四川轻化工大学学报（自然科学版）2025，Vol.38Issue(1)：69-76,8.DOI:10.11863/j.suse.2025.01.08
基于Jetson Nano的头盔佩戴检测系统设计
Design of a Helmet Wear Detection System Based on Jetson Nano
摘要
Abstract
Currently,many algorithms used to detect helmet wearing conditions cannot meet the real-time detection requirements on low computational power embedded devices,thereby limiting the widespread application of helmet wear detection technology.To address this challenge,a TensorRT optimization and deployment method for the Jetson Nano development board has been proposed.Firstly,algorithm performance and accelerate inference speed are improved by using the techniques such as Int8 quantization,inter-layer fusion,and tensor fusion.Then,the loss of algorithm performance is minimized by using TensorRT's automated calibration process,addressing the problem of information loss caused by the use of Int8.The experiments show that after deploying the helmet wear detection algorithm model into the Jetson Nano embedded device,the mAP@0.5 of the algorithm achieves to 98.63%,and the total inference time reduces from 320.52 ms to 64.11 ms,which is decreased by 80%.This improvement effectively solves the problem of insufficient real-time deployment inference of the algorithm on low computational power embedded devices,giving a new method for the widespread application of helmet wearing detection technology.关键词
嵌入式开发/TensorRT/Int8量化/层间融合/张量融合Key words
embedded development/TensorRT/Int8 quantization/inter-layer fusion/tensor fusion分类
信息技术与安全科学引用本文复制引用
彭梓洋,周顺勇,陆欢,张鑫,张航领,罗扬铭..基于Jetson Nano的头盔佩戴检测系统设计[J].四川轻化工大学学报（自然科学版）,2025,38(1):69-76,8.基金项目
国家自然科学基金项目(61801319) （61801319）
四川省科技厅省院校合作项目(2020YFSY0027) （2020YFSY0027）
四川省大学生创新创业项目(S202210622033) （S202210622033）
