Example Concept: Data filtering in IoT involves using algorithms like low-pass, high-pass, or Kalman filters to process raw sensor data. These filters help in smoothing out noise and extracting meaningful signals by allowing only the desired frequency components to pass through. For instance, a low-pass filter can remove high-frequency noise from temperature sensor readings, ensuring that only the relevant temperature changes are captured.