US 12,008,504 B2
Food safety risk and sanitation compliance tracking
Nicolas A. Granucci, Woodbury, MN (US); Jeffrey L. Testa, Greensboro, NC (US); Kevin S. Smyth, Woodbury, MN (US); Adam T. Johnson, Bentonville, AR (US); Tracy A. Thomas, Woodbury, MN (US); Darrell B. Wiser, Lehi, UT (US); and Gregory B. Hayes, Apple Valley, MN (US)
Assigned to Ecolab USA Inc., St. Paul, MN (US)
Filed by Ecolab USA Inc., St. Paul, MN (US)
Filed on May 16, 2019, as Appl. No. 16/413,998.
Claims priority of provisional application 62/672,944, filed on May 17, 2018.
Prior Publication US 2019/0354907 A1, Nov. 21, 2019
Int. Cl. G06Q 10/0635 (2023.01); G06F 9/54 (2006.01); G06Q 30/018 (2023.01); G06Q 50/12 (2012.01)
CPC G06Q 10/0635 (2013.01) [G06F 9/542 (2013.01); G06Q 30/018 (2013.01); G06Q 50/12 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A system, comprising:
one or more data sources comprising one or more sensors located at a food establishment and connected to a network, the one or more data sources being configured to:
track one or more events at the food establishment; and
generate data based on the one or more events at the food establishment, the data being related to food safety risk and sanitation compliance tracking of the food establishment, wherein the data generated by the one or more sensors comprise sensor data; and
a server connected to the network, the server comprising:
a data collection module configured to collect the data, via the network, from the one or more data sources;
a database interaction module configured to store, into a database, data collected by the data collection module and to retrieve data from the database; and
a predictive analysis module configured to analyze data in the database using predictive analytics algorithms to identify one or more trends and one or more predictive indicators and calculate, based on the analyzed data, a probability of a future inspection resulting in a violation of a health code.