US 12,113,875 B1
Apparatus and method for data conversion
Joseph Allen Steele, III, Plumas Lake, CA (US); Josh David Schumacher, Sacramento, CA (US); Mark Daniel Adams, Roseville, CA (US); and Betsy Danielle Urschel, Germantown, TN (US)
Assigned to Quick Quack Car Wash Holdings, LLC, Roseville, CA (US)
Filed by Quick Quack Car Wash Holdings, LLC, Roseville, CA (US)
Filed on May 11, 2023, as Appl. No. 18/196,238.
Int. Cl. H04L 67/50 (2022.01); G06V 30/148 (2022.01)
CPC H04L 67/535 (2022.05) [G06V 30/153 (2022.01)] 18 Claims
OG exemplary drawing
 
1. An apparatus for converting data, wherein the apparatus comprises:
at least a processor; and
a memory communicatively connected to the at least a processor, wherein the memory contains instructions configuring the at least a processor to:
extract, using a data extraction module, user activity data from user device data, wherein the user activity data comprises data related to user activity in a vehicle maintenance system;
classify the user activity data into one or more user activity data groups;
convert, using a data converting module, the user activity data to system data as a function of the one or more user activity data groups, wherein the converting module is further configured to perform a data enrichment of the system data after conversion by adding additional data to the system data, wherein the additional data is generated by performing a web indexing process comprising systematically browsing and indexing sources using a web query to retrieve demographic information;
flag missing data of the user activity data using the data converting module;
identify trends in user behavior as a function of the converted user activity data, wherein identifying trends in the user behavior comprises using a machine-learning model configured to identity demographics trends related to a vehicle maintenance system; and
generate, using a report generation module, a user activity report as a function of the system data and the flagged missing data, wherein the user activity report comprises the identified trends of user behavior related to optimizing usability of the user activity data.