US 12,267,155 B2
Machine-learning based analysis and response based on electromagnetic waveforms and sensor data
Syed Mohammad Amir Husain, Georgetown, TX (US)
Assigned to SPARKCOGNITION, INC., Austin, TX (US)
Filed by SparkCognition, Inc., Austin, TX (US)
Filed on Sep. 7, 2021, as Appl. No. 17/468,013.
Claims priority of provisional application 63/075,950, filed on Sep. 9, 2020.
Prior Publication US 2022/0077951 A1, Mar. 10, 2022
This patent is subject to a terminal disclaimer.
Int. Cl. H04B 1/00 (2006.01); G06N 20/00 (2019.01); H04K 3/00 (2006.01)
CPC H04K 3/80 (2013.01) [G06N 20/00 (2019.01); H04B 1/0003 (2013.01)] 23 Claims
OG exemplary drawing
 
1. A method comprising:
determining, based at least in part on parameters of a software defined radio (SDR), waveform data descriptive of an electromagnetic waveform;
obtaining sensor data distinct from the waveform data;
generating feature data based on the sensor data and the waveform data;
providing the feature data as input to a first machine learning model; and
initiating a response action based on an output of the first machine learning model.