It allows a large number of devices to connect simultaneously   

It supports a fixed number of IoT connections per cell tower   

It enables dedicated virtual networks for specific functionality   

It provides guaranteed low latency for real-time decision making   

Real-time decision making and control with minimal delay

High data throughput and low power consumption

Robust security and privacy for data transmission

Seamless connectivity and large-scale IoT device support

Storing data generated by IoT devices    

Receiving alerts to the core cloud for analysis    

Running machine learning models for anomaly detection    

Training machine learning models using e.g., TensorFlow    

Conducting real-time simulations

Synchronizing multi-sensor data

Pre-processing sensor data at the edge

Finding hidden patterns in the data

Guaranteeing ultra-reliable low latency communications for safety and efficiency

Ensuring low-power consumption for distributed edge-cloud computing

Balancing data flow between edge and cloud for robotics control

Achieving ultra-high data rates for real-time collaboration

Developing and training machine learning models   

Providing data cleaning for models trained on the edge

Ingest data from edge to the data lake   

Running real-time anomaly detection on edge data