System and method for creating a census hub in resource constrained regions

Patent metadata

Field	Value
Publication number	US-10929786-B2
Application number	US-201615058290-A
Country	US
Kind code	B2
Filing date	Mar 2, 2016
Priority date	Mar 2, 2016
Publication date	Feb 23, 2021
Grant date	Feb 23, 2021

Abstract

The disclosure provides systems and methods for generating attendance census models using data received from a network of automated census sensors as well as various additional secondary data sources. The models may be generated and used in real time to provide attendance predictions, to efficiently allocate resources, and to detect fraud, among many other uses.

First claim

What is claimed is:

1. A computer system, comprising:
one or more processors, one or more memories, one or more census gathering sensor inputs, one or more non-census data inputs, and one or more outputs;
one or more attendance census gathering sensors capable of providing sensor signals to the census gathering sensor inputs that represent one or more physical attributes of one or more student attendees;
one or more data signals connected to the non-census data inputs, the data signals being from a secondary or tertiary data source;
a database that stores one or more attendee data records containing attendee attribute information that represents the physical personal identification attributes of the student attendees determined from the sensor signals and one or more non-census data records containing non-census data determined from the non-census data inputs;
an aggregator that aggregates and correlates one or more of the attendee data records to one or more of the non-census data records using one or more of a time factor, a location factor and an identity factor to transform the database into a census hub, the census hub being a data structure with attendee data records correlated to one or more non-census data records by time, location, and identity of the student attendee;
an attendance pattern module that produces an attendance pattern for each of one or more of the student attendees, the attendance patterns produced from the attendee data records and the non-census data;
a data and predictors module that uses one or more factors in combination to produce one or more predictors;
a linkage module that links the predictors and attendance patterns; and
a prediction module that makes predictions based on the links provided by the linkage module to allocate resources by performing the following steps:
for one or more groups of students in one or more schools, determining an attendance forecast that includes past events and future predictions over a time scale; and
generating a notification based on the forecast that is a requisition order to a supplier.

2. A computer system, comprising:
one or more processors, one or more memories, one or more census gathering sensor inputs, one or more non-census data inputs, and one or more outputs;
one or more attendance census gathering sensors capable of providing sensor signals to the census gathering sensor inputs that represent one or more physical attributes of one or more student attendees;
one or more data signals connected to the non-census data inputs, the data signals being from a secondary or tertiary data source;
a database that stores one or more attendee data records containing attendee attribute information that represents the physical personal identification attributes of the student attendees determined from the sensor signals and one or more non-census data records containing non-census data determined from the non-census data inputs;
an aggregator that aggregates and correlates one or more of the attendee data records to one or more of the non-census data records using one or more of a time factor, a location factor and an identity factor to transform the database into a census hub, the census hub being a data structure with attendee data records correlated to one or more non-census data records by time, location, and identity of the student attendee;
an attendance pattern module that produces an attendance pattern for each of one or more of the student attendees, the attendance patterns produced from the attendee data records and the non-census data;
a data and predictors module that uses one or more factors in combination to produce one or more predictors;
a linkage module that links the predictors and attendance patterns; and
a prediction module that makes predictions based on the links provided by the linkage module to allocate resources by performing the following steps:
for one or more groups of students in one or more schools, determining an attendance forecast that includes past events and future predictions over a time scale; and
generating one or more notifications based on the forecast that include a requisition order to a supplier and a public notice to enable transparent and fair allocation and distribution of a resource.

3. A computer system, comprising:
one or more processors, one or more memories, one or more census gathering sensor inputs one or more non-census data inputs, and one or more outputs;
one or more attendance census gathering sensors capable of providing sensor signals to the census gathering sensor inputs that represent one or more physical attributes of one or more student attendees;
one or more data signals connected to the non-census data inputs, the data signals being from a secondary or tertiary data source;
a database that stores one or more attendee data records containing attendee attribute information that represents the physical personal identification attributes of the student attendees determined from the sensor signals and one or more non-census data records containing non-census data determined from the non-census data inputs;
an aggregator that aggregates and correlates one or more of the attendee data records to one or more of the non-census data records using one or more of a time factor, a location factor and an identity factor to transform the database into a census hub, the census hub being a data structure with attendee data records correlated to one or more non-census data records by time, location, and identity of the student attendee;
an attendance pattern module that produces an attendance pattern for each of one or more of the student attendees, the attendance patterns produced from the attendee data records and the non-census data;
a data and predictors module that uses one or more factors in combination to produce one or more predictors;
a linkage module that links the predictors and attendance patterns; and
a prediction module that makes predictions based on the links provided by the linkage module to allocate resources by performing the following steps:
for one or more groups of students in one or more schools, determining an attendance forecast that includes past events and future predictions over a time scale; and
generating one or more notifications based on the forecast that include a requisition order to a supplier and a public notice to enable transparent and fair allocation and distribution of a resource; and

the prediction module further predicts fraud by performing the following steps:
generating a student profile for one or more students; and
matching one or more of the student profiles to one or more fraud signatures to determine a fraudulent behavior.

4. The computer system of claim 3 , wherein the fraudulent behavior includes one or more of the following: fraudulent attendance data, credit card fraud, fraudulent resource allocation, and rates of fraud.

5. The computer system of claim 1 , wherein the processor is configured to extract, analyze, and characterize features from the attendee data records, and to align the physical personal identification attributes of the student attendees with user-supplied metadata and context information.

6. The computer system of claim 1 , wherein the census hub is a database configured to store historical census data from a plurality of venues, and wherein the computer system is further configured to generate an attendance model, and wherein the attendance forecast is part of the attendance model.

7. The computer system of claim 1 , wherein:
the sensor signals originate at one or more venues remotely located with respect to the computer system;
the secondary data source is one or more of the following: a sensor, a social media network, a website, a manual input device, o

Assignees

• IBM

Inventors

• Bhattacharya Kamal
• Kalton Alan
• Weldemariam Komminist

Classifications

• G06Q50/20

  Education · CPC title

• G06Q10/0631 Primary

  Resource planning, allocation, distributing or scheduling for enterprises or organisations · CPC title