Development of Artificial Intelligence in Activity Recognition

Shuohan Tao

doi:10.54097/hset.v7i.1079

Authors

Shuohan Tao

DOI:

https://doi.org/10.54097/hset.v7i.1079

Keywords:

Artificial Intelligence, Activity Recognition, sensor, Wi-Fi, visual

Abstract

This essay focuses on how the technology of activity recognition has developed with the development of artificial intelligence. It illustrates three major solutions in activity recognition, including sensor-based solution, visual solutions, and Wi-Fi-based solutions, and discuss the pros and cons of each of the solutions.

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References

Activity recognition. (2022). In Wikipedia. Wikimedia Foundation. https: //en.wikipedia.org/wiki/ Activity_recognition.

Fuller, S. H., & Millett, L. I. (2011). Chapter 10. In the Future of Computing Performance: Game Over or Next Level? National Academies Press.

Hao Wang. (2016). Human respiration detection with commodity wifi devices: do user location and body orientation matter? UbiComp’16: Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing, 25–36.

Kinect. (2022). In Wikipedia. Wikimedia Foundation. https://en.wikipedia.org/wiki/Kinect.

Maxwell, D. R. (1983). Graphical Marionette: A Modern-day Pinocchio [Phdthesis].

Rotoscoping. (2022). In Wikipedia. Wikimedia Foundation. https://en.wikipedia.org/wiki/Rotoscoping

Roy Want. (1992). The active badge location system. ACM Transactions on Information Systems, 10(1), 91–102.

Tong, C., Tailor, S. A., & Lane, N. D. (2020). Are Accelerometers for Activity Recognition a Dead-end? CoRR, abs/2001.08111. https://arxiv.org/abs/2001.08111.