Issue |
ITM Web Conf.
Volume 57, 2023
Fifth International Conference on Advances in Electrical and Computer Technologies 2023 (ICAECT 2023)
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Article Number | 02001 | |
Number of page(s) | 8 | |
Section | Electronics Circuits & Systems | |
DOI | https://doi.org/10.1051/itmconf/20235702001 | |
Published online | 10 November 2023 |
Human Activity Recognition by Edge Computing Based Convolutional Neural Network
Department of ECE, PES University, Bangalore
* usha.jange1998@gmail.com
** rajeshwari@pes.edu
Human activity recognition has become a hotly debated research topic due to its numerous important and futuristic applications, such as automated surveillance, automated vehicles, language interpretation, and human-computer interfaces. (HCI). Extensive and in-depth research has been conducted, and good progress is been achieved in this area of research. The proposed system is designed by taking health monitoring as an application and implemented on a Raspberry Pi board, which can be used for monitoring and surveillance purposes. The activities considered in our proposed work are standing, jogging, climbing upstairs, and climbing downstairs. The surveillance camera will watch people’s movements to see if they are performing the assigned job. We propose a CNN-based technique to recognize different actions. An alert will sound and the system will report that the person’s designated task has been disrupted if the camera determines that they are engaged in another activity.
Key words: Video Surveillance / Raspberry Pi / Raspberry Pi Camera / Open CV
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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