US 12,142,119 B1
Intelligent method and system on autonomous monitoring and controlling of automatic teller machines (“ATMS”) in distress conditions leveraging sub-orbital satellite network
Shailendra Singh, Maharashtra (IN)
Assigned to Bank of America Corporation, Charlotte, NC (US)
Filed by Bank of America Corporation, Charlotte, NC (US)
Filed on Jan. 1, 2024, as Appl. No. 18/401,639.
Int. Cl. G07F 19/00 (2006.01); H04W 84/06 (2009.01)
CPC G07F 19/209 (2013.01) [G07F 19/207 (2013.01); H04W 84/06 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method for autonomously controlling and monitoring automatic teller machines (“ATMs”) during an ATM distress event, the autonomously controlling and monitoring being executed by a network of low-orbit satellites, the method comprising:
identifying, at a first ATM, the ATM distress event;
creating, using an ATM distress program stored on the first ATM, a distress message payload (“DMP”) associated with the first ATM, the DMP comprising:
a geolocation of the first ATM;
an ownership of the first ATM; and
the ATM distress event;
transmitting, using the first ATM, the DMP to a first low-orbit satellite in the network of low-orbit satellites;
transmitting, using the first low-orbit satellite, the DMP to all low-orbit satellites in the network of low-orbit satellites;
scanning, using an ATM monitoring program stored on all low-orbit satellites in the network of low-orbit satellites, all ATMs affected by the ATM distress event, including the first ATM (“the ATMs”);
transmitting, using low-orbit satellites in the network of low-orbit satellites located threshold distances from the ATMs, a data recovery and purge program to the ATMs;
creating, using the data recovery and purge program in the ATMs, data recovery and purge payloads (“DRAPPs”), the DRAPPs associated with the ATMs, the DRAPPs comprising:
geolocations of the ATMs;
ownerships of the ATMs; and
data stored on the ATMs;
storing, on all low-orbit satellites in the network of low-orbit satellites, the DRAPPs;
purging, using the data recovery and purge program stored on the ATMs, the data stored on the ATMs;
running a recovery/purge orchestration engine, using the first low-orbit satellite, the recovery/purge orchestration engine using machine learning (“ML”) to identify a pathway for transporting the DRAPPs to a centralized server, the pathway comprising all low-orbit satellites in the network of low-orbit satellites operating as carriers for the DRAPPs to the centralized server;
storing, on all low-orbit satellites in the network of low-orbit satellites, a copy of the DRAPPs in a satellite blockchain distributed ledger, wherein each low-orbit satellite in the network of low-orbit satellites is a block in the satellite blockchain distributed ledger;
receiving on the centralized server, via the recovery/purge orchestration engine, the DRAPPs; and
transferring, after the ATM distress event, the DRAPPs between low-orbit satellites in the network of low-orbit satellites located threshold distances from the ATMs and the ATMs, via the centralized server.