With the growth of the wind turbine size, the aerodynamic performance of the rotor blades becomes more and more complex to evaluate, due to the large spectrum of encountered atmospheric wind conditions and the large deflections of the blade. The evaluation of the aerodynamic performance in real conditions is valuable for both wind turbine design and operational optimisation and can be achieved through aerodynamic measurements on the rotor blades. However, field measurements are scarce, due to the complexity and the cost of the installation. Recent developments in electronics allow the implementation of internet-connected, low-power and robust sensors at low cost, which enable new possibilities for field measurements on rotor blades. These sensors come, however, with lower sensitivity, precision, and frequency ranges, but can still provide useful aerodynamic insights, if the raw data is corrected using the fusion of different sensor types during the post-processing phase. In this work, we demonstrate a process for analysing time-resolved pressure data on operating rotor blades using low-cost pressure sensors. The process, comprising the data acquisition, the correction, and the post-processing of the measurement data, is presented using a real example from an instrumented operating 6 kW wind turbine. Absolute pressure sensors, differential pressure sensors and an inertial measurement unit are installed together as a flexible sensor node attached on a rotor blade (figure 1). The system is wireless and low power, making it thin and easy to install without damaging the blade. The position of the sensors on the blade is measured with a precision of less than one millimetre using photogrammetry. The data are automatically stored in a BigQuery space, capable of handling very large databases. The raw data is imported into a collaborative Jupyter notebook, and then corrected and processed to be able to analyse the aerodynamic performance for different wind conditions. We show that the accelerations and rotational speed recorded by the sensor node can be used to remove the influence of the hydrostatic pressure. We demonstrate that the centrifugal acceleration does not significantly disturb the pressure measurements and describe how we take into account the atmospheric pressure variations. The measurement system can be easily installed and used on multi-megawatt wind turbines, for example to help validate the design of prototypes as well as to assess the performance of wind turbines over the longer term for operators.