Integrating Sensor Data into a Raspberry Pi: A Hands‑On Guide

Abstract

Learn how to connect and read data from a GPS module and an MPU‑9150 IMU on a Raspberry Pi using I²C and UART interfaces, and process the information in real time for autonomous navigation.

Keywords: I2C communication, UART communication, Adafruit Ultimate GPS Breakout, Sparkfun MPU‑9150 Breakout, Raspberry Pi Setup

Introduction

Sensor data acquisition is the backbone of any digital control system. When an embedded controller processes these inputs, the choice of communication interface becomes critical. For a robotic navigation project, continuous GPS location updates and accurate course measurements are essential. This tutorial demonstrates how to wire a GPS module and a magnetometer to a Raspberry Pi, view the data remotely, and integrate it into control software.

Objective

This advanced tutorial assumes familiarity with Raspbian and basic bash commands. It guides you through reading accelerometer and GPS data via the Pi’s serial interfaces, wiring the sensors, and configuring the necessary hardware drivers.

Information

Hardware

• Sparkfun 9‑Degrees‑of‑Freedom Breakout (MPU‑9150)
• Adafruit Ultimate GPS Breakout

The MPU‑9150 is a multi‑chip module combining an MPU‑6050 (3‑axis gyroscope & accelerometer) and an AK8975 digital compass. It is widely used in smartphones and tablets for its low power and high performance.

The Adafruit Ultimate GPS is built around an MTK3339 chip, offering a 10 Hz update rate, 22‑satellite tracking, and an external antenna port. Its red LED indicates signal status: 1 Hz while searching and 15‑second blinks when a fix is achieved.

Communication Standards

I²C uses two bidirectional lines (SDA & SCL) to connect a master (the Pi) to multiple slaves, each with a unique address.

UART transmits data asynchronously in 5–8‑bit frames at a programmer‑defined baud rate, requiring separate TxD and RxD lines.

Parts List

• Raspberry Pi
• Power supply
• Wi‑Fi dongle
• Sparkfun MPU‑9150 breakout
• Adafruit Ultimate GPS breakout
• USB‑to‑TTL adapter (optional)
• Breadboard
• M‑to‑F jumper wires

Assumptions

• Internet access is available.
• Raspbian is installed and set to desktop mode.
• A mouse, keyboard, and HDMI monitor are connected.

Procedures

1. Identify the Pi’s GPIO pins: UART uses GPIO 14 (Tx) & 15 (Rx); I²C uses GPIO 2 (SDA) & 3 (SCL).
2. Wiring the GPS: Connect the GPS’s Tx to Pi’s Rx, Rx to Pi’s Tx, provide 3.3 V or 5 V to Vin, and tie GND to the Pi’s ground.
3. Wiring the MPU‑9150: Connect Vcc to 3.3 V, GND to ground, SDA to GPIO 2, and SCL to GPIO 3.
4. Enable I²C on the Pi:
   • Run sudo apt‑get update && sudo apt‑get install i2c‑tools libi2c‑dev.
   • Install WiringPi: git clone git://git.drogon.net/wiringPi && cd wiringPi && sudo nano /etc/modules and add snd-bcm2835, i2c-bcm2708, i2c-dev.
   • Edit /boot/config.txt to add dtparam=i2c1=on and dtparam=i2c_arm=on, then reboot.
5. Install the MPU‑6050 demo:
   • Clone git://github.com/richardghirst/PiBits.git, navigate to MPU6050-Pi-Demo, install libgtkmm-3.0-dev.
   • Edit I2Cdev.cpp and setup‑i2c.sh to replace /dev/i2c-0 with /dev/i2c-1.
   • Compile with make, run ./setup-i2c.sh, then verify with sudo i2cdetect -y 1.
   • Execute the demo with ./demo_raw to view raw gyro and accelerometer data.
6. Set up GPS data acquisition:
   • Adafruit’s GPS Daemon guide is a starting point, but for custom handling we use the open‑source libgps library.
   • Clone git://github.com/wdalmut/libgps.git, compile with make && sudo make install.
   • Test with the provided position_logger.c example: compile via gcc -o position_logger position_logger.c -lgps -lm and run ./position_logger. When a fix is obtained, latitude and longitude will print in decimal degrees.

Conclusion

This tutorial covered the hardware wiring, enabling communication protocols, and basic software setup for two common sensors on a Raspberry Pi. While the examples focus on data display, the same principles extend to integrating sensor outputs into sophisticated navigation or control algorithms. Mastery of each sensor’s library and a solid grasp of C/C++ development will enable more complex, real‑time sensor fusion.

References

• Kevin Townsend. Adafruit Ultimate GPS on the Raspberry Pi, 15 July 2014.
• Walter Dal Mut. UART NMEA GPS library for Raspberry Pi, 08 Sept 2014.
• InvenSense. MPU‑9150 Datasheet, 18 Sept 2013.