The Mechanics team integrates Artificial Intelligence (AI) object detection with fifth-generation (5G) mobile communication technology to enable real-time acquisition and analysis of traffic flow through high-performance video recognition systems. This approach facilitates intelligent traffic management, enhancing road efficiency, alleviating congestion, reducing commute times, and reinforcing system safety and stability. In addition, the solution incorporates Internet of Things (IoT) architecture and high-speed communication capabilities to support real-time monitoring and data sharing across transportation infrastructure and vehicle flow. The overall framework not only improves user mobility and operational efficiency but also establishes a foundational pillar for sustainable, intelligent urban transportation—demonstrating strong potential for scalable deployment in smart city development.
Integrating IoT technology and intelligent image management, this multi-functional smart traffic management system supports real-time equipment monitoring, anomaly alerts, and resource optimization. It ensures stable operation of traffic infrastructure and enhances service quality, helping agencies effectively monitor traffic status and respond promptly to improve management efficiency and safety.
By introducing AI-based image recognition and automated data processing, a standardized head-turning model is established to reduce subjective judgment deviation. The system uses simulation signals and serial port sensors to detect violations such as lane crossing or failure to use turn signals in real-time, automatically deducts points, and records the exam process for review. Applicants can check their waiting status and estimated time via LINE@ or a dedicated app to reduce onsite waiting. After the test, results are displayed immediately on a digital screen to streamline the process and improve convenience.
Utilizing deep learning and high-precision image processing technology, the system can accurately recognize license plates in real-time under various lighting and dynamic traffic conditions. It integrates vehicle tracking, supports camera management by intersection and device ID, enables low-cost rapid deployment with existing checkpoints, and enhances traffic management and road safety through centralized monitoring and real-time data display.
Utilizing AI image recognition and camera equipment, this system intelligently monitors traffic volume and vehicle turning at intersections, helping authorities grasp real-time traffic conditions and congestion trends. The collected traffic data serves as an important basis for traffic signal timing adjustments, dynamic control strategies, and signal plan optimization, enhancing intersection efficiency and traffic management intelligence.
Utilizing AI image recognition and camera equipment to intelligently track temporary vehicle parking behavior, determining violations of specific road usage regulations. Applicable scenarios include non-bus occupancy at bus stops, overstaying in pick-up/drop-off zones, and occupying no-parking zones. The system automatically issues alert messages and sends them to the management platform, assisting enforcement agencies to monitor violations in real-time, issue warnings, and respond flexibly, effectively improving traffic order and road safety.
Incorporating AI-powered intelligent image recognition technology to detect potential risks in intersections or accident hotspots in real-time, such as red-light running vehicles, pedestrians crossing illegally, and vehicles failing to yield. The system proactively triggers alerts and warnings, effectively reducing accident rates and enhancing road user safety.
