Equipping Traffic Signals with "Eyes": SingTown Technology's AI Vision Assistance

In urban traffic management, accurately identifying pedestrians within crosswalks and promptly triggering safety warnings is a crucial requirement for intelligent transportation systems.

Traditional radar or infrared detection struggles to accurately distinguish pedestrians from vehicles in complex environments, resulting in high false alarm rates and insufficient reliability.

To this end, traffic intelligent equipment manufacturers adopt SingTown's OpenMV intelligent camera recognition technology, utilising AI machine vision algorithms and regional detection models to achieve dynamic monitoring of designated areas (such as crosswalks) and pedestrian detection warnings.

Traffic intelligent equipment manufacturers utilise SingTown's OpenMV intelligent camera recognition technology to achieve real-time pedestrian detection at crosswalks and signal linkage warnings.

The intelligent vision module is installed at road intersections, delineating a rectangular monitoring area and detecting only moving targets within this region.

Upon detection of a moving pedestrian target, the camera promptly issues a high-level signal through GPIO. This signal can be connected to signal lights, buzzers, or traffic management systems to provide alarm notifications.

The system utilises the edge deployment advantages of embedded vision and on-device AI, enabling real-time pedestrian recognition through background modelling, target motion detection, and morphological recognition algorithms. It performs image analysis and signal output locally without requiring additional servers, with a recognition latency of less than 200 milliseconds.

The system can adapt to various lighting conditions and weather environments, featuring strong robustness and low power consumption characteristics.

Through SingTown Technology's OpenMV intelligent camera recognition technology, traffic intelligent equipment manufacturers have achieved an intelligent upgrade from traditional induction detection to AI visual pedestrian recognition and warning, providing efficient and real-time visual solutions for urban traffic safety.