Analisis Penggunaan Sumber Daya Pada Jetson Nano Untuk Sistem Pengenalan Wajah
DOI:
https://doi.org/10.21460/jutei.2024.82.374Keywords:
Jetson Nano, pengenalan wajah, analisis sumber dayaAbstract
Jetson Nano, a Single-Board Computer or SBC developed by NVIDIA, is used to implement a face recognition system that requires large computing resources. This research aims to analyze the resource usage on the Jetson Nano during the running of the face recognition system, including CPU usage, GPU, memory, and power consumption. Monitoring data was obtained using Jtop software to record real-time resource usage and a wattmeter for electrical power consumption. The results showed that the Jetson Nano CPU performed consistently with an average utilization of 77.14%, reflecting an even distribution of workload. The GPU showed an average utilization of 44.05% with higher fluctuations, indicating variations in graphics workload intensity. Memory was used close to the maximum capacity of 4 GB, with an average utilization of 3.75 GB, indicating efficient memory management. Average power consumption was recorded at 8.56 Wh, confirming the energy efficiency of this device. This study concludes that the Jetson Nano is capable of running the facial recognition system stably and efficiently, although there is room for further optimization on GPU load distribution and memory management. With its high power efficiency, the Jetson Nano is an ideal solution for artificial intelligence-based applications with low power requirements.
References
M. Wang dan W. Deng, “Deep Face Recognition: A Survey,” Apr 2018, doi: 10.1016/j.neucom.2020.10.081.
Y. Taigman, M. Yang, M. Ranzato, dan L. Wolf, “DeepFace: Closing the gap to human-level performance in face verification,” dalam Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, IEEE Computer Society, Sep 2014, hlm. 1701–1708. doi: 10.1109/CVPR.2014.220.
NVIDIA Developer, Jetson Nano Developer Kit. Nvidia Corporation, 2019. Diakses: 19 Maret 2024. [Daring]. Tersedia pada: https://developer.nvidia.com/embedded/jetson-nano-developer-kit
V. Chandra Sekhar, D. Penchalaiah, G. Naresh Kumar, dan A. Bhattacharyya, “Real Time Face Recognition System using Jetson Nano,” dalam 5th ISSE National Conference (INAC-05) on Systems Approach for Self-Reliance in Advanced Technologies, BS Publications, Mar 2023. doi: 10.37285/bsp.sasat2023.29.
E. Yose, Victor, dan N. Surantha, “Portable smart attendance system on Jetson Nano,” Bulletin of Electrical Engineering and Informatics, vol. 13, no. 2, hlm. 1050–1059, Apr 2024, doi: 10.11591/eei.v13i2.6061.
V. Sati, S. M. Sánchez, N. Shoeibi, A. Arora, dan J. M. Corchado, “Face Detection and Recognition, Face Emotion Recognition Through NVIDIA Jetson Nano,” 2021, hlm. 177–185. doi: 10.1007/978-3-030-58356-9_18.
NVIDIA Developer, “NVIDIA Jetson Nano.” Diakses: 19 Mei 2024. [Daring]. Tersedia pada: https://www.nvidia.com/en-us/autonomous-machines/embedded-systems/jetson-nano/product-development/
NVIDIA Developer, “CUDA Zone - Library of Resources.” Diakses: 6 Juni 2024. [Daring]. Tersedia pada: https://developer.nvidia.com/cuda-zone
R. Bonghi, “Jetson Stats.” Diakses: 26 Juli 2024. [Daring]. Tersedia pada: https://developer.nvidia.com/embedded/community/jetson-projects/jetson_stats
D. E. King, “Dlib Human Face Detector.” Diakses: 24 Juli 2024. [Daring]. Tersedia pada: https://github.com/davisking/dlib-models#mmod_human_face_detectordatbz2
D. E. King, “Dlib Face Recognition ResNet Model.” Diakses: 24 Juli 2024. [Daring]. Tersedia pada: https://github.com/davisking/dlib-models#dlib_face_recognition_resnet_model_v1datbz2
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Dion Dwi Wijaya, Hugeng, Hadian Satria Utama
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Authors who publish articles in JUTEI agree on the following rules:
1. The author grants non exclusive royalty free rights, and is willing to publish articles online and complete (full access). With such rights JUTEI reserves the right to save, transfers, manages in various forms, maintains and publishes articles while keeping the author's name as the copyright owner.
2. Each author contained in the article has contributed fully to the substance and intellectual, and is accountable to the public. If in the future there is a copyright infringement notification then this will be responsibility of the author, not JUTEI.
