Techniques for automatically outputting severe weather notifications at a user's mobile computing device

• US 8,588,821 B1
• Filed: 10/08/2012
• Issued: 11/19/2013
• Est. Priority Date: 10/08/2012
• Status: Expired due to Fees

• Current Assignee: Google LLC (Alphabet Inc.)
• Original Assignee: Google Inc. (Alphabet Inc.)
• Inventors: Hewinson, Philip
• Primary Examiner(s): Agosta, Steve D
• Application Number:
  US13/646,821
• Time in Patent Office: 407 Days
• Field of Search: 455/414.1, 455/414.2, 455/414.3, 455418-420, 455/432.1, 455/550.1, 455/566, 455/569.2, 4554561-457, 340/601, 340/602, 340/687, 701/200, 701/204, 701/211, 707/705
• US Class Current: 455/456.3
• CPC Class Codes: G06Q 10/04 Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem" market predictions or forecasting for commercial activities G06Q30/0202
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: H04L 51/222 using geographical location information, e.g. messages transmitted or received in proximity of a certain spot or area
• CPC Class Codes: H04W 24/00 Supervisory, monitoring or testing arrangements
• CPC Class Codes: H04W 4/02 Services making use of location information
• CPC Class Codes: H04W 4/029 Location-based management or tracking services

Abstract

A computer-implemented technique includes receiving, at a mobile computing device including one or more processors, an input from a user, the input indicating a weather severity threshold for providing a notification at the mobile computing device. The technique includes determining one or more locations where the mobile computing device is likely to be, indicative of a likely location of a user, during a future period of time based on user-related data. The technique includes receiving a weather prediction for the future period of time for each of the one or more locations. The technique also includes automatically outputting the notification when the weather prediction for at least one of the one or more locations exceeds the weather severity threshold and at a time depending on distances between the one of more locations and a home location of the user.

Claims

1. A computer-implemented method, comprising:

receiving, at a mobile computing device including one or more processors, an input from a user, the input indicating a weather severity threshold for providing a notification at the mobile computing device;

determining, at the mobile computing device, one or more locations where the mobile computing device is likely to be during a future period of time based on user-related data from at least one of a plurality of software applications associated with the user, the plurality of software applications including (i) a calendar application, (ii) a travel application, and (iii) an aggregation application;

receiving, at the mobile computing device, a weather prediction for the future period of time for each of the one or more locations;

determining, using the at least one of the plurality of software applications, whether any of the one or more locations that are greater than a distance threshold from a residence location of the user are associated with a multiple-day trip by the user; and

automatically outputting, at the mobile computing device, the notification responsive to the weather prediction for at least one of the one or more locations exceeding the weather severity threshold, the automatically outputting occurring;

(i) at a first time responsive to none of the one or more locations being greater than the distance threshold from the residence location of the user, and

(ii) at a second time responsive to at least one of the one or more locations being greater than the distance threshold from the residence location of the user and associated with a multiple-day trip, wherein the second time is before the first time and before the user is scheduled, according to the at least one of the plurality of software applications, to leave for the multiple-day trip.

2. The computer-implemented method of claim 1, wherein automatically outputting the notification includes outputting, at the mobile computing device, the notification by overriding or interrupting any applications or processes currently being executed by the mobile computing device.

3. The computer-implemented method of claim 2, wherein automatically outputting the notification includes outputting, at the mobile computing device, a pop-up window including the notification.

4. The computer-implemented method of claim 2, wherein automatically outputting the notification includes:

generating, at the mobile computing device, an electronic message including the notification; and

outputting, at the mobile computing device, the electronic message.

5. The computer-implemented method of claim 1, wherein the input indicates first and second weather severity thresholds for providing the notification at the mobile computing device, wherein the second weather severity threshold is more severe than the first weather severity threshold, and wherein the notification is automatically output at the mobile computing device at least one of:

(i) at a third time responsive to the weather prediction for at least one of the one or more locations exceeding the first weather severity threshold, and

(ii) at a fourth time responsive to the weather prediction for at least one of the one or more locations exceeding the second weather severity threshold, wherein the fourth time is before the third time.

6. The computer-implemented method of claim 1, wherein the notification further includes a recommendation relating to the weather prediction that exceeds the weather severity threshold, and wherein the recommendation identifies at least one of (i) a recommended article of clothing for the user based on the weather prediction and (ii) a device for assisting the user with respect to the weather prediction that exceeds the weather severity threshold.

7. The computer-implemented method of claim 1, wherein the weather prediction includes (i) a weather condition prediction and (ii) a parameter prediction associated with the weather condition prediction, wherein the weather severity threshold indicates an amount of deviation from an average parameter associated with the weather condition prediction, and wherein automatically outputting the notification at the second time is based on whether the parameter prediction for the location greater than the distance threshold from the residence location of the user is greater than the weather severity threshold from the average parameter for that location.

8. The computer-implemented method of claim 1, wherein the user-related data includes at least one of (i) one or more repeat locations associated with the user and (ii) one or more movement patterns associated with the user, and wherein determining the one or more locations that the mobile computing device is likely to be during a future period based on the user-related data includes:

determining, at the mobile computing device, one or more possible locations that the mobile computing device is likely to be during the future time period based on the user-related data;

determining, at the mobile computing device, a probability score for each of the one or more possible locations using a machine learning algorithm, wherein a specific probability score is indicative of a likelihood that the mobile computing device is at a specific location during the future time period; and

selecting, at the mobile computing device, each of the one or more possible locations having a probability score greater than a probability score threshold to obtain the one or more locations, wherein the probability score threshold is indicative of an acceptable likelihood that the mobile computing device is at the specific location during the future time period.

9. A mobile computing device, comprising:

a communication device configured to receive an input from a user, the input indicating a weather severity threshold for providing a notification at the mobile computing device, the weather severity threshold indicating an amount of deviation from an average parameter associated with a weather condition prediction;

one or more processors configured to determine one or more locations where the mobile computing device is likely to be during a future period of time based on user-related data; and

a user interface configured to automatically output the notification responsive to a weather prediction for at least one of the one or more locations exceeding the weather severity threshold, the weather prediction including (i) the weather condition prediction and (ii) a parameter prediction associated with the weather condition prediction, the automatically outputting occurring;

(i) at a first time responsive to none of the one or more locations being greater than a distance threshold from a residence location of the user, and

(ii) at a second time responsive to at least one of the one or more locations being greater than the distance threshold from the residence location of the user and the parameter prediction for the at least one of the one or more locations being greater than the distance threshold from the residence location of the user is greater than the weather severity threshold from the average parameter for that location, wherein the second time is before the first time, wherein the communication device is further configured to receive the weather prediction for the future period of time for each of the one or more locations.

10. The mobile computing device of claim 9, wherein the user interface is configured to automatically output the notification by overriding or interrupting any applications or processes currently being executed by the mobile computing device.

11. The mobile computing device of claim 10, wherein the user interface is configured to automatically output the notification via a pop-up window including the notification.

12. The mobile computing device of claim 10, wherein the one or more processors are further configured to generate an electronic message including the notification, and wherein the user interface is configured to automatically outputting the notification by outputting the electronic message.

13. The mobile computing device of claim 9, wherein the input indicates first and second weather severity thresholds for providing the notification at the mobile computing device, wherein the second weather severity threshold is more severe than the first weather severity threshold, and wherein the user interface is configured to automatically output the notification at least one of:

(i) at a third time responsive to the weather prediction for at least one of the one or more locations exceeding the first weather severity threshold, and

(ii) at a fourth time responsive to the weather prediction for at least one of the one or more locations exceeding the second weather severity threshold, wherein the fourth time is before the third time.

14. The mobile computing device of claim 9, wherein the notification further includes a recommendation relating to the weather prediction that exceeds the weather severity threshold, and wherein the recommendation identifies at least one of (i) a recommended article of clothing for the user based on the weather prediction and (ii) a device for assisting the user with respect to the weather prediction that exceeds the weather severity threshold.

15. The mobile computing device of claim 9, wherein the one or more processors are configured to determine the one or more locations where the mobile computing device is likely to be during the future period of time further based on at least of a plurality of software applications associated with the user, the plurality of software applications including (i) a calendar application, (ii) a travel application, and (iii) an aggregation application.

16. The mobile computing device of claim 15, wherein the one or more processors are further configured to determine whether any of the one or more locations that are greater than the distance threshold from the residence location of the user are associated with a multiple-day trip by the user using the at least one of the plurality of software applications, wherein when a specific location is associated with a multiple day trip, the second time is before the user is scheduled to leave for the multiple-day trip according to the at least one of the plurality of software applications.

17. The mobile computing device of claim 9, wherein the user-related data includes at least one of (i) one or more repeat locations associated with the user and (ii) one or more movement patterns associated with the user, and wherein the one or more processors are configured to determine the one or more locations that the mobile computing device is likely to be during a future period based on the user-related data by:

determining one or more possible locations that the mobile computing device is likely to be during the future time period based on the user-related data;

determining a probability score for each of the one or more possible locations using a machine learning algorithm, wherein a specific probability score is indicative of a likelihood that the mobile computing device is at a specific location during the future time period; and

selecting each of the one or more possible locations having a probability score greater than a probability score threshold to obtain the one or more locations, wherein the probability score threshold is indicative of an acceptable likelihood that the mobile computing device is at the specific location during the future time period.

18. A non-transitory computer-readable medium having instructions stored thereon that, when executed by one or more processors of a mobile computing device, causes the mobile computing device to perform operations including:

receiving an input from a user, the input indicating a weather severity threshold for providing a notification at the mobile computing device;

determining one or more locations where the mobile computing device is likely to be during a future period of time based on user-related data, the user-related data including at least one of (i) one or more repeat locations associated with the user and (ii) one or more movement patterns associated with the user, and the determining the one or more locations including;

determining one or more possible locations that the mobile computing device is likely to be during the future time period based on the user-related data;

determining a probability score for each of the one or more possible locations using a machine learning algorithm, wherein a specific probability score is indicative of a likelihood that the mobile computing device is at a specific location during the future time period; and

selecting each of the one or more possible locations having a probability score greater than a probability score threshold to obtain the one or more locations, wherein the probability score threshold is indicative of an acceptable likelihood that the mobile computing device is at the specific location during the future time period; and

receiving a weather prediction for the future period of time for each of the one or more locations; and

automatically outputting the notification responsive to the weather prediction for at least one of the one or more locations exceeding the weather severity threshold, the automatically outputting occurring;

(i) at a first time responsive to none of the one or more locations being greater than a distance threshold from a residence location of the user, and

(ii) at a second time responsive to at least one of the one or more locations being greater than the distance threshold from the residence location of the user, wherein the second time is before the first time.

19. The computer-readable medium of claim 18, wherein automatically outputting the notification includes outputting the notification by overriding or interrupting any applications or processes currently being executed by the mobile computing device.

20. The computer-readable medium of claim 19, wherein automatically outputting the notification includes outputting a pop-up window including the notification.

21. The computer-readable medium of claim 19, wherein automatically outputting the notification includes:

generating an electronic message including the notification; and

outputting the electronic message.

22. The computer-readable medium of claim 18, wherein the input indicates first and second weather severity thresholds for providing the notification at the mobile computing device, wherein the second weather severity threshold is more severe than the first weather severity threshold, and wherein the notification is automatically output at the mobile computing device at least one of:

(i) at a third time responsive to the weather prediction for at least one of the one or more locations exceeding the first weather severity threshold, and

(ii) at a fourth time responsive to the weather prediction for at least one of the one or more locations exceeding the second weather severity threshold, wherein the fourth time is before the third time.

23. The computer-readable medium of claim 18, wherein the notification further includes a recommendation relating to the weather prediction that exceeds the weather severity threshold, and wherein the recommendation identifies at least one of (i) a recommended article of clothing for the user based on the weather prediction and (ii) a device for assisting the user with respect to the weather prediction that exceeds the weather severity threshold.

24. The computer-readable medium of claim 18, wherein determining the one or more locations where the mobile computing device is likely to be during the future period of time is further based on at least of a plurality of software applications associated with the user, the plurality of software applications including (i) a calendar application, (ii) a travel application, and (iii) an aggregation application.

25. The computer-readable medium of claim 24, wherein the operations further include determining whether any of the one or more locations that are greater than the distance threshold from the residence location of the user are associated with a multiple-day trip by the user using the at least one of the plurality of software applications, wherein when a specific location is associated with a multiple day trip, the second time is before the user is scheduled to leave for the multiple-day trip according to the at least one of the plurality of software applications.

26. The computer-readable medium of claim 18, wherein the weather prediction includes (i) a weather condition prediction and (ii) a parameter prediction associated with the weather condition prediction, wherein the weather severity threshold indicates an amount of deviation from an average parameter associated with the weather condition prediction, and wherein automatically outputting the notification at the second time is based on whether the parameter prediction for the location greater than the distance threshold from the residence location of the user is greater than the weather severity threshold from the average parameter for that location.