Granted Patent B2

US 12,309,602 · App. 18/896,165 · Granted May 20, 2025

Inventor: Armando Montalvo (Winter Garden, FL)

Assignee: Digital Global Systems, Inc.

H04W16/10G06F30/27G06N3/02G06N5/022G06N5/04G06N20/00G06N20/10G06N20/20H04L41/0893H04W24/02H04W72/0453G06N3/042G06N3/045H04L41/0894H04W16/14H04W24/08

Abstract

Claims (33)

1. A system for dynamic, prioritized spectrum utilization management in an electromagnetic environment comprising:

at least one data analysis engine for analyzing measured data from the electromagnetic environment; and

at least one machine learning engine;

wherein the at least one data analysis engine is in communication with the at least one machine learning engine;

wherein the at least one data analysis engine is operable to identify open space in the electromagnetic environment based on the measured data and/or information from the at least one machine learning engine;

wherein the at least one machine learning engine is operable to use actionable data to provide results and/or solutions based on policies; and

wherein the at least one machine learning engine learns the electromagnetic environment and/or makes predictions about the electromagnetic environment.

2. The system of claim 1 , further comprising at least one monitoring sensor including at least one antenna for creating the measured data from the electromagnetic environment.

3. The system of claim 2 , wherein the at least one antenna includes a directional antenna.

4. The system of claim 2 , wherein the at least one monitoring sensor includes at least one antenna array.

5. The system of claim 1 , further comprising a survey occupancy application, wherein the survey occupancy application is operable to determine occupancy in frequency bands.

6. The system of claim 5 , wherein the survey occupancy application is operable to preprocess at least two signals that exist in one frequency band.

7. The system of claim 1 , wherein the at least one machine learning engine utilizes statistical learning techniques and/or control theory.

8. The system of claim 1 , wherein the system is operable to provide information on the open space.

9. The system of claim 8 , wherein the system is operable to provide the information on the open space in real time.

10. The system of claim 1 , wherein the actionable data is processed by the at least one machine learning engine to provide results and/or solutions for spectrum management based on policies.

11. The system of claim 1 , wherein the system is operable to survey the electromagnetic environment from 20 MHz to 6 GHz.

12. A system for dynamic, prioritized spectrum utilization management in an electromagnetic environment comprising:

at least one monitoring sensor operable to monitor the electromagnetic environment and create measured data based on the electromagnetic environment; and

at least one machine learning engine in communication with the at least one monitoring sensor;

wherein the at least one machine learning engine is operable to control the at least one monitoring sensor and/or use actionable data to provide results and/or solutions.

13. The system of claim 12 , wherein the at least one machine learning engine learns the electromagnetic environment and/or makes predictions about the electromagnetic environment based on measured data from the electromagnetic environment.

14. The system of claim 12 , wherein the system is operable to survey the electromagnetic environment from 20 MHz to 6 GHz.

15. The system of claim 12 , further comprising a survey occupancy application operable to determine occupancy in frequency bands.

16. The system of claim 15 , wherein the survey occupancy application is operable to preprocess at least two signals that exist in the same band.

17. A method for dynamic, prioritized spectrum utilization management in an electromagnetic environment comprising:

at least one monitoring sensor monitoring the electromagnetic environment and creating measured data based on the electromagnetic environment;

at least one data analysis engine analyzing the measured data to create analyzed data;

at least one machine learning engine learning the electromagnetic environment and/or making predictions about the electromagnetic environment based on the analyzed data;

providing at least one report and/or activating an alarm using actionable data based on the analyzed data.

18. The method of claim 17 , wherein the at least one report is further based on customer goals.

19. The method of claim 17 , further comprising surveying the electromagnetic environment in a frequency range between 20 MHz to 6 GHz.

20. The method of claim 17 , wherein the at least one machine learning engine utilizes statistical learning techniques and/or control theory to learn the electromagnetic environment and/or make predictions about the electromagnetic environment.

Assignments (1)

Continuity (11)

References Cited (400)