Tracking Your World: GPS with MicroPython on Raspberry Pi Pico

The Raspberry Pi Pico, combined with MicroPython's simplicity, offers a potent platform for DIY GPS tracking projects. By understanding the basics of GPS modules and leveraging MicroPython's capabilities, you can build a functional GPS tracking system.

Essential Components

• Raspberry Pi Pico: The microcontroller for running the project.

• GPS Module: A GPS module like the NEO-6M to acquire location data.

• MicroPython Firmware: The programming language for the Pico.

• Power Source: To supply power to both the Pico and the GPS module.

To create a GPS tracking system using MicroPython on a Raspberry Pi Pico, you will need to interface the Pico with a GPS module (like the NEO-6M) and possibly an OLED display for visual output. Here’s a comprehensive guide based on the search results.

Components Required

1. Raspberry Pi Pico

2. NEO-6M GPS Module

3. OLED Display (optional, e.g., SSD1306)

4. Jumper Wires

5. Breadboard (optional)

Step-by-Step Guide

1. Wiring the Components

Connect the NEO-6M GPS module and OLED display to the Raspberry Pi Pico as follows:

• NEO-6M GPS Module:

• VCC to 3.3V on Pico

• GND to GND on Pico

• TX to GPIO 5 (RX on Pico)

• RX to GPIO 4 (TX on Pico)

• OLED Display (SSD1306):

• VCC to 3.3V on Pico

• GND to GND on Pico

• SDA to GPIO 14

• SCL to GPIO 15

2. Install MicroPython

Make sure you have MicroPython installed on your Raspberry Pi Pico. You can download it from the MicroPython website.

3. Set Up the Development Environment

Use an IDE like Thonny to write and upload your code to the Pico. Ensure that you have the necessary libraries for handling GPS data and OLED display. You may need to upload the micropyGPS.py library for parsing GPS data.

4. Writing the MicroPython Code

Here’s a sample code snippet that initializes the GPS module, reads GPS data, and displays it on the OLED screen:

from machine import Pin, UART, I2C

import utime

from ssd1306 import SSD1306_I2C

from micropyGPS import MicropyGPS

# Initialize I2C and OLED display

i2c = I2C(1, sda=Pin(14), scl=Pin(15), freq=400000)

oled = SSD1306_I2C(128, 64, i2c)

# Initialize GPS module

gps_module = UART(1, baudrate=9600, tx=Pin(4), rx=Pin(5))

gps = MicropyGPS()

while True:

    if gps_module.any():

        data = gps_module.read()

        for char in data:

            gps.update(char)

        # Display GPS coordinates

        if gps.latitude and gps.longitude:

            oled.fill(0)  # Clear the display

            oled.text('Lat: {:.6f}'.format(gps.latitude), 0, 0)

            oled.text('Lon: {:.6f}'.format(gps.longitude), 0, 10)

            oled.show()

    utime.sleep(1)

5. Testing the System

1. Upload the code to your Raspberry Pi Pico using Thonny.

2. Ensure the GPS antenna is exposed to the sky for better signal acquisition.

3. Run the code, and you should see the latitude and longitude displayed on the OLED screen.

6. Sending Data to Google Maps

To visualize the GPS data on Google Maps, you can send the coordinates to a web service or use a service like PubNub or a custom server that logs the GPS data and displays it on a map. This involves setting up an HTTP request to send the latitude and longitude to your server.

Additional Resources

• For a complete project with detailed wiring and code, you can refer to the GitHub repository mentioned in the search results .

• A tutorial that covers the NEO-6M GPS module with Raspberry Pi Pico can be found here .

By following these steps, you can successfully set up a GPS tracking system using the Raspberry Pi Pico and MicroPython, enabling you to track locations and potentially visualize them on Google Maps.