Build an Aerospace Data Logger in C
Write embedded C firmware to capture atmospheric data during a weather balloon or drone flight.
Last reviewed: March 2026Overview
Almost every flight vehicle—from a $30,000 weather balloon to a $30 billion space station—carries data loggers. These devices continuously record sensor readings during flight so engineers can reconstruct exactly what happened, diagnose anomalies, and validate models against real measurements. In this project you will build a data logger from scratch using an Arduino microcontroller, a BME280 environmental sensor, and an SD card module—all components costing under $30 total.
You will write the firmware in C (the Arduino IDE uses a C/C++ dialect), learning the fundamentals of embedded programming: configuring hardware peripherals, reading sensor data over the I2C bus, managing a real-time sampling loop, and writing structured data to flash storage. These are exactly the skills that avionics engineers and flight software developers use, just scaled down to educational hardware.
Once you have flight data from a test—whether mounted to a weather balloon, drone, or simply carried up a tall stairwell—you will use Python to parse the CSV log, convert barometric pressure to altitude using the barometric formula, and plot the altitude profile over time. This complete hardware-to-analysis pipeline is a genuine engineering achievement that demonstrates real skills to college admissions and future employers alike.
What You'll Learn
- ✓ Write and flash C firmware to an Arduino that reads sensor data over I2C at a fixed sample rate.
- ✓ Implement structured data logging to an SD card in CSV format with timestamps.
- ✓ Explain the I2C communication protocol and how it connects microcontrollers to sensors.
- ✓ Use the barometric formula to convert pressure readings to altitude in Python.
- ✓ Plot and interpret a time-series altitude profile from real flight data.
Step-by-Step Guide
Gather hardware and install the Arduino IDE
You will need: Arduino Nano or Uno (~$5), BME280 sensor breakout board (~$8), micro SD card module (~$5), 32 GB microSD card, jumper wires, and a breadboard. Download the Arduino IDE from arduino.cc. In the Library Manager, install "Adafruit BME280", "Adafruit Unified Sensor", and "SD" libraries. Connect the BME280 to the Arduino's I2C pins (SDA to A4, SCL to A5 on an Uno) and the SD module to the SPI pins (MOSI/MISO/SCK/CS). Power both from the Arduino's 3.3V pin.
Write firmware to read and print sensor data
Create a new Arduino sketch. Include the BME280 library, initialize the sensor in setup() with bme.begin(0x76), and in loop() read temperature, pressure, and humidity: float temp = bme.readTemperature(), float pres = bme.readPressure()/100.0F, float hum = bme.readHumidity(). Print the readings to Serial as comma-separated values followed by a newline. Upload the sketch and open the Serial Monitor to verify you see live sensor readings updating every second. If you see all zeros, check your wiring connections.
Add SD card logging with timestamps
Include the SD library and initialize it in setup() with SD.begin(10) (pin 10 is CS). Create a log file: File dataFile = SD.open("flight.csv", FILE_WRITE). Write a header row: dataFile.println("time_ms,temp_C,pressure_hPa,humidity_pct"). In loop(), open the file in append mode, write one row per sample using millis() for the timestamp, and close the file after each write. Verify data is being saved by removing the SD card, inserting it into a computer, and opening the CSV in a spreadsheet.
Implement a precise 10 Hz sampling loop
Using delay(100) gives approximately 10 Hz but is imprecise because it does not account for sensor read time. Instead, record unsigned long lastSample = millis() at the start of each loop iteration and only take a new sample when millis() - lastSample >= 100. This non-blocking approach keeps sampling precise even if SD writes occasionally take extra time. Add a red LED that blinks once per sample so you have a visual indicator that logging is active during flight.
Conduct a test flight or vertical ascent
Mount the logger in a small enclosure (a plastic food container works) and tape it securely. Carry it to the top of a multi-story building stairwell, or mount it on a balloon or drone for a proper flight test. Let it log for at least 5 minutes. Retrieve the SD card and copy flight.csv to your computer. Open it in a spreadsheet and scan for any missing rows or obviously wrong values (sensor glitches show up as 0 or 9999 readings) that you will need to handle in your Python analysis.
Analyze the flight data in Python
Load the CSV with pandas: df = pd.read_csv("flight.csv"). Convert time_ms to seconds. Apply the barometric formula to compute altitude from pressure: altitude = 44330 * (1 - (pressure/1013.25)**0.1903) where pressure is in hPa. Plot altitude and temperature vs. time on the same axes with a dual y-axis. Mark the moment of peak altitude. Compare measured peak altitude to GPS-measured height if available. Calculate average ascent rate in m/s. Export the plot as a PNG and write a caption explaining what the data shows.
Career Connection
See how this project connects to real aerospace careers.
Avionics Technician →
Avionics technicians work with flight data recorders (black boxes) that operate on the same principles as this project—understanding how data is captured and stored is fundamental to the role.
Aerospace Engineer →
Flight test engineers design data acquisition systems, calibrate sensors, and analyze flight data for every new aircraft program; this project is a scaled-down version of that entire workflow.
Drone & UAV Ops →
Professional drone operators analyze telemetry logs after every flight to verify vehicle health and performance—building your own logger gives deep insight into what those logs contain.
Pilot →
Pilots who understand how aircraft instruments and data loggers work are better equipped to interpret abnormal readings and communicate with maintenance after flight incidents.
Go Further
- Add a GPS module (u-blox NEO-6M, ~$10) and log latitude, longitude, and GPS altitude alongside the barometric data, then plot the flight path on a map using the Folium Python library.
- Implement a simple data quality checker in the Arduino firmware that detects sensor dropouts and logs a "FLAG" column when readings are out of range.
- Add a radio transmitter (LoRa module) to stream live telemetry to a ground station laptop rather than relying solely on the SD card for recovery.
- Submit your flight data to a citizen science project such as GLOBE Observer or a local weather balloon research program.