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IoT edge devices that use machine learning inference typically perform different types of processing, as shown in Figure 1.2.

Figure 1.2. Different types of processing in machine learning inference applications

These devices typically perform some pre-processing and feature extraction on the sensor input data before performing the actual neural network processing for the trained model. For example, a smart speaker with voice control capabilities may first pre-process the voice signal by performing acoustic echo cancellation and multimicrophone beam-forming. It may then apply FFTs to extract the spectral features for use in the neural network processing, which has been trained to recognize a vocabulary of voice commands.