Machine Learning and AI Technologies for Smart Wearables

Kah Phooi Seng*, Li Minn Ang, Eno Peter, Anthony Mmonyi

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

19 Citations (Scopus)


The recent progress in computational, communications, and artificial intelligence (AI) technologies, and the widespread availability of smartphones together with the growing trends in multimedia data and edge computation devices have led to new models and paradigms for wearable devices. This paper presents a comprehensive survey and classification of smart wearables and research prototypes using machine learning and AI technologies. The paper aims to survey these new paradigms for machine learning and AI for wearables from various technological perspectives which have emerged, including: (1) smart wearables empowered by machine learning and AI; (2) data collection architectures and information processing models for AI smart wearables; and (3) applications for AI smart wearables. The review covers a wide range of enabling technologies for AI and machine learning for wearables and research prototypes. The main findings of the review are that there are significant technical challenges for AI smart wearables in networking and communication aspects such as issues for routing and communication overheads, information processing and computational aspects such as issues for computational complexity and storage, and algorithmic and application-dependent aspects such as training and inference. The paper concludes with some future directions in the smart wearable market and potential research.

Original languageEnglish
Article number1509
JournalElectronics (Switzerland)
Issue number7
Publication statusPublished - Apr 2023


  • artificial intelligence (AI)
  • deep learning
  • smart wearables
  • wearable devices


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