Cellular system

1. A system, comprising:

one or more sensors coupled to equipment to monitor equipment operation;

one or more 5G antennas;

one or more 5G transceivers coupled to the one or more 5G antennas;

a processor to control the one or more 5G transceivers in communication with the one or more sensors; and

a neural network or an artificial intelligence (AI) processor coupled to the processor;

a control plane coupled to the neural network;

a management plane coupled to the neural network; and

a data plane coupled to the neural network, wherein the neural network receives cellular network statistics for training, and during run-time, the neural network provides operating parameters to the data, control and management planes.

2. The system of claim 1 , comprising a remote processor to perform predictive maintenance based on sensor output indicating a potential breakdown.

3. The system of claim 1 , comprising a remote processor to track equipment performance over time to predict a potential maintenance issue before they occur.

4. The system of claim 1 , wherein the transceiver connects sensors, machines or robots.

5. The system of claim 1 , wherein one or more sensors are at the edge to communicate with equipment.

6. The system of claim 1 , comprising maintaining equipment based on statistics for wear rates or sensed equipment operation over time.

7. The system of claim 1 , comprising an Internet of Things (IoT) device wirelessly coupled to the processor.

8. The system of claim 1 , comprising a remote processor to compare real-time data from sensors on connected equipment to an equipment history.

9. The system of claim 1 , comprising a remote processor and AI predictive analytics to request predictive maintenance.

10. The system of claim 1 , comprising one or more cameras and sensors to capture security information.

11. The system of claim 1 , comprising a camera for identity identification.

12. The system of claim 1 , wherein the processor analyzes walking gaits and facial features for identity identification.

13. The system of claim 1 , wherein the processor analyzes sound captured using a microphone to determine events in progress.

14. The system of claim 1 , comprising an edge processor to provide local edge processing for Internet-of-Things (IOT) sensors.

15. The system of claim 1 , comprising an edge learning machine that uses pre-trained models and modifies the pre-trained models for a selected task.

16. The system of claim 1 , comprising a cellular device for a person crossing a street near a city light or street light, the cellular device emitting a person to vehicle (P2V) or a vehicle to person (V2P) safety message.

17. The system of claim 1 , comprising a cloud trained neural network whose network parameters are down-sampled or count reduced before transferring to an edge neural network.

18. The system of claim 1 , comprising a display to overlay one or more digital elements onto the real world.

19. The system of claim 18 , comprising code to determine cellular transceiver location determination based on nearby device locations.

20. The system of claim 1 , comprising a flexible antenna surface.