Using SingTown Technology's machine vision solution to deploy the "eyes and brain" of intelligent transportation at low cost.

在城市道路或交通模型系统中，传统的红绿灯控制方式通常采用固定时间策略，难以实时反映道路车流变化。

当某一方向车辆稀少而另一方向严重拥堵时，固定时长的信号灯控制不仅降低通行效率，也增加能源浪费。

To achieve dynamic optimisation and intelligent control of traffic signals, the intelligent transportation system incorporates SingTown's OpenMV intelligent camera AI image recognition technology. Through AI neural network algorithms and machine vision analysis, it detects the number of vehicles and flow distribution on roads in real time, and dynamically adjusts traffic light durations based on the results, thereby enabling adaptive intelligent regulation of traffic flow.

智能交通系统采用星瞳科技OpenMV智能摄像头识别技术，构建了基于AI图像识别与神经网络算法的车辆检测与信号控制系统。

The camera is installed on one side of the road, capturing real-time traffic flow images. The system detects and counts the number and direction of passing vehicles using computer vision algorithms. Based on the detected traffic density, it automatically determines the priority for each direction and transmits the data via a serial port to the microcontroller control unit, dynamically adjusting the duration of traffic lights.

This system solution supports multiple vehicle recognition modes: traditional image detection methods (such as frame difference, colour and shape recognition) or neural network models. The OpenMV smart camera possesses edge computing capabilities, enabling it to run algorithms locally via on-device AI and output results directly, without the need for an external computer or cloud server, resulting in low recognition latency and rapid response.

因此，该方案能稳定应对车流变化，实现“车多延长、车少缩短”的自适应红绿灯控制。

通过星瞳科技OpenMV智能摄像头AI图像识别技术，交通信号控制从固定时序迈向AI视觉动态调控，为智慧城市交通提供了低成本、高可靠、边缘部署的智能化动态管理方案。