US 11,818,662 B2
Energy savings system based machine learning of wireless performance activity for mobile information handling system connected to plural wireless networks
Abu S. Sanaullah, Austin, TX (US); Liam B. Quinn, Austin, TX (US); and Jace W. Files, Round Rock, TX (US)
Assigned to Dell Products, LP, Round Rock, TX (US)
Filed by Dell Products, LP, Round Rock, TX (US)
Filed on Sep. 5, 2022, as Appl. No. 17/902,984.
Application 17/902,984 is a division of application No. 16/779,476, filed on Jan. 31, 2020, granted, now 11,438,841.
Prior Publication US 2022/0417861 A1, Dec. 29, 2022
Int. Cl. H04W 28/02 (2009.01); H04W 52/02 (2009.01); G06N 20/00 (2019.01)
CPC H04W 52/0258 (2013.01) [G06N 20/00 (2019.01); H04W 52/0254 (2013.01); H04W 52/0274 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A mobile information handling system comprising:
a processor, a memory, a power management system, and a plurality of wireless network interface modules for wireless connection to a plurality of wireless networks;
a wireless network interface control system for controlling the plurality of wireless network interface modules;
the processor executing instructions of a wireless utilization machine learning inference modulator to receive iterative wireless utilization profiles indicating aggregated time and location profiles of wireless network utilization parameters and the performance of each of the plurality wireless network interface modules; and
a sensor to receive input descriptive of the environment and location of the mobile information handling system for inclusion in the iterative wireless utilization profiles;
the processor reporting user configuration states for data needs including applications operating, and processing, port, battery, and memory hardware usage levels for inclusion in the iterative wireless utilization profiles;
the wireless utilization machine learning inference modulator to, upon execution of a machine learning process, determine a predictive time and date based plural wireless control setting index for adjusting control settings of the plural wireless network interface modules based on information associated with the received iterative wireless utilization profiles and updating the predictive time and date based plural wireless control setting index to a wireless recommendation history database; and
the wireless network interface control system accessing the predictive time and date based plural wireless control setting index correlating to a current calendar day, time and location to disable or leave enabled each of the plurality of wireless network interface modules.