Development of Artificial Intelligence in Activity Recognition
DOI:
https://doi.org/10.54097/hset.v7i.1079Keywords:
Artificial Intelligence, Activity Recognition, sensor, Wi-Fi, visualAbstract
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.
Downloads
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.
Downloads
Published
Conference Proceedings Volume
Section
License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.