| CPC H04W 16/14 (2013.01) [G06F 30/27 (2020.01); G06N 3/02 (2013.01); G06N 5/022 (2013.01); G06N 5/04 (2013.01); G06N 20/00 (2019.01); G06N 20/10 (2019.01); G06N 20/20 (2019.01); H04L 41/0893 (2013.01); H04L 41/16 (2013.01); H04W 16/10 (2013.01); H04W 24/02 (2013.01); H04W 72/0453 (2013.01); G06N 3/042 (2023.01); G06N 3/045 (2023.01); H04L 41/0894 (2022.05); H04W 24/08 (2013.01)] | 20 Claims |

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1. A system for predicting and mitigating interference in an electromagnetic environment comprising:
at least one sensor operable to monitor the electromagnetic environment and create measured data based on the electromagnetic environment, wherein the at least one sensor is in communication with a learning engine, at least one data analysis engine, a semantic engine, and at least one server;
wherein the at least one server is operable to create actionable data;
wherein the learning engine is operable to utilize prediction models to create forecasts for future spectrum usage;
wherein the prediction models incorporate descriptive analytics, diagnostic analytics, predictive analytics, and/or prescriptive analytics;
wherein the learning engine is operable to predict interference in the electromagnetic environment based on the prediction models;
wherein the at least one server creates the actionable data based on the predicted interference, analyzed data from the at least one data analysis engine, and information relating to a rule or a policy;
wherein the semantic engine is operable to establish the rule or the policy based on converting a user data input into the actionable data using natural language processing (NLP).
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