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The integration of artificial intelligence, particularly machine learning, has significantly improved wearable devices' data processing capabilities. This advancement allows for the classification of fiber sensors into macroscopic and microscopic categories based on their dimensions and working principles. The study highlights various machine learning algorithms, including traditional and deep learning methods, that enhance the functionality of fiber sensors.
Despite the progress, current fiber sensors primarily focus on single signal types, such as mechanical force, limiting their potential. The article emphasizes the need for integrating diverse data types, like temperature and humidity, to enhance sensor capabilities. Future developments in machine learning algorithms, such as reinforcement learning and generative adversarial networks, are expected to make wearable devices more intelligent and user-friendly.
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