AI Integration

In-depth review of AI/ML in mobile networks and security.

Future Network

Use edge computing nodes (such as NVIDIA Jetson AGX Orin) to deploy lightweight models (such as the compressed version of MobileNet-V3) to analyze vital sign data from bedside devices (such as ECG monitors and ventilators) in real time. For example, the Mayo Clinic's emergency triage system uses edge computing to delay the recognition of acute myocardial infarction in patients with chest pain by up to 0.3 seconds.

Research Gaps

Clinical data may be incomplete, noisy, inconsistently labeled, etc. For example, different hospitals have different electronic medical record systems with different record formats and standards, which makes data integration difficult, and manual data labeling is time-consuming and laborious, and may also contain subjective differences.

Traffic Scenarios

Based on 5G network slicing technology, dedicated communication channels are built for vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I), with a latency of less than 10ms, supporting real-time transmission of vehicle status (such as speed, brake signal) and road environment data (such as traffic light status, construction area). For example, a city deploys edge computing boxes (such as NVIDIA Jetson AGX Orin) on roadside units (RSUs) to analyze camera and lidar data in real time, warn of sudden road conditions 500 meters in advance, and shorten the braking distance of autonomous vehicles by 30%.