Predictive alert targeting for mass notification systems

• US 8,542,117 B1
• Filed: 02/15/2011
• Issued: 09/24/2013
• Est. Priority Date: 02/18/2010
• Status: Active Grant

• Current Assignee: AtHoc Incorporated (Blackberry Limited)
• Original Assignee: AtHoc Incorporated (Blackberry Limited)
• Inventors: Miasnik, Guy, Siegel, Aviv
• Primary Examiner(s): Tweel, Jr., John A
• Application Number:
  US13/027,602
• Time in Patent Office: 952 Days
• Field of Search: 340/540, 370/230, 370/232, 370/252, 455/11.1, 455/41.3, 455/91, 455/404.1, 455/404.2, 455/423, 455/561, 725/19
• US Class Current: 340/540
• CPC Class Codes: G08B 23/00 Alarms responsive to unspecified undesired or abnormal conditions
• CPC Class Codes: G08B 27/00 Alarm systems in which the alarm condition is signalled from a central station to a plurality of substations
• CPC Class Codes: G08B 27/005 with transmission via computer network
• CPC Class Codes: G08B 27/006 with transmission via telephone network
• CPC Class Codes: G08B 5/222 Personal calling arrangements or devices, i.e. paging systems selective calling systems and call receivers H04W84/00, H04W68/00
• CPC Class Codes: H04W 4/90 Services for handling of emergency or hazardous situations, e.g. earthquake and tsunami warning systems [ETWS]

Abstract

A system and a method are disclosed for predicting potential reach of an alert to a targeted audience, targeted personal delivery devices and targeted non-personal notification delivery devices in an emergency mass notification system. The method includes receiving recipients and alert delivery devices data which define a targeted audience and devices of an emergency alert. The method further comprises evaluating contact and configuration data targeting quality rating, tracking data targeting quality rating and real-time data targeting quality rating based on the received recipients and devices data and a data sources repository. Responsive to the targeting quality ratings and prediction weighting data (e.g., numeric weights and descriptive thresholds), the method generating one or more predictions of the potential reach of the alert based on the targeting quality ratings.

Claims

1. A method for predicting potential reach of an alert to a plurality of targeted recipients within an emergency mass notification system, the method comprising:

receiving a plurality of recipients data and delivery devices data, the recipients data and delivery devices data defining a targeted audience of an alert, the plurality of recipients data identifying at least one of a designated set of users and non-personal notification devices delivery end points, and the plurality of delivery devices data identifying at least one of a designated set of alert personal communication devices associated with the plurality of recipients and a designated set of non-personal devices delivery end points;

evaluating at least one of;

contact data targeting quality rating based on the plurality of the recipients data and delivery devices data and a user and device information database;

tracking data targeting quality rating based on the plurality of the recipients data and delivery devices data and an alert delivery events tracking database;

real-time data targeting quality rating based on the plurality of the recipients data and delivery devices data and a real-time data database;

generating at least one prediction of the potential reach of the alert based on at least one of the contact data targeting quality rating, the tracking data targeting quality rating and the real-time data targeting quality rating; and

outputting the prediction of the potential reach of the alert.

2. The method of claim 1, wherein evaluating contact data targeting quality rating comprises generating at least one of targeting quality ratings of the plurality of recipients and delivery devices based on data availability, data validity and data update quality associated with the plurality of recipients and delivery devices.

3. The method of claim 1, wherein evaluating tracking data targeting quality rating comprises generating at least one of targeting quality ratings of the plurality of recipients and delivery devices based on tracking data availability, consistency of alerts delivery and tracking data freshness associated with the plurality of recipients and delivery devices.

4. The method of claim 1, wherein evaluating real-time data targeting quality rating comprises generating at least one of targeting quality ratings of the plurality of recipients and delivery devices based on current device status, recipient presence information, recipient location information, data freshness associated with the plurality of recipients and delivery devices.

5. The method of claim 1, further comprising receiving a plurality of prediction weighting data for generating the prediction of the potential reach of the alert.

6. The method of claim 1, further comprises using the prediction of alert targeting quality to optimize alert delivery configuration and to maximize the reach of the alert in alert preparation and configuration.

7. The method of claim 1, further comprises using the prediction of alert targeting quality to ensure maximum reach to all intended audience during at least one of alert creation and alert activation.

8. The method of claim 7, wherein using the prediction of alert targeting quality during alert activation further comprises comparing the prediction alert target quality to previous prediction alert target quality values and indicating differences between the prediction alert target quality values.

9. The method of claim 1, further comprises using the prediction of alert targeting quality to automatically prioritize users and devices with high targeting quality measure over users and devices with low targeting quality measure during alert delivery.

10. The method of claim 1, further comprises periodically monitoring the quality of users and devices data of the prediction of alert targeting quality.

11. The method of claim 1, wherein generating at least one prediction of the potential reach of the alert comprises estimating whether the alert reaches at least one of the plurality of recipients via at least one of the delivery devices associated with the recipient.

12. A non-transitory computer-readable storage medium storing executable computer program instructions for predicting potential reach of an alert to a plurality of targeted recipients within an emergency mass notification system, the computer program instructions comprising instructions for:

receiving a plurality of recipients data and delivery devices data, the recipients data and delivery devices data defining a targeted audience of receiving an alert, the plurality of recipients data identifying at least one of a designated set of users and non-personal notification devices delivery end points, and the plurality of delivery devices data identifying at least one of a designated set of alert personal communication devices associated with the plurality of recipients and a designated set of non-personal devices delivery end points;

evaluating at least one of;

contact data targeting quality rating based on the plurality of the recipients data and delivery devices data and a user and device information database;

tracking data targeting quality rating based on the plurality of the recipients data and delivery devices data and an alert delivery events tracking database;

real-time data targeting quality rating based on the plurality of the recipients data and delivery devices data and a real-time data database;

generating at least one prediction of the potential reach of the alert based on at least one of the contact data targeting quality rating, the tracking data targeting quality rating and the real-time data targeting quality rating; and

outputting the prediction of the potential reach of the alert.

13. The computer-readable storage medium of claim 12, wherein the computer program instructions for evaluating contact data targeting quality rating comprises computer program instructions for generating at least one of targeting quality ratings of the plurality of recipients and delivery devices based on data availability, data validity and data update quality associated with the plurality of recipients and delivery devices.

14. The computer-readable storage medium of claim 12, wherein the computer program instructions for evaluating tracking data targeting quality rating comprises computer program instructions for generating at least one of targeting quality ratings of the plurality of recipients and delivery devices based on tracking data availability, consistency of alerts delivery and tracking data freshness associated with the plurality of recipients and delivery devices.

15. The computer-readable storage medium of claim 12, wherein the computer program instructions for evaluating real-time data targeting quality rating comprises computer program instruction for generating at least one of targeting quality ratings of the plurality of recipients and delivery devices based on current device status, recipient response information, recipient location information, data freshness associated with the plurality of recipients and delivery devices.

16. The computer-readable storage medium of claim 12, further comprising computer program instructions for receiving a plurality of prediction weighting data for generating the prediction of the potential reach of the alert.

17. A system for predicting potential reach of an alert to a plurality of targeted recipients within an emergency mass notification system comprising:

a non-transitory computer-readable storage medium storing executable computer program modules comprising;

a targeting user and device data module for receiving a plurality of recipients data and delivery devices data, the recipients data and delivery devices data defining a targeted audience of receiving an alert, the plurality of recipients data identifying at least one of a designated set of users and non-personal notification devices delivery end points, and the plurality of delivery devices data identifying at least one of a designated set of alert personal communication devices associated with the plurality of recipients and a designated set of non-personal devices delivery end points;

a targeting quality rating engine for evaluating at least one of;

contact data targeting quality rating based on the plurality of the recipients data and delivery devices data and a user and device information database;

tracking data targeting quality rating based on the plurality of the recipients data and delivery devices data and an alert delivery events tracking database;

real-time data targeting quality rating based on the plurality of the recipients data and delivery devices data and a real-time data database; and

a predictive alert targeting engine for;

generating at least one prediction of the potential reach of the alert based on at least one of the contact data targeting quality rating, the tracking data targeting quality rating and the real-time data targeting quality rating; and

outputting the prediction of the potential reach of the alert; and

a processor for executing the computer program modules.

18. The system of claim 17, wherein the predictive alert targeting engine is further for using the prediction of alert targeting quality to optimize alert delivery configuration and to maximize the reach of the alert in alert preparation and configuration.

19. The system of claim 17, wherein the predictive alert targeting engine is further for using the prediction of alert targeting quality to ensure maximum reach to all intended audience during at least one of alert creation and alert activation.

20. The system of claim 19, wherein using the prediction of alert targeting quality during alert activation further comprises comparing the prediction alert target quality to previous prediction alert target quality values and indicating differences between the prediction alert target quality values.

21. The system of claim 17, wherein the predictive alert targeting engine is further for using the prediction of alert targeting quality to automatically prioritize users and devices with high targeting quality measure over users and devices with low targeting quality measure during alert delivery.

22. The system of claim 17, wherein the predictive alert targeting engine is further for periodically monitoring the quality of users and devices data of the prediction of alert targeting quality.