基于图像深度学习的物联网智能地锁系统研究与设计
Research and Design of IoT Intelligent Ground Lock System Based on Image Deep Learning
刘燕青1
作者信息
- 1. 桂林科技学院信息工程学院,广西桂林 541004
- 折叠
摘要
针对常规地锁开关不方便等问题,文章研究深度学习和物联网的应用,设计基于图像深度学习的物联网智能地锁系统,以此提升地锁系统的实用性.该系统由摄像头、网络通信、电磁锁控制等模块组成.通过地锁终端采集车牌图像数据,利用5G网络将图像数据传输给服务器.由服务器利用基于yolov4-tiny的车牌检测算法进行车牌检测,利用基于轻量级卷积神经网络(License Plate Recognition via Deep Neural Networks,LPRNet)的车牌识别算法进行车牌识别,并根据识别结果控制地锁开关.
Abstract
In response to the inconvenience of conventional locking switches and locks,this paper mainly studies the application of deep learning and the Internet of Things,and designs an intelligent IoT locking system based on image deep learning to improve the practicality of the locking system.The system consists of modules such as cameras,network communication,and electromagnetic lock control.Collect license plate image data through the ground lock terminal,and transmit the image data to the server using a 5G network.The server utilizes yolov4-tiny based license plate detection algorithm for license plate detection and LPRNet(License Plate Recognition via Deep Neural Networks)based license plate recognition algorithm for license plate recognition,and controls the ground lock switch based on the recognition results.
关键词
深度学习/地锁系统/5G网络/车牌识别Key words
deep learning/ground lock system/5G network/license plate recognition引用本文复制引用
出版年
2024
NETL
NSTL
万方数据