Intelligent Traffic Monitoring System Based On Internet Of Things

With the development of technologies such as the Internet and cloud computing,the Internet of Things has been used in more and more fields,and many aspects of smart cities have also used the Internet of Things technology.The intelligent traffic monitoring system proposed in this paper is based on the application of the Internet of Things.It mainly includes three subsystems: vehicle speed detection system,vehicle behavioral semantic analysis system and vehicle license plate recognition system.The thesis verified the three subsystems from the perspective of theory and experiment,and achieved good results.In the vehicle speed detection system,the paper improved a virtual coil vehicle speed detection algorithm.First a virtual coil is added at a fixed location in the camera scene and the actual distance between the two virtual coils is known.When it is detected that the vehicle passes the virtual coil,the license plate is located and recognized,so that the time required for the vehicle to pass a fixed distance is obtained,and the vehicle speed is obtained by dividing the distance by the time.The algorithm can not only realize vehicle speed detection in a wide range of areas,but also realize the detection of the speed of multiple vehicles at the same time.It can also obtain the vehicle license plate number while detecting the vehicle speed,which facilitates the follow-up control management and vehicle tracking.In the vehicle behavioral semantic analysis system,the paper designs a vehicle behavioral semantic analysis algorithm based on the relationship between the vehicle trajectory and the lane line.Through video detection and tracking the vehicle's moving target,the vehicle's trajectory is obtained,and the vehicle's motion characteristics in each frame of image are extracted,including vehicle position,vehicle speed,and vehicle driving direction.Combining the relationship between the lane line equation and the vehicle's trajectory,a semantic representation of vehicle behavior is derived.In the license plate recognition system,the paper introduces a license plate location algorithm that integrates the maximum stable extreme region and license plate features.First,the maximum stable extreme value region method is used to roughly locate the license plate characters,and then the license plate features are combined with the license plate character features to perform license plate recognition.Accurate positioning,you can get accurate license plate area;then use license plate character segmentation,license plate recognition,identify the license plate number.In addition to locating the common blue license plate,the algorithm can also successfully locate the yellow license plate and the license plate with blue background,and can also locate the license plate with multiple cars in one image.The intelligent traffic monitoring system proposed in this paper processes the video data and image data acquired based on the Internet of Things to implement functions such as vehicle speed detection,vehicle behavior semantic analysis,license plate recognition,etc.,and can capture ilegal vehicles and then identify violations.The license plates of vehicles are conducive to promoting the management and control of intelligent traffic and reducing the occurrence of traffic accidents.