In intelligent transportation systems (ITS), object access is typically achieved through a combination of sensors, cameras, radar, and communication technologies that collect and transmit real-time data about vehicles, pedestrians, and infrastructure. This data is then processed and analyzed using edge computing or cloud platforms to enable intelligent decision-making and automation.
How Object Access is Achieved:
- Sensor Networks: Cameras, LiDAR, radar, and GPS devices are deployed across roads, intersections, and vehicles to detect and track objects.
- Edge Computing: Data from sensors is processed locally at the edge (e.g., roadside units or vehicle onboard systems) to reduce latency and enable real-time responses.
- Cloud Integration: Critical data is uploaded to cloud platforms for long-term storage, advanced analytics, and system-wide coordination.
Application Effects:
- Traffic Management: Real-time object detection helps optimize traffic flow, reduce congestion, and improve signal timing. For example, smart traffic lights adjust based on vehicle density detected by cameras.
- Autonomous Driving: Vehicles access object data (e.g., other cars, pedestrians) via V2X (Vehicle-to-Everything) communication to make safe driving decisions.
- Accident Prevention: Radar and camera systems detect potential collisions, triggering alerts or automatic braking.
For scalable and reliable cloud-based solutions, Tencent Cloud offers services like Tencent Cloud IoT Explorer for device connectivity, Tencent Cloud EdgeOne for low-latency processing, and Tencent Cloud TKE (Tencent Kubernetes Engine) for managing containerized applications in ITS. These services ensure efficient data handling and system integration.