Methods and systems for generating setting recommendation to user accounts for registered vehicles via cloud systems and remotely applying settings

• US 9,104,537 B1
• Filed: 05/30/2013
• Issued: 08/11/2015
• Est. Priority Date: 04/22/2011
• Status: Active Grant

• Current Assignee: Emerging Automotive, LLC
• Original Assignee: Albert S. Penilla, Angel A. Penilla
• Inventors: Penilla, Albert S., Penilla, Angel A.
• Primary Examiner(s): Elchanti, Hussein A.
• Application Number:
  US13/906,335
• Time in Patent Office: 803 Days
• Field of Search: 701/36
• US Class Current: 1/1
• CPC Class Codes: B60L 1/06 using only one supply
• CPC Class Codes: B60L 2240/12 Speed
• CPC Class Codes: B60L 2240/34 Cabin temperature
• CPC Class Codes: B60L 2240/547 Voltage
• CPC Class Codes: B60L 2240/549 Current
• CPC Class Codes: B60L 2240/622 by satellite navigation
• CPC Class Codes: B60L 2240/662 Temperature
• CPC Class Codes: B60L 2240/667 Precipitation
• CPC Class Codes: B60L 2240/68 Traffic data
• CPC Class Codes: B60L 2240/70 Interactions with external data bases, e.g. traffic centres
• CPC Class Codes: B60L 2240/80 Time limits
• CPC Class Codes: B60L 2250/10 by alarm
• CPC Class Codes: B60L 2250/12 by confirmation, e.g. of the input
• CPC Class Codes: B60L 2250/16 by display
• CPC Class Codes: B60L 2250/18 by enquiring driving style
• CPC Class Codes: B60L 2250/20 by driver identification
• CPC Class Codes: B60L 3/12 Recording operating variables ; Monitoring of operating variables
• CPC Class Codes: B60L 53/305 Communication interfaces
• CPC Class Codes: B60L 53/63 in response to network capacity
• CPC Class Codes: B60L 53/64 Optimising energy costs, e.g. responding to electricity rates
• CPC Class Codes: B60L 53/65 : involving identification of vehicles or their battery types
• CPC Class Codes: B60L 53/665 : Methods related to measuring, billing or payment
• CPC Class Codes: B60L 53/68 : Off-site monitoring or control, e.g. remote control
• CPC Class Codes: B60L 53/80 : Exchanging energy storage elements, e.g. removable batteries
• CPC Class Codes: G06F 17/00 : Digital computing or data processing equipment or methods, specially adapted for specific functions information retrieval, database structures or file system structures therefor G06F16/00
• CPC Class Codes: G06Q 10/20 : Administration of product repair or maintenance
• CPC Class Codes: G06Q 20/18 : involving self-service terminals [SST], vending machines, kiosks or multimedia terminals
• CPC Class Codes: G06Q 20/308 : using the Internet of Things
• CPC Class Codes: G06Q 30/00 : Commerce
• CPC Class Codes: G06Q 30/0255 : based on user history
• CPC Class Codes: G06Q 30/0643 : Graphical representation of items or shoppers
• CPC Class Codes: G06Q 30/0645 : Rental transactions; Leasing transactions
• CPC Class Codes: G07C 2205/02 : using a vehicle scan tool
• CPC Class Codes: G07C 5/006 : Indicating maintenance
• CPC Class Codes: G07F 15/005 : dispensed for the electrical charging of vehicles electrical charging as such, B60L50/00
• CPC Class Codes: G08G 1/20 : Monitoring the location of vehicles belonging to a group, e.g. fleet of vehicles, countable or determined number of vehicles
• CPC Class Codes: H04L 67/306 : User profiles
• CPC Class Codes: H04W 4/44 : for communication between vehicles and infrastructures, e.g. vehicle-to-cloud [V2C] or vehicle-to-home [V2H]
• CPC Class Codes: Y02E 60/00 : Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
• CPC Class Codes: Y02T 10/70 : Energy storage systems for electromobility, e.g. batteries
• CPC Class Codes: Y02T 10/7072 : Electromobility specific charging systems or methods for batteries, ultracapacitors, supercapacitors or double-layer capacitors
• CPC Class Codes: Y02T 10/72 : Electric energy management in electromobility
• CPC Class Codes: Y02T 90/12 : Electric charging stations
• CPC Class Codes: Y02T 90/14 : Plug-in electric vehicles
• CPC Class Codes: Y02T 90/16 : Information or communication technologies improving the operation of electric vehicles
• CPC Class Codes: Y02T 90/167 : Systems integrating technologies related to power network operation and communication or information technologies for supporting the interoperability of electric or hybrid vehicles, i.e. smartgrids as interface for battery charging of electric vehicles [EV] or hybrid vehicles [HEV]
• CPC Class Codes: Y04S 10/126 : the energy generation units being or involving electric vehicles [EV] or hybrid vehicles [HEV], i.e. power aggregation of EV or HEV, vehicle to grid arrangements [V2G]
• CPC Class Codes: Y04S 30/14 : Details associated with the interoperability, e.g. vehicle recognition, authentication, identification or billing

Abstract

Methods and systems are provide a method for processing information associated with a vehicle. An example method includes receiving a plurality of actions set at the vehicle over a period of time. The actions can be received from a server or services of a provider over the Internet. The method includes updating a history profile for a user account of the vehicle for the plurality of actions. The history profile includes meta data for each of the plurality of actions. The method generates confidence scores for each of the plurality of actions in the history profile and generating one or more action recommendations that can be accepted for implementation by the vehicle. For actions having confidence scores that exceed a threshold, the method sends the one or more action recommendations to the user account associated with the vehicle.

Claims

1. A method for processing information associated with a vehicle, comprising,

(a) receiving a plurality of actions set at the vehicle over a period of time;

(b) updating a history profile for a user account of the vehicle for the plurality of actions, the history profile includes meta data for each of the plurality of actions;

(c) generating confidence scores for each of the plurality of actions in the history profile;

(d) generating one or more action recommendations, that can be accepted for implementation by the vehicle, for actions having confidence scores that exceed a threshold;

(e) sending the one or more action recommendations to the user account associated with the vehicle, the action recommendations including an accept or decline option that can be set via the user account to cause data to be received indicative of the option,

for action recommendations that are accepted,

(i) setting a time to send a programming instruction to the vehicle; and

(ii) sending the programming instruction to the vehicle to cause the vehicle to programmatically perform a programmed action to implement at least one of the action recommendations, the action recommendations being vehicle settings, wherein the method being executed by a processor.

2. The method of claim 1, wherein the meta data of each action includes a record of a time and date of each occurrence and for actions that show a repeating pattern of occurrences will have an increased confidence score, wherein the threshold is predefined to require a set number of occurrences of the actions to occur so that the repeating pattern is identifiable.

3. The method of claim 1, wherein confidence scores are increased for actions that reoccur multiple times at about a similar time and date, and the confidence scores are decreased for actions that do not reoccur multiple at about the similar time and date or occur at dissimilar times and dates.

5. The method of claim 1, wherein the actions set at the vehicle are selected from one or more of setting a temperature of the vehicle, setting a window defrost mode in the vehicle, heating a seat or seats of the vehicle, setting an emergency signal of the vehicle, setting an emergency signal for help, setting a restriction or enabling a feature for the vehicle, disabling the vehicle, selecting an audio setting, making a reservation for service, reporting an error in the vehicle, setting a position of mirrors of the vehicle, setting to open or crack windows upon reaching a temperature, setting notifications for recharging a battery if the vehicle is an electric vehicle, setting reminders to charge upon reaching a predefined battery state if an electric vehicle, setting parameters to identify nearby charge stations if the vehicle is an electric vehicle, setting advertisement settings allowed to be displayed via a screen of the electric vehicle, setting maps data, setting communications data, setting navigation data, setting display settings data, setting customization of display applications on the screen of the vehicle, setting suspension parameters for the vehicle, setting auto lock/unlock controls of the vehicle, activating an alarm, setting instructions to receive video feedback from the vehicle upon detection of alarm conditions, setting to call for help when an accident is detected, setting time of day on vehicle clocks based on local time;

setting navigation parameters in the vehicle, setting preferred radio stations, setting sensitivity of collision detection sensors, setting sensor programming, or combinations of two or more thereof.

6. The method of claim 1, further comprising:

(f) receiving sensor data from the vehicle, the sensor data being associated to particular ones of the plurality of actions, the sensor data being saved to the meta data of the respective actions in the history profile.

7. The method of claim 6, wherein the sensor data includes one or more of actual sensed temperature, geo-location, speed, vehicle condition, occupant identification, number of occupants sensed;

biometric detection of an occupant in the vehicle, proximity of surrounding vehicles or obstacles, voice data, video data, touch data, gesture data, surrounding vehicle shared sensor data, or at combination of two or more thereof.

8. The method claim 6,

wherein the confidence score for an action in the history profile is increased for actions having repeat occurrences while having similar sensor data present in the meta data of the actions, or

wherein the confidence score for an action in the history profile is increased for actions having repeat occurrences and having same sensor data present in the meta data of the actions.

9. The method claim 6, further comprising,

for particular sensors associated with particular actions, the action recommendation includes,

sending data to populate a user interface of a computing device with a control to accept or decline the option, the data sent is via a network connected to the Internet,

wherein the computing device is one of a vehicle computing device, or a mobile computer device, or a tablet computing device, or a smart phone computing device, or an internet terminal computing device, or a non-portable computing device;

wherein the data is sent to the user account, the user account being accessible over the Internet.

10. The method of claim 9, wherein when the sensor is a temperature sensor and the action is inputting a heating or cooling setting at the vehicle, the action recommendation includes,

sending data to populate a user interface of a computing device with a control to accept or decline the option, the data sent is via a network connected to the Internet,

wherein the computing device is one of a vehicle computing device, or a mobile computer device, or a tablet computing device, or a smart phone computing device, or an internet terminal computing device, or a non-portable computing device;

wherein the data is sent to the user account, the user account being accessible over the Internet.

11. The method of claim 10, wherein the heating or cooling setting includes one or more of activating a window defrost setting, or activating a heating setting, or activating an air conditioning setting,

wherein the action recommendation for the heating or cooling setting at least in part uses weather forecast data obtained from the Internet for a predicted geo-location of the vehicle.

12. The method of claim 11, further comprising,

receiving temperature data from a sensor of the vehicle;

determining that the received temperature is inconsistent with the weather forecast; and

programmatically declining the action recommendation if the action recommendation was initially accepted, such that the programming instruction is not sent to the vehicle or is updated so as to cancel the programming instruction.

13. The method of claim 1, wherein confidence scores for actions that exceed a threshold is indicative that such action will more likely than not occur again at a future time.

14. The method of claim 1, further comprising,

(f) accessing third-party history profiles of other user accounts;

(g) examining the actions and meta data of the third-party history profiles to identify similar actions and patterns to those of the history profile;

(h) adjusting one or more of the action recommendations in (d) based on the examining of (g), the adjusting being weighted to provide more significance to meta data in the history profile than that in the third-party history profiles.

15. The method of claim 14, wherein the action recommendations change over time based on changes in patterns detected in the history profile.

16. The method of claim 15, wherein changes in action recommendations include removal of previously accepted action recommendations when either override of activating the action is detected to occur a number of times or changes in patterns of use of the actions at the vehicle suggested removal of the previously accepted action recommendation.

17. The method of claim 14, wherein the third-party history profiles and the history profile are defined as one or more databases on storage accessible by a server that is accessible over the Internet,

wherein the vehicle uses communication logic for communicating with the server over the Internet,

wherein the server further includes logic for sending the action recommendations to devices of a user having the user account for the vehicle.

18. The method of claim 17, wherein the server executes cloud processing logic to perform operations (a)-(h).

4. The method as recited in 3, wherein increases in actions that reoccur multiple times at about a similar time and date have a repeating pattern that is indicative of a likelihood that the action recommendation will be accepted.

19. A method for recommending settings to be applied at a vehicle registered to a user account, the recommending being processed by a server that receives data from the vehicle over a network and sends action recommendations to one or more predefined user devices associated with the user account, comprising,

(a) receiving information at the server that a plurality of actions have been applied at the vehicle over a period of time;

(b) updating a history profile for a user account of the vehicle for the plurality of actions, the history profile includes meta data for each of the plurality of actions;

(c) generating confidence scores for each of the plurality of actions in the history profile, the confidence scores are saved to the meta data of the history profile;

(d) generating one or more action recommendations, that can be accepted for implementation by the vehicle, for actions having confidence scores that exceed a threshold;

(e) sending the one or more action recommendations to the user account associated with the vehicle, the action recommendations including an accept or decline option that can be set via the user account to cause data to be received indicative of the option,

for action recommendations that are accepted,

(i) setting a time to send a programming instruction to the vehicle; and

(ii) sending the programming instruction via the network to the vehicle to cause the vehicle to programmatically perform a programmed action to implement at least one of the action recommendations, the action recommendations being vehicle settings,

wherein the meta data of each action includes a record of a time and date of each occurrence and for actions that show a repeating pattern of occurrences will have an increased confidence score, wherein the threshold is predefined to require a set number of occurrences of the actions to occur so that the repeating pattern is identifiable, and wherein the method being executed by a processor.

20. A method for recommending settings to be applied at a vehicle registered to a user account, the recommending being processed by a server that receives data from the vehicle over a network and sends action recommendations to one or more predefined user devices associated with the user account, comprising,

(a) receiving information at the server that a plurality of actions have been applied at the vehicle over a period of time;

(b) updating a history profile for a user account of the vehicle for the plurality of actions, the history profile includes meta data for each of the plurality of actions;

(c) generating confidence scores for each of the plurality of actions in the history profile, the confidence scores are saved to the meta data of the history profile;

(d) generating one or more action recommendations, that can be accepted for implementation by the vehicle, for actions having confidence scores that exceed a threshold;

(e) sending the one or more action recommendations to the user account associated with the vehicle, the action recommendations including an accept or decline option that can be set via the user account to cause data to be received indicative of the option,

for action recommendations that are accepted,

(i) setting a time to send a programming instruction to the vehicle; and

(ii) sending the programming instruction via the network to the vehicle to cause the vehicle to programmatically perform a programmed action to implement at least one of the action recommendations, the action recommendations being vehicle settings,

(f) accessing third-party history profiles of other user accounts;

(g) examining the actions and meta data of the third-party history profiles to identify similar actions and patterns to those of the history profile; and

(h) adjusting one or more of the action recommendations in (d) based on the examining of (g), the adjusting being weighted to provide more significance to meta data in the history profile than that in the third-party history profiles.