUM 21 #define Y4_GPIO_NUM 19 #define Y3_GPIO_NUM 18 #define Y2_GPIO_NUM 5 #define VSYNC_GPIO_NUM 25 #define HREF_GPIO_NUM 23 #define PCLK_GPIO_NUM 22 #else #error "Camera model not selected" #endif /* Constant defines -------------------------------------------------------- */ #define EI_CAMERA_RAW_FRAME_BUFFER_COLS 320 #define EI_CAMERA_RAW_FRAME_BUFFER_ROWS 240 #define EI_CAMERA_FRAME_BYTE_SIZE 3 /* Private variables ------------------------------------------------------- */ static bool debug_nn = false; // Set this to true to see e.g. features generated from the raw signal static bool is_initialised = false; uint8_t *snapshot_buf; //points to the output of the capture static camera_config_t camera_config = { .pin_pwdn = PWDN_GPIO_NUM, .pin_reset = RESET_GPIO_NUM, .pin_xclk = XCLK_GPIO_NUM, .pin_sscb_sda = SIOD_GPIO_NUM, .pin_sscb_scl = SIOC_GPIO_NUM, .pin_d7 = Y9_GPIO_NUM, .pin_d6 = Y8_GPIO_NUM, .pin_d5 = Y7_GPIO_NUM, .pin_d4 = Y6_GPIO_NUM, .pin_d3 = Y5_GPIO_NUM, .pin_d2 = Y4_GPIO_NUM, .pin_d1 = Y3_GPIO_NUM, .pin_d0 = Y2_GPIO_NUM, .pin_vsync = VSYNC_GPIO_NUM, .pin_href = HREF_GPIO_NUM, .pin_pclk = PCLK_GPIO_NUM, //XCLK 20MHz or 10MHz for OV2640 double FPS (Experimental) .xclk_freq_hz = 20000000, .ledc_timer = LEDC_TIMER_0, .ledc_channel = LEDC_CHANNEL_0, .pixel_format = PIXFORMAT_JPEG, //YUV422,GRAYSCALE,RGB565,JPEG .frame_size = FRAMESIZE_QVGA, //QQVGA-UXGA Do not use sizes above QVGA when not JPEG .jpeg_quality = 12, //0-63 lower number means higher quality .fb_count = 1, //if more than one, i2s runs in continuous mode. Use only with JPEG .fb_location = CAMERA_FB_IN_PSRAM, .grab_mode = CAMERA_GRAB_WHEN_EMPTY, }; /* Function definitions ------------------------------------------------------- */ bool ei_camera_init(void); void ei_camera_deinit(void); bool ei_camera_capture(uint32_t img_width, uint32_t img_height, uint8_t *out_buf) ; /** * @brief Arduino setup function */ void setup() { // put your setup code here, to run once: Serial.begin(115200); //comment out the below line to start inference immediately after upload while (!Serial); Serial.println("Edge Impulse Inferencing Demo"); if (ei_camera_init() == false) { ei_printf("Failed to initialize Camera!\r\n"); } else { ei_printf("Camera initialized\r\n"); } ei_printf("\nStarting continious inference in 2 seconds...\n"); ei_sleep(2000); } /** * @brief Get data and run inferencing * * @param[in] debug Get debug info if true */ void loop() { // instead of wait_ms, we'll wait on the signal, this allows threads to cancel us... if (ei_sleep(5) != EI_IMPULSE_OK) { return; } snapshot_buf = (uint8_t*)malloc(EI_CAMERA_RAW_FRAME_BUFFER_COLS * EI_CAMERA_RAW_FRAME_BUFFER_ROWS * EI_CAMERA_FRAME_BYTE_SIZE); // check if allocation was successful if(snapshot_buf == nullptr) { ei_printf("ERR: Failed to allocate snapshot buffer!\n"); return; } ei::signal_t signal; signal.total_length = EI_CLASSIFIER_INPUT_WIDTH * EI_CLASSIFIER_INPUT_HEIGHT; signal.get_data = &ei_camera_get_data; if (ei_camera_capture((size_t)EI_CLASSIFIER_INPUT_WIDTH, (size_t)EI_CLASSIFIER_INPUT_HEIGHT, snapshot_buf) == false) { ei_printf("Failed to capture image\r\n"); free(snapshot_buf); return; } // Run the classifier ei_impulse_result_t result = { 0 }; EI_IMPULSE_ERROR 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 (DSP: %d ms., Classification: %d ms., Anomaly: %d ms.): \n", result.timing.dsp, result.timing.classification, result.timing.anomaly); #if EI_CLASSIFIER_OBJECT_DETECTION == 1 ei_printf("Object detection bounding boxes:\r\n"); for (uint32_t i = 0; i < result.bounding_boxes_count; i++) { ei_impulse_result_bounding_box_t bb = result.bounding_boxes[i]; if (bb.value == 0) { continue; } ei_printf(" %s (%f) [ x: %u, y: %u, width: %u, height: %u ]\r\n", bb.label, bb.value, bb.x, bb.y, bb.width, bb.height); } // Print the prediction results (classification) #else ei_printf("Predictions:\r\n"); for (uint16_t i = 0; i < EI_CLASSIFIER_LABEL_COUNT; i++) { ei_printf(" %s: ", ei_classifier_inferencing_categories[i]); ei_printf("%.5f\r\n", result.classification[i].value); } #endif // Print anomaly result (if it exists) #if EI_CLASSIFIER_HAS_ANOMALY ei_printf("Anomaly prediction: %.3f\r\n", result.anomaly); #endif #if EI_CLASSIFIER_HAS_VISUAL_ANOMALY ei_printf("Visual anomalies:\r\n"); for (uint32_t i = 0; i < result.visual_ad_count; i++) { ei_impulse_result_bounding_box_t bb = result.visual_ad_grid_cells[i]; if (bb.value == 0) { continue; } ei_printf(" %s (%f) [ x: %u, y: %u, width: %u, height: %u ]\r\n", bb.label, bb.value, bb.x, bb.y, bb.width, bb.height); } #endif free(snapshot_buf); } /** * @brief Setup image sensor & start streaming * * @retval false if initialisation failed */ bool ei_camera_init(void) { if (is_initialised) return true; #if defined(CAMERA_MODEL_ESP_EYE) pinMode(13, INPUT_PULLUP); pinMode(14, INPUT_PULLUP); #endif //initialize the camera esp_err_t err = esp_camera_init(&camera_config); if (err != ESP_OK) { Serial.printf("Camera init failed with error 0x%x\n", err); return false; } // sensor_t * s = esp_camera_sensor_get(); // initial sensors are flipped vertically and colors are a bit saturated //if (s->id.PID == OV3660_PID) { // s->set_vflip(s, 1); // flip it back // s->set_brightness(s, 1); // up the brightness just a bit // s->set_saturation(s, 0); // lower the saturation } #if defined(CAMERA_MODEL_M5STACK_WIDE) s->set_vflip(s, 1); s->set_hmirror(s, 1); #elif defined(CAMERA_MODEL_ESP_EYE) s->set_vflip(s, 1); s->set_hmirror(s, 1); s->set_awb_gain(s, 1); #endif is_initialised = true; return true; } /** * @brief Stop streaming of sensor data */ void ei_camera_deinit(void) { //deinitialize the camera esp_err_t err = esp_camera_deinit(); if (err != ESP_OK) { ei_printf("Camera deinit failed\n"); return; } is_initialised = false; return; } /** * @brief Capture, rescale and crop image * * @param[in] img_width width of output image * @param[in] img_height height of output image * @param[in] out_buf pointer to store output image, NULL may be used * if ei_camera_frame_buffer is to be used for capture and resize/cropping. * * @retval false if not initialised, image captured, rescaled or cropped failed * */ bool ei_camera_capture(uint32_t img_width, uint32_t img_height, uint8_t *out_buf) { bool do_resize = false; if (!is_initialised) { ei_printf("ERR: Camera is not initialized\r\n"); return false; } camera_fb_t *fb = esp_camera_fb_get(); if (!fb) { ei_printf("Camera capture failed\n"); return false; } bool converted = fmt2rgb888(fb->buf, fb->len, PIXFORMAT_JPEG, snapshot_buf); esp_camera_fb_return(fb); if(!converted){ ei_printf("Conversion failed\n"); return false; } if ((img_width != EI_CAMERA_RAW_FRAME_BUFFER_COLS) || (img_height != EI_CAMERA_RAW_FRAME_BUFFER_ROWS)) { do_resize = true; } if (do_resize) { ei::image::processing::crop_and_interpolate_rgb888( out_buf, EI_CAMERA_RAW_FRAME_BUFFER_COLS, EI_CAMERA_RAW_FRAME_BUFFER_ROWS, out_buf, img_width, img_height); } return true; } static int ei_camera_get_data(size_t offset, size_t length, float *out_ptr) { // we already have a RGB888 buffer, so recalculate offset into pixel index size_t pixel_ix = offset * 3; size_t pixels_left = length; size_t out_ptr_ix = 0; while (pixels_left != 0) { // Swap BGR to RGB here // due to https://github.com/espressif/esp32-camera/issues/379 out_ptr[out_ptr_ix] = (snapshot_buf[pixel_ix + 2] << 16) + (snapshot_buf[pixel_ix + 1] << 8) + snapshot_buf[pixel_ix]; // go to the next pixel out_ptr_ix++; pixel_ix+=3; pixels_left--; } // and done! return 0; } #if !defined(EI_CLASSIFIER_SENSOR) || EI_CLASSIFIER_SENSOR != EI_CLASSIFIER_SENSOR_CAMERA #error "Invalid model for current sensor" #endif
And here is the error:
C:\Users\HP\AppData\Local\Temp\.arduinoIDE-unsaved202486-9240-1p71wzh.ggfb\esp32_camera\esp32_camera.ino:382:2: error: #error "Invalid model for current sensor" 382 | #error "Invalid model for current sensor" | ^~~~~ exit status 1 Compilation error: #error "Invalid model for current sensor"
Please help me to solve this.

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P

I am working on an object detection since 2 weeks. I have started the project by a testing object using edge impulse to create the library based on this object but when i compile the code i have an error
That's the code:

'''
#include <Parvesdomino-project-IPT_inferencing.h>
#include "edge-impulse-sdk/dsp/image/image.hpp"

#include "esp_camera.h"

// Select camera model - find more camera models in camera_pins.h file here
// https://github.com/espressif/arduino-esp32/blob/master/libraries/ESP32/examples/Camera/CameraWebServer/camera_pins.h

//#define CAMERA_MODEL_ESP_EYE // Has PSRAM
#define CAMERA_MODEL_AI_THINKER // Has PSRAM

#if defined(CAMERA_MODEL_ESP_EYE)
#define PWDN_GPIO_NUM -1
#define RESET_GPIO_NUM -1
#define XCLK_GPIO_NUM 4
#define SIOD_GPIO_NUM 18
#define SIOC_GPIO_NUM 23

#define Y9_GPIO_NUM 36
#define Y8_GPIO_NUM 37
#define Y7_GPIO_NUM 38
#define Y6_GPIO_NUM 39
#define Y5_GPIO_NUM 35
#define Y4_GPIO_NUM 14
#define Y3_GPIO_NUM 13
#define Y2_GPIO_NUM 34
#define VSYNC_GPIO_NUM 5
#define HREF_GPIO_NUM 27
#define PCLK_GPIO_NUM 25

#elif defined(CAMERA_MODEL_AI_THINKER)
#define PWDN_GPIO_NUM 32
#define RESET_GPIO_NUM -1
#define XCLK_GPIO_NUM 0
#define SIOD_GPIO_NUM 26
#define SIOC_GPIO_NUM 27

#define Y9_GPIO_NUM 35
#define Y8_GPIO_NUM 34
#define Y7_GPIO_NUM 39
#define Y6_GPIO_NUM 36
#define Y5_GPIO_NUM 21
#define Y4_GPIO_NUM 19
#define Y3_GPIO_NUM 18
#define Y2_GPIO_NUM 5
#define VSYNC_GPIO_NUM 25
#define HREF_GPIO_NUM 23
#define PCLK_GPIO_NUM 22

#else
#error "Camera model not selected"
#endif

/* Constant defines -------------------------------------------------------- */
#define EI_CAMERA_RAW_FRAME_BUFFER_COLS 320
#define EI_CAMERA_RAW_FRAME_BUFFER_ROWS 240
#define EI_CAMERA_FRAME_BYTE_SIZE 3

/* Private variables ------------------------------------------------------- */
static bool debug_nn = false; // Set this to true to see e.g. features generated from the raw signal
static bool is_initialised = false;
uint8_t *snapshot_buf; //points to the output of the capture

static camera_config_t camera_config = {
.pin_pwdn = PWDN_GPIO_NUM,
.pin_reset = RESET_GPIO_NUM,
.pin_xclk = XCLK_GPIO_NUM,
.pin_sscb_sda = SIOD_GPIO_NUM,
.pin_sscb_scl = SIOC_GPIO_NUM,
.pin_d7 = Y9_GPIO_NUM, .pin_d6 = Y8_GPIO_NUM, .pin_d5 = Y7_GPIO_NUM, .pin_d4 = Y6_GPIO_NUM, .pin_d3 = Y5_GPIO_NUM, .pin_d2 = Y4_GPIO_NUM, .pin_d1 = Y3_GPIO_NUM, .pin_d0 = Y2_GPIO_NUM, .pin_vsync = VSYNC_GPIO_NUM, .pin_href = HREF_GPIO_NUM, .pin_pclk = PCLK_GPIO_NUM, //XCLK 20MHz or 10MHz for OV2640 double FPS (Experimental) .xclk_freq_hz = 20000000, .ledc_timer = LEDC_TIMER_0, .ledc_channel = LEDC_CHANNEL_0, .pixel_format = PIXFORMAT_JPEG, //YUV422,GRAYSCALE,RGB565,JPEG .frame_size = FRAMESIZE_QVGA, //QQVGA-UXGA Do not use sizes above QVGA when not JPEG .jpeg_quality = 12, //0-63 lower number means higher quality .fb_count = 1, //if more than one, i2s runs in continuous mode. Use only with JPEG .fb_location = CAMERA_FB_IN_PSRAM, .grab_mode = CAMERA_GRAB_WHEN_EMPTY,
};

/* Function definitions ------------------------------------------------------- */
bool ei_camera_init(void);
void ei_camera_deinit(void);
bool ei_camera_capture(uint32_t img_width, uint32_t img_height, uint8_t *out_buf) ;

/**

@brief Arduino setup function
*/
void setup()
{
// put your setup code here, to run once:
Serial.begin(115200);
//comment out the below line to start inference immediately after upload
while (!Serial);
Serial.println("Edge Impulse Inferencing Demo");
if (ei_camera_init() == false) {
ei_printf("Failed to initialize Camera!\r\n");
}
else {
ei_printf("Camera initialized\r\n");
}

ei_printf("\nStarting continious inference in 2 seconds...\n");
ei_sleep(2000);
}

/**

@brief Get data and run inferencing

@param[in] debug Get debug info if true
*/
void loop()
{

// instead of wait_ms, we'll wait on the signal, this allows threads to cancel us...
if (ei_sleep(5) != EI_IMPULSE_OK) {
return;
}

snapshot_buf = (uint8_t*)malloc(EI_CAMERA_RAW_FRAME_BUFFER_COLS * EI_CAMERA_RAW_FRAME_BUFFER_ROWS * EI_CAMERA_FRAME_BYTE_SIZE);

// check if allocation was successful
if(snapshot_buf == nullptr) {
ei_printf("ERR: Failed to allocate snapshot buffer!\n");
return;
}

ei::signal_t signal;
signal.total_length = EI_CLASSIFIER_INPUT_WIDTH * EI_CLASSIFIER_INPUT_HEIGHT;
signal.get_data = &ei_camera_get_data;

if (ei_camera_capture((size_t)EI_CLASSIFIER_INPUT_WIDTH, (size_t)EI_CLASSIFIER_INPUT_HEIGHT, snapshot_buf) == false) {
ei_printf("Failed to capture image\r\n");
free(snapshot_buf);
return;
}

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

EI_IMPULSE_ERROR 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 (DSP: %d ms., Classification: %d ms., Anomaly: %d ms.): \n",
result.timing.dsp, result.timing.classification, result.timing.anomaly);

#if EI_CLASSIFIER_OBJECT_DETECTION == 1
ei_printf("Object detection bounding boxes:\r\n");
for (uint32_t i = 0; i < result.bounding_boxes_count; i++) {
ei_impulse_result_bounding_box_t bb = result.bounding_boxes[i];
if (bb.value == 0) {
continue;
}
ei_printf(" %s (%f) [ x: %u, y: %u, width: %u, height: %u ]\r\n",
bb.label,
bb.value,
bb.x,
bb.y,
bb.width,
bb.height);
}
// Print the prediction results (classification)
#else
ei_printf("Predictions:\r\n");
for (uint16_t i = 0; i < EI_CLASSIFIER_LABEL_COUNT; i++) {
ei_printf(" %s: ", ei_classifier_inferencing_categories[i]);
ei_printf("%.5f\r\n", result.classification[i].value);
}
#endif
// Print anomaly result (if it exists)
#if EI_CLASSIFIER_HAS_ANOMALY
ei_printf("Anomaly prediction: %.3f\r\n", result.anomaly);
#endif

#if EI_CLASSIFIER_HAS_VISUAL_ANOMALY
ei_printf("Visual anomalies:\r\n");
for (uint32_t i = 0; i < result.visual_ad_count; i++) {
ei_impulse_result_bounding_box_t bb = result.visual_ad_grid_cells[i];
if (bb.value == 0) {
continue;
}
ei_printf(" %s (%f) [ x: %u, y: %u, width: %u, height: %u ]\r\n",
bb.label,
bb.value,
bb.x,
bb.y,
bb.width,
bb.height);
}
#endif
free(snapshot_buf);
}

/**

@brief Setup image sensor & start streaming

@retval false if initialisation failed
*/
bool ei_camera_init(void) {

if (is_initialised) return true;

#if defined(CAMERA_MODEL_ESP_EYE)
pinMode(13, INPUT_PULLUP);
pinMode(14, INPUT_PULLUP);
#endif
//initialize the camera esp_err_t err = esp_camera_init(&camera_config); if (err != ESP_OK) { Serial.printf("Camera init failed with error 0x%x\n", err); return false; }
// sensor_t * s = esp_camera_sensor_get();
// initial sensors are flipped vertically and colors are a bit saturated
//if (s->id.PID == OV3660_PID) {
// s->set_vflip(s, 1); // flip it back
// s->set_brightness(s, 1); // up the brightness just a bit
// s->set_saturation(s, 0); // lower the saturation
}

#if defined(CAMERA_MODEL_M5STACK_WIDE)
s->set_vflip(s, 1);
s->set_hmirror(s, 1);
#elif defined(CAMERA_MODEL_ESP_EYE)
s->set_vflip(s, 1);
s->set_hmirror(s, 1);
s->set_awb_gain(s, 1);
#endif
is_initialised = true; return true;
}

/**

@brief Stop streaming of sensor data
*/
void ei_camera_deinit(void) {

//deinitialize the camera
esp_err_t err = esp_camera_deinit();

if (err != ESP_OK)
{
ei_printf("Camera deinit failed\n");
return;
}

is_initialised = false;
return;
}

/**
@brief Capture, rescale and crop image @param[in] img_width width of output image @param[in] img_height height of output image @param[in] out_buf pointer to store output image, NULL may be used if ei_camera_frame_buffer is to be used for capture and resize/cropping. @retval false if not initialised, image captured, rescaled or cropped failed
*/
bool ei_camera_capture(uint32_t img_width, uint32_t img_height, uint8_t *out_buf) {
bool do_resize = false;
if (!is_initialised) { ei_printf("ERR: Camera is not initialized\r\n"); return false; } camera_fb_t *fb = esp_camera_fb_get(); if (!fb) { ei_printf("Camera capture failed\n"); return false; }
bool converted = fmt2rgb888(fb->buf, fb->len, PIXFORMAT_JPEG, snapshot_buf);

esp_camera_fb_return(fb);

if(!converted){
ei_printf("Conversion failed\n");
return false;
}
if ((img_width != EI_CAMERA_RAW_FRAME_BUFFER_COLS) || (img_height != EI_CAMERA_RAW_FRAME_BUFFER_ROWS)) { do_resize = true; } if (do_resize) { ei::image::processing::crop_and_interpolate_rgb888( out_buf, EI_CAMERA_RAW_FRAME_BUFFER_COLS, EI_CAMERA_RAW_FRAME_BUFFER_ROWS, out_buf, img_width, img_height); } return true;
}

static int ei_camera_get_data(size_t offset, size_t length, float *out_ptr)
{
// we already have a RGB888 buffer, so recalculate offset into pixel index
size_t pixel_ix = offset * 3;
size_t pixels_left = length;
size_t out_ptr_ix = 0;
while (pixels_left != 0) { // Swap BGR to RGB here // due to https://github.com/espressif/esp32-camera/issues/379 out_ptr[out_ptr_ix] = (snapshot_buf[pixel_ix + 2] << 16) + (snapshot_buf[pixel_ix + 1] << 8) + snapshot_buf[pixel_ix]; // go to the next pixel out_ptr_ix++; pixel_ix+=3; pixels_left--; } // and done! return 0;
}

#if !defined(EI_CLASSIFIER_SENSOR) || EI_CLASSIFIER_SENSOR != EI_CLASSIFIER_SENSOR_CAMERA
#error "Invalid model for current sensor"
#endif
'''

and here is the error
'''
C:\Users\HP\AppData\Local\Temp.arduinoIDE-unsaved202486-9240-1p71wzh.ggfb\esp32_camera\esp32_camera.ino:382:2: error: #error "Invalid model for current sensor"
382 | #error "Invalid model for current sensor"
| ^~~~~
exit status 1

Compilation error: #error "Invalid model for current sensor"
'''

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I'm trying to create an IoT network based on LoRa Wan and ESP32. I have tried using an RA02 module to for transmission of data but the range I'm getting is around 250m. The required range for my project is around 5KM with no line of sight. What is the best way to go about it? Which will be the best LoRa module that I use for this project?

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Hi @Vishnuraj2003 ,

As per the documentation, I think we only route the data over the LoRa oR BT. The Wifi is used for sniffing access points for better geo-location and positioning along with GPS.

And what is the issue you facing when connecting the tracker with gateway? Double check the FREQ on both node and gateway configuration

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