Granted Patent B2

US 11,700,533 · App. 18/085,874 · Granted Jul 11, 2023

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 (53)

1. A system for autonomous spectrum management in an electromagnetic environment comprising:

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

at least one data analysis engine for analyzing the measured data;

a semantic engine including a programmable rules and policy editor; and

a tip and cue server;

wherein the at least one data analysis engine includes a detection engine and a learning engine, wherein the detection engine is operable to automatically detect at least one signal of interest, wherein the learning engine is operable to learn the electromagnetic environment;

wherein the programmable rules and policy editor includes at least one rule and/or at least one policy;

wherein the tip and cue server is operable to use analyzed data from the at least one data analysis engine to create actionable data; and

wherein the tip and cue server and the at least one data analysis engine are operable to run autonomously without requiring user interaction and/or input.

2. The system of claim 1 , wherein the tip and cue server is operable to activate an alarm and/or provide at least one report based on the actionable data.

3. The system of claim 2 , wherein the alarm is stored in a database for visualization.

4. The system of claim 1 , wherein the at least one monitoring sensor includes at least one antenna, at least one antenna array, at least one radio server, and/or at least one software defined radio.

5. The system of claim 1 , wherein one or more of the at least one monitoring sensor is integrated with at least one camera to capture video and/or still images.

6. The system of claim 1 , wherein the at least one data analysis engine further includes an identification engine, a classification engine, and/or a geolocation engine.

7. The system of claim 1 , further including a resource brokerage application, wherein the resource brokerage application is operable to optimize resources to improve performance of at least one customer application and/or at least one customer device.

8. The system of claim 1 , further including a certification and compliance application, wherein the certification and compliance application is operable to determine if at least one customer application and/or at least one customer device is behaving according to the at least one rule and/or the at least one policy.

9. The system of claim 1 , further including a survey occupancy application, wherein the survey occupancy application is operable to determine occupancy in frequency bands and schedule occupancy in at least one frequency band.

10. The system of claim 1 , wherein the actionable data indicates that the at least one signal of interest is behaving like a drone.

11. The system of claim 1 , wherein the semantic engine is operable to receive queries, searches, and/or search-related functions using natural language.

12. The system of claim 1 , wherein the semantic engine is operable to receive data as audio data, text data, video data, and/or image data.

13. The system of claim 1 , wherein the semantic engine is operable to create a semantic map including target data, wherein the semantic engine is operable to analyze related data and/or data with similar characteristics to the target data.

14. The system of claim 1 , further including a translator, wherein the translator is operable to receive data input including at least one use case, at least one objective, and/or at least one signal.

15. The system of claim 1 , wherein the learning engine is operable to use machine learning (ML), artificial intelligence (AI), deep learning (DL), neural networks (NNs), artificial neural networks (ANNs), support vector machines (SVMs), Markov decision process (MDP), natural language processing (NLP), control theory, and/or statistical learning techniques.

16. The system of claim 1 , wherein the learning engine is operable to compute a set of possible conditional probabilities depicting a set of all possible outputs based on input measurements to provide a predicted outcome using a data model.

17. The system of claim 1 , wherein the learning engine is operable to use third party data, wherein the third party data includes social media, population, real estate, traffic, geographic information system (GIS), network, signal site, site issue, and/or crowdsourced information.

18. The system of claim 1 , wherein the learning engine is operable to determine whether a data set processed and/or analyzed represents a sufficient statistical data set.

19. The system of claim 1 , wherein the learning engine includes a learning engine software development kit (SDK) operable to manage system resources relating to monitoring, logging, and/or organizing learning aspects of the system.

20. The system of claim 1 , wherein the semantic engine further includes a language dictionary.

21. The system of claim 1 , wherein the actionable data indicates that one or more of the at least one signal of interest is behaving like a drone.

22. The system of claim 1 , wherein the actionable data indicates a location for at least one macrosite and/or at least one tower.

23. The system of claim 1 , wherein the actionable data is created in near-real time.

24. A system for autonomous spectrum management in a radio frequency (RF) environment comprising:

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

at least one data analysis engine for analyzing the measured data;

a semantic engine including a programmable rules and policy editor; and

a tip and cue server;

wherein the at least one data analysis engine includes a detection engine, a geolocation engine, and a learning engine, wherein the detection engine is operable to automatically detect at least one signal of interest, wherein the learning engine is operable to learn the RF environment;

wherein the programmable rules and policy editor includes at least one rule and/or at least one policy;

wherein the semantic engine is operable to create a semantic map including target data;

wherein the tip and cue server is operable to use analyzed data from the at least one data analysis engine to create actionable data; and

wherein the tip and cue server and the at least one data analysis engine are operable to run autonomously without requiring user interaction and/or input.

25. The system of claim 24 , further including a visualization of the semantic map.

26. A method for autonomous spectrum management in an electromagnetic environment comprising:

providing a semantic engine including a programmable rules and policy editor, wherein the programmable rules and policy editor includes at least one rule and/or at least one policy;

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

analyzing the measured data using at least one data analysis engine, thereby creating analyzed data, wherein the at least one data analysis engine includes a detection engine and a learning engine;

learning the electromagnetic environment using the learning engine;

automatically detecting at least one signal of interest using the detection engine; and

creating actionable data using a tip and cue server based on the analyzed data from the at least one data analysis engine;

wherein the tip and cue server and the at least one data analysis engine are operable to run autonomously without requiring user interaction and/or input.

27. The method of claim 26 , further including the tip and cue server activating an alarm and/or providing at least one report based on the actionable data.

28. The method of claim 26 , further including the semantic engine creating a semantic map including target data.

29. The method of claim 26 , wherein the actionable data is created in near-real time.

Assignments (1)

Continuity (7)

Cited By (105)

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