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Activity Recognition

In: Machine Learning for Data Science Handbook

Author

Listed:
  • Jindong Wang

    (Microsoft Research Asia)

  • Yiqiang Chen

    (Chinese Academy of Sciences, Institute of Computing Technology)

  • Chunyu Hu

    (Chinese Academy of Sciences, Institute of Computing Technology)

Abstract

This chapter presents an overview of human activity recognition (HAR). In ubiquitous computing, it is of extreme importance to sense and understand human’s behaviors and activities, which can then be used as information to other high-level activities. In this chapter, firstly we briefly introduce the basics of HAR and its applications in ubiquitous computing. Then, we introduce the main procedures of HAR, followed by more detailed components: data preprocessing and feature engineering, model building, and evaluations. Finally, we present some grand challenges in HAR that could be improved in the future. We hope through this chapter, readers will have a basic understanding of HAR and how to perform successful HAR.

Suggested Citation

  • Jindong Wang & Yiqiang Chen & Chunyu Hu, 2023. "Activity Recognition," Springer Books, in: Lior Rokach & Oded Maimon & Erez Shmueli (ed.), Machine Learning for Data Science Handbook, edition 0, pages 659-680, Springer.
    • Handle: RePEc:spr:sprchp:978-3-031-24628-9_29
    DOI: 10.1007/978-3-031-24628-9_29
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