2.3 KiB
Decode GPS data - Virtual IoT Hardware and Raspberry Pi
In this part of the lesson, you will decode the NMEA messages read from the GPS sensor by the Raspberry Pi or Virtual IoT Device, and extract the latitude and longitude.
Decode GPS data
Once the raw NMEA data has been read from the serial port, it can be decoded using an open source NMEA library.
Task - decode GPS data
Program the device to decode the GPS data.
-
Open the
gps-sensor
app project if it's not already open -
Install the
pynmea2
Pip package. This package has code for decoding NMEA messages.pip3 install pynmea2
-
Add the following code to the imports in the
app.py
file to import thepynmea2
module:import pynmea2
-
Replace the contents of the
printGPSData
function with the following:msg = pynmea2.parse(line) if msg.sentence_type == 'GGA': lat = pynmea2.dm_to_sd(msg.lat) lon = pynmea2.dm_to_sd(msg.lon) if msg.lat_dir == 'S': lat = lat * -1 if msg.lon_dir == 'W': lon = lon * -1 print(f'{lat},{lon} - from {msg.num_sats} satellites')
This code will use the
pynmea2
library to parse the line read from the UART serial port.If the sentence type of the message is
GGA
, then this is a position fix message, and is processed. The latitude and longitude values are read from the message and converted to decimal degrees from the NMEA(d)ddmm.mmmm
format. Thedm_to_sd
function does this conversion.The direction of the latitude is then checked, and if the latitude is south, then the value is converted to a negative number. Same with the longitude, if it is west then it is converted to a negative number.
Finally the coordinates are printed to the console, along with the number of satellites used to get the location.
-
Run the code. If you are using a virtual IoT device, then make sure the CounterFit app is running and the GPS data is being sent.
pi@raspberrypi:~/gps-sensor $ python3 app.py 47.6423109,-122.1390293 - from 3 satellites
💁 You can find this code in the code-gps-decode/virtual-device folder, or the code-gps-decode/pi folder.
😀 Your GPS sensor program with data decoding was a success!