Electrotechnical and Computer Engineering
Vol. 37 No. 02 (2022): Proceedings of the Faculty of Technical Sciences
COMPARATIVE ANALYSIS OF MACHINE LEARNING AT THE EDGE TECHNOLOGIES USING THE NVIDIA JETSON TX2
Abstract
This paper presents the theoretical foundations of machine learning at the edge and data flow processing, the meaning of the term Machine Learning Operations and a description of the Nvidia Jetson TX2 device. Then, machine learning technologies at the edge are analyzed and their comparative analyzes are given. Some of these technologies were applied to the demographic analytics solution using Nvidia Jetson TX2 device.
References
[1] Culjak, I., Abram, D., Pribanic, T., Dzapo, H., & Cifrek, M. (2012, May). A brief introduction to OpenCV. In 2012 proceedings of the 35th international convention MIPRO (pp. 1725-1730). IEEE.
[2] Getting started with OpenCV and Python, https://medium.com/the-andela-way/simple-operations-on-images-using-opencv-d37b26e6e3ab
[3] Thuan, D. (2021). Evolution of yolo algorithm and yolov5: the state-of-the-art object detection algorithm.
[4] Dobbelaere, P., & Esmaili, K. S. (2017, June). Kafka versus RabbitMQ: A comparative study of two industry reference publish/subscribe implementations: Industry Paper. In Proceedings of the 11th ACM international conference on distributed and event-based systems (pp. 227-238).
[5] Isah, H., Abughofa, T., Mahfuz, S., Ajerla, D., Zulkernine, F., & Khan, S. (2019). A survey of distributed data stream processing frameworks. IEEE Access, 7, 154300-154316.