US 12,309,878 B1
Electronic device identification using emitted electromagnetic signals
Augusto Savaris, Chicago, IL (US); Joseph Loftus, Seattle, WA (US); Michael B. Cox, Chicago, IL (US); and Keith Puckett, Chicago, IL (US)
Assigned to Ubiety Technologies, Inc., Chicago, IL (US)
Filed by Ubiety Technologies, Inc., Chicago, IL (US)
Filed on Jun. 21, 2024, as Appl. No. 18/750,866.
Int. Cl. H04W 12/00 (2021.01); H04W 8/00 (2009.01); H04W 12/79 (2021.01); H04W 24/02 (2009.01); H04W 84/12 (2009.01)
CPC H04W 8/005 (2013.01) [H04W 12/009 (2019.01); H04W 12/79 (2021.01); H04W 24/02 (2013.01); H04W 84/12 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A computer system comprising:
at least one hardware processor; and
at least one non-transitory computer-readable storage medium storing instructions, which,
when executed by the at least one hardware processor, cause the computer system to:
receive at least one Wi-Fi probe request emitted by an electronic device, wherein the at least one Wi-Fi probe request includes multiple metadata fields;
extract data values present in a subset of the multiple metadata fields,
wherein the subset of the multiple metadata fields is determined to be indicative of a type of the electronic device based on training a machine learning model to identify, based on wireless signals emitted by other electronic devices, the other electronic devices;
determine that at least one metadata field of the subset of the multiple metadata fields is empty;
responsive to determining that the at least one metadata field is empty, insert a particular value into the at least one metadata field;
generate a feature vector based on the data values present in the subset of the multiple metadata fields and the particular value present in the at least one metadata field,
wherein the feature vector is indicative of the type of the electronic device;
determine, using the machine learning model, the type of the electronic device based on the feature vector; and
send the type of the electronic device to a computer device.