Abstract
Abstract
With the popularity of wearable devices, we can collect various data to support a series of innovative applications. The complex and massive data requires stronger data processing technologies. In recent years, artificial intelligence technology has been used to process this rich but complex data. In this paper, we summarize the research of AI technologies for wearable devices, from the aspects of types of wearable devices, collected data, models, and applications. We find that artificial intelligence technology has not only made a breakthrough in performance over traditional methods, but also creates a series of new applications. For the future research directions, we also point out some problems, e.g., the sensor data measurement and classification are not accurate enough, which would inspires the following research to investigate further.
Reference29 articles.
1. Deep learning[J];LeCun;nature,2015
2. Deep residual learning for image recognition[C];He,2016
3. Beyond short snippets: Deep networks for video classification[C];Yue-Hei,2015
4. Geospatial data to images: A deep-learning framework for traffic forecasting[J];Jiang;Tsinghua Science and Technology,2019
5. Deep learning algorithms for human activity recognition using mobile and wearable sensor networks: State of the art and research challenges[J];Nweke;Expert Systems with Applications,2018
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