US 12,328,639 B1
Dynamic geofence generation and adjustment for asset tracking and monitoring
Jason Smith, Signal Mountain, TN (US); Pierre Gavaret, Novato, CA (US); Matthew Basham, Oakland, CA (US); Suryakant Kaushik, Austin, TX (US); Faiz Sohaib Abbasi, San Francisco, CA (US); Jaiveer Kothari, San Francisco, CA (US); Frieda Bobay, Hendersonville, TN (US); Matthew Geddie, New York, NY (US); Darrin Joseph Yuhn, Jr., Kansas City, MO (US); Katherine Heddleston, Austin, TX (US); and Rachel Hiu Tung Cheng, San Francisco, CA (US)
Assigned to Samsara Inc., San Francisco, CA (US)
Filed by Samsara Inc., San Francisco, CA (US)
Filed on Jun. 24, 2024, as Appl. No. 18/752,307.
Claims priority of provisional application 63/631,353, filed on Apr. 8, 2024.
Int. Cl. H04W 4/021 (2018.01); G06Q 10/083 (2024.01); G06Q 10/0833 (2023.01); H04W 4/029 (2018.01)
CPC H04W 4/021 (2013.01) [G06Q 10/0833 (2013.01); G06Q 10/0838 (2013.01); H04W 4/029 (2018.02)] 9 Claims
OG exemplary drawing
 
1. A computerized method of generating a dynamic combined geofence, the computerized method performed by a computing system having a hardware processor and a non-transitory computer-readable storage device storing software instructions executable by the computing system to perform the computerized method comprising:
a) detecting locations of a group of assets including two or more primary assets and one or more secondary assets, wherein locations of secondary assets are detected based on locations of one or more primary assets;
b) determining a geofence associated with a first primary asset, wherein the first primary asset is a vehicle and a first secondary asset of the one or more secondary assets comprises a tool or equipment associated with the vehicle;
c) determining a geofence associated with a second primary asset;
d) identifying an overlap of geofences of first primary asset and the second primary asset;
e) adjusting one or more of a size or a shape of a combined geofence based on the identified overlap, wherein adjusting the combined geofence comprises using one or more machine learning algorithms to make an adjustment to the combined geofence based on historical data; and
f) repeating (c)-(e) for each additional primary asset having a geofence overlapping the combined geofence.