US 11,750,214 B2
System for electronic data compression by automated time-dependent compression algorithm
Brandon Sloane, Indian Land, SC (US)
Assigned to BANK OF AMERICA CORPORATION, Charlotte, NC (US)
Filed by BANK OF AMERICA CORPORATION, Charlotte, NC (US)
Filed on Jan. 27, 2023, as Appl. No. 18/102,423.
Application 18/102,423 is a continuation of application No. 17/363,478, filed on Jun. 30, 2021, granted, now 11,601,136.
Prior Publication US 2023/0170919 A1, Jun. 1, 2023
This patent is subject to a terminal disclaimer.
Int. Cl. G06F 16/17 (2019.01); H03M 7/30 (2006.01); G06F 16/174 (2019.01)
CPC H03M 7/6011 (2013.01) [G06F 16/1744 (2019.01)] 20 Claims
OG exemplary drawing
 
1. A system for electronic data compression by automated time-dependent compression algorithm, the system comprising:
a communication device;
at least one processing device; and
at least one non-transitory storage device with computer-readable program code stored thereon and accessible by the at least one processing device, wherein the computer-readable code when executed is configured to cause the at least one processing device to:
identify, within a network, a data set;
detect, based on a countdown timer associated with the data set, that a time threshold for the data set has been reached;
based on detecting that the time threshold for the data set has been reached, execute a data compression process on the data set, wherein the data compression process comprises removing at least one least significant bit from the data set;
iteratively execute the data compression process on the data set at a predefined interval, wherein the predefined interval is based on a compression rate associated with the data set;
detect that further compression of the data set would cause the data set to be unrecoverable;
determine that the data set is fully compressed;
detect that the data set has been accessed by a computing device within the network;
initiate an intelligent reconstruction process on the data set, wherein the intelligent reconstruction process comprises generating a reconstructed data set using a fuzzy reconstruction algorithm to restore the at least one least significant bit of the data set; and
provision the reconstructed data set to the computing device.