# US 12,008,504 B2 · Food safety risk and sanitation compliance tracking

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- Number: US 12,008,504 B2
- Document ID: US12008504B2
- Status: Granted
- Kind: B2
- Application number: 16/413,998
- Filed: 2019-05-16
- Published: 2019-11-21
- Granted: 2024-06-11
- Earliest claimed: 2018-05-17
- Assignees: Ecolab USA Inc.
- Applicants: Ecolab USA Inc.
- Inventors: Nicolas A. Granucci; Jeffrey L. Testa; Kevin S. Smyth; Adam T. Johnson; Tracy A. Thomas; Darrell B. Wiser; Gregory B. Hayes
- Web page: https://patentgrep.com/patent/US12008504B2

## CPC

- G06Q 10/06: Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q 10/0635: Risk analysis of enterprise or organisation activities
- G06F 9/542: {Event management; Broadcasting; Multicasting; Notifications}
- G06Q 10/08774: {using consumer inventory reporting}
- G06Q 30/018: Certifying business or products
- G16H 20/60: relating to nutrition control, e.g. diets
- G16H 40/20: for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
- G06Q 50/12: Hotels or restaurants
- G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N)
- G16H: HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA

## Abstract

A system includes a server connected to a network. The server includes a data collection module, a database interaction module, and a predictive analysis module. The data collection module is configured to collect data, via the network, from one or more data sources, the data being related to food safety risk and sanitation compliance tracking of a food establishment. The database interaction module is configured to store, into a database, data collected by the data collection module and to retrieve data from the database. The predictive analysis module is configured to analyze data in the database and calculate, based on the analyzed data, a probability of the food establishment violating a health code.

## Claims

### Claim 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.

### Claim 2 (depends on 1)

The system of claim 1, wherein the one or more data sources further comprise at least one of: one or more dispensers of the food establishment configured to generate dispenser data, pest elimination services that generate pest control data, health department inspections that generate health department inspection data, one or more users that enter self-audit data and/or self-reported data, and servicers that generate equipment care and maintenance data.

### Claim 3 (depends on 1)

The system of claim 1, wherein the one or more sensors of the food establishment include at least one of: thermometers, hygrometers, and barometers.

### Claim 4 (depends on 2)

The system of claim 2, wherein the one or more dispensers include at least one of: sanitizer dispensers and water dispensers.

### Claim 5 (depends on 1)

The system of claim 1, wherein upon the calculated probability of the food establishment violating a health code exceeding a threshold, the server transmits a notification to one or more devices associated with the food establishment.

### Claim 6 (depends on 1)

The system of claim 1, wherein the server further comprises:
a report generator module configured to generate a report including the probability of the food establishment violating the health code.

### Claim 7 (depends on 6)

The system of claim 6, wherein the report generator is configured to transmit the report to a client device for display.

### Claim 8 (depends on 6)

The system of claim 6, wherein the probability of the food establishment violating the health code comprises a predictive risk score for the food establishment.

### Claim 9 (depends on 8)

The system of claim 8, wherein the probability of the food establishment violating the health code comprises a plurality of individual risk indicators for the food establishment, and wherein each of the plurality of individual risk indicators for the food establishment provides an assessment of risk relative to other food establishments.

### Claim 10 (depends on 9)

The system of claim 9, wherein the plurality of individual risk indicators for the food establishment comprise personal hygiene, cleaning and sanitation, time and temperature, and documentation.

### Claim 11

A method implemented on at least one server connected to a network, the method comprising:
tracking, using one or more data sources comprising one or more sensors located at a food establishment and connected to the network, one or more events at the food establishment;
generating, by the one or more data sources, 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;
collecting the data, via the network, from the one or more data sources;
storing, into a database, the collected data;
retrieving data from the database;
analyzing data in the database using predictive analytics algorithms to identify one or more trends and one or more predictive indicators; and
calculating, based on the analyzed data, a probability of a future inspection resulting in a violation of a health code.

### Claim 12 (depends on 11)

The method of claim 11, wherein the one or more data sources further comprise at least one of: one or more dispensers of the food establishment configured to generate dispenser data, pest elimination services that generate pest control data, health department inspections that generate health department inspection data, one or more users that enter self-audit data and/or self-reported data, and servicers that generate equipment care and maintenance data.

### Claim 13 (depends on 11)

The method of claim 11, wherein the one or more sensors of the food establishment include at least one of: thermometers, hygrometers, and barometers.

### Claim 14 (depends on 12)

The method of claim 12, wherein the one or more dispensers include at least one of: sanitizer dispensers and water dispensers.

### Claim 15 (depends on 11)

The method of claim 11, further comprising:
transmitting a notification to one or more devices associated with the food establishment upon the calculated probability of the food establishment violating a health code exceeding a threshold.

### Claim 16

A non-transitory computer-readable medium including instructions that, when executed by a computer, cause the computer to:
track, using one or more data sources comprising one or more sensors located at a food establishment and connected to a network, one or more events at the food establishment;
generate, using the one or more data sources, 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;
collect the data, via the network, from the one or more data sources;
store, into a database, the collected data;
retrieve the data from the database;
analyze the 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.

### Claim 17 (depends on 16)

The non-transitory computer-readable medium of claim 16, wherein the one or more data sources further comprise at least one of: one or more dispensers of the food establishment configured to generate dispenser data, pest elimination services that generate pest control data, health department inspections that generate health department inspection data, one or more users that enter self-audit data and/or self-reported data, and servicers that generate equipment care and maintenance data.

### Claim 18 (depends on 16)

The non-transitory computer-readable medium of claim 16, wherein the one or more sensors of the food establishment include at least one of: thermometers, hygrometers, and barometers.

### Claim 19 (depends on 17)

The non-transitory computer-readable medium of claim 17, wherein the one or more dispensers include at least one of: sanitizer dispensers and water dispensers.

### Claim 20 (depends on 16)

The non-transitory computer-readable medium of claim 16, further comprising instructions that, when executed by a computer, cause the computer to:
transmit a notification to one or more devices associated with the food establishment upon the calculated probability of the food establishment violating a health code exceeding a threshold.