基于机器视觉和GPS的校园车速监控系统

Vehicle speed monitoring system on campus based on machine vision and GPS

针对校园内高速行驶的车辆带来的安全隐患,以及现有的车速检测一般采用定点测试,不能对车速进行全程监测的问题,本文设计一种基于机器视觉和GPS的校园车速监控系统,包括便携式GPS速度监测警报系统和基于深度学习的车牌识别系统。速度监测警报系统利用GPS对车速全程监控,在超速时发出警报并记录超速里程与时间;车牌识别系统在校园出入口识别车牌号并存储超速车辆的车牌信息,以便对超速车辆进行管理。实验结果表明,该系统可以全程监测车速并记录车牌和超速信息。该系统能够解决校园内车速无法全程监控的问题,通过禁止有超速记录的车辆再次进入校园,减少校内车辆超速现象的发生,进而保证师生的安全。

In view of the safety risks brought by high-speed vehicles on campus,and the problem that the current speed detection generally adopts fixed-point test and the vehicle speed cannot be monitored in the whole driving process,a vehicle speed monitoring system on campus based on machine vision and GPS was designed,including a portable GPS speed monitoring and alarming system and a license plate recognition system based on deep learning.The speed monitoring and alarming system uses GPS to monitor the speed throughout the whole driving process,raises the alarm and records the speeding range and time when there was a speeding.The license plate recognition system recognizes and stores license plate information at the entrance and the exit of the campus in order to manage the vehicles which have speeding records.The experimental results show that the system can monitor vehicle speed in the whole driving process and record the vehicle license plate and over speed information.This system can solve the problem that the speed of vehicles on the campus cannot be monitored in the whole driving process.By banning the vehicles with speeding records from entering the campus again,the phenomenon of speeding on the campus can be reduced,so as to ensure the safety of teachers and students.