IP Library › Granted Patent US 9,758,095
Granted Patent B2
US 9,758,095 · App. 15/005,675 · Granted Sep 12, 2017

Smartwatch blackbox

Inventors: Benjamin D. Briggs (Waterford, NY); Lawrence A. Clevenger (LaGrangeville, NY); Leigh Anne H. Clevenger (Rhinebeck, NY); Jonathan H. Connell, II (Cortlandt Manor, NY); Nalini K. Ratha (White Plains, NY); Michael Rizzolo (Albany, NY)
Assignee: International Business Machines Corporation
B60Q9/00B60W30/08B60W2540/22
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Quick Facts
Patent No.
US 9,758,095
App. No.
15/005,675
Granted
Sep 12, 2017
Kind
B2
Abstract

Techniques are provided for alerting drivers of hazardous driving conditions using the sensing capabilities of wearable mobile technology. In one aspect, a method for alerting drivers of hazardous driving conditions includes the steps of: collecting real-time data from a driver of a vehicle, wherein the data is collected via a mobile device worn by the driver; determining whether the real-time data indicates that a hazardous driving condition exists; providing feedback to the driver if the real-time data indicates that a hazardous driving condition exists, and continuing to collect data from the driver in real-time if the real-time data indicates that a hazardous driving condition does not exist. The real-time data may also be collected and used to learn characteristics of the driver. These characteristics can be compared with the data being collected to help determine, in real-time, whether the driving behavior is normal and whether a hazardous driving condition exists.

Claims (29)

1. A method for alerting drivers of hazardous driving conditions, the method comprising the steps of:

collecting real-time data from a driver of a vehicle, wherein the data is collected via a mobile device worn by the driver;

determining whether the real-time data indicates that a hazardous driving condition exists;

providing feedback to the driver if the real-time data indicates that the hazardous driving condition exists;

continuing to collect data from the driver in real-time if the real-time data indicates that the hazardous driving does not exist,

wherein the method further comprises the steps of:

detecting hand deviations of the driver using the real-time data;

determining whether the hand deviations of the driver involve side-to-side hand movements;

estimating speed of the vehicle using the real-time data if the hand deviations of the driver involve side-to-side hand movements;

continuing to collect data from the driver in real-time if the hand deviations of the driver do not involve side-to-side hand movements;

determining whether the speed of the vehicle is higher than an average speed for a roadway on which the vehicle is travelling;

providing the feedback to the driver if the speed of the vehicle is higher than the average speed for the roadway on which the vehicle is travelling; and

continuing to collect data from the driver in real-time if the speed of the vehicle is not higher than an average speed for a roadway on which the vehicle is travelling.

2. The method of claim 1 , further comprising the step of:

using the real-time data to learn characteristics of the driver.

3. The method of claim 2 , further comprising the step of:

comparing the real-time data to the characteristics of the driver to determine whether the real-time data indicates that the hazardous driving condition exists.

4. The method of claim 1 , wherein the feedback is provided to the driver via the mobile device worn by the driver.

5. The method of claim 4 , wherein the feedback is provided as an audible alert message to the driver via the mobile device worn by the driver.

6. The method of claim 1 , wherein the feedback is provided as an audible alert message to the driver via an audio system of the vehicle.

7. The method of claim 1 , further comprising the step of:

tracking feedback provided to the driver.

8. The method of claim 1 , wherein the real-time data collected from the user comprises physiological data for the user selected from the group consisting of: skin electrical characteristics, blood oxygen levels, heart rate, pulse, and combinations thereof.

9. The method of claim 1 , wherein the real-time data collected from the user comprises trajectory data for the user selected from the group consisting of: movement, speed, direction, orientation, location, and combinations thereof.

10. The method of claim 1 , wherein the real-time data collected from the user comprises environmental data selected from the group consisting of: air pressure, temperature, wind velocity, and combinations thereof.

11. The method of claim 1 , wherein the mobile device worn by the user comprises at least one sensor selected from the group consisting of: an electrodermal activity (EDA) sensor, a pulse oximeter sensor, a heart rate sensor, and combinations thereof.

12. The method of claim 1 , wherein the mobile device worn by the user comprises at least one sensor selected from the group consisting of: a gyroscope sensor, a global positioning system (GPS) sensor, and combinations thereof.

13. The method of claim 1 , wherein the mobile device worn by the user comprises at least one sensor selected from the group consisting of: a barometer, an air temperature sensor, a wind speed sensor, and combinations thereof.

14. The method of claim 1 , wherein the mobile device worn by the user comprises a smartwatch.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 25, 2016
From: BRIGGS, BENJAMIN D.; CLEVENGER, LAWRENCE A.; CLEVENGER, LEIGH ANNE H.; CONNELL, JONATHAN H., II; RATHA, NALINI K.; RIZZOLO, MICHAEL
To: INTERNATIONAL BUSINESS MACHINES CORPORATION
Reel/Frame 037575/0747 →
Continuity (1)
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