Automotive activity monitor

• US 9,779,557 B2
• Filed: 08/10/2016
• Issued: 10/03/2017
• Est. Priority Date: 08/18/2015
• Status: Active Grant

• Current Assignee: Carfit Corp.
• Original Assignee: Carfit Corp.
• Inventors: Hauser, Peter Edmund Heinrich, Olivier, Henri-Nicolas
• Primary Examiner(s): Pipala, Edward J
• Application Number:
  US15/233,840
• Publication Number:
  US 20170053460A1
• Time in Patent Office: 419 Days
• CPC Class Codes: B60W 50/00 Details of control systems for road vehicle drive control not related to the control of a particular sub-unit , e.g. process diagnostic or vehicle driver interfaces
• CPC Class Codes: G07C 2205/02 using a vehicle scan tool
• CPC Class Codes: G07C 5/008 communicating information to a remotely located station transmission systems for measured values G08C
• CPC Class Codes: G07C 5/04 using counting means or digital clocks
• CPC Class Codes: G07C 5/08 Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle or waiting time
• CPC Class Codes: G07C 5/0816 Indicating performance data, e.g. occurrence of a malfunction
• CPC Class Codes: G07C 5/0833 using audio means
• CPC Class Codes: H04L 67/12 specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks

Abstract

Embodiments are directed to monitoring vehicle operations. If sensor information based on sensor data captured by a sensor computer installed in a vehicle is provided to a server by a client computer. An analysis engine may compare the sensor information to vehicle models associated with the vehicle. One or more reports based on the comparison may be distributed registered subscribers. A modeling engine may be employed to update the vehicle models based on the sensor information. The one or more updated vehicle models may be communicated to one or more client computers that may be associated with one or more users. The sensor information may be obtained from the sensor computer. Sensor information may include metrics associated with the operation of the vehicle. Metrics may include timestamps, road shocks, straight line driving, harshness, acceleration, deceleration, trip length, travel speeds, or the like.

Claims

1. A method for monitoring vehicle operations, wherein one or more processors in a network computer execute instructions to perform actions, comprising:

providing sensor information based on sensor data captured by a sensor computer installed in a vehicle;

employing the provided sensor information to use the network computer to perform further actions, including;

storing the sensor information in a memory;

employing a local analysis engine to compare the sensor information to one or more vehicle models and one or more machine learning models that are based in part on one or more knowledge bases that include information from a plurality of other vehicles and determined habits of an operator of the vehicle, wherein the one or more vehicle models and the one or more machine learning models are updated with the information provided by the one or more knowledge bases and associated with the vehicle; and

providing one or more reports based on the comparison, wherein the one or more reports are distributed to one or more registered subscribers.

2. The method of claim 1, wherein the sensor computer is installed, to directly capture the sensor information, on one or more of a dashboard of the vehicle, the steering wheel of the vehicle, or a steering column of the vehicle.

3. The method of claim 1, further comprising:

employing a modeling engine to update the one or more vehicle models based in part on the sensor information; and

communicating the one or more updated vehicle models to one or more client computers associated with one or more users.

4. The method of claim 1, further comprising:

employing the sensor computer to capture sensor data during operation of the vehicle;

employing the sensor computer to compare the sensor data to one or more vehicle baselines models; and

based on the comparison indicating an anomaly, communicating the sensor information to a client computer operated by a user of the vehicle, wherein the sensor information is based in part on the sensor data captured by the sensor computer.

5. The method of claim 1, further comprising:

mapping one or more portions of the signal information to one or more trouble codes, wherein the one or more trouble codes are associated with one or more vehicle systems that generate vibrations, including one or more of tires, wheels, alignment, suspension, engine, electric motor, or brakes.

6. The method of claim 1, wherein the sensor information, further comprises, one or more metrics associated with the current operation of the vehicle, wherein the metrics include one or more of, timestamps, road shocks, straight line driving, harshness, acceleration, deceleration, trip length, hard starts, hard stops, accidents, highway driving, city driving, being stopped, enroute, or travel speeds.

7. The method of claim 1, further comprising, employing a natural language engine to provide one or more response actions based on one or more chat inputs from one or more users of the vehicle.

8. The method of claim 1, further comprising:

collecting vehicle information from one or more data sources;

providing one or more intents that are associated with one or more responses; and

updating a natural language engine to use the one or more intents and the one or more associated responses.

9. A system for monitoring vehicle operations comprising:

a network computer, comprising;

a transceiver that communicates over a network;

a memory that stores at least instructions; and

one or more processors that execute instructions that perform actions, including;

when sensor information based on sensor data captured by a sensor computer installed in a vehicle is provided, performing further actions, including;

storing the sensor information in a memory;

employing a local analysis engine to compare the sensor information to one or more vehicle models and one or more machine learning models that are based in part on one or more knowledge bases that include information from a plurality of other vehicles and determined habits of an operator of the vehicle, wherein the one or more vehicle models and the one or more machine learning models are updated with the information provided by the one or more knowledge bases and associated with the vehicle; and

providing one or more reports based on the comparison, wherein the one or more reports are distributed to one or more registered subscribers; and

a client computer, comprising,

a transceiver that communicates over the network;

a memory that stores at least instructions; and

one or more processors that execute instructions that perform actions, including;

obtaining the sensor information from the sensor computer; and

providing the sensor information to the network computer; and

the sensor computer, comprising;

a transceiver that communicates over the network with the client computer;

a memory that stores at least instructions;

one or more processors that execute instructions that perform actions, including;

capturing sensor data.

10. The system of claim 9, wherein the sensor computer is installed, to directly capture the sensor information, on one or more of a dashboard of the vehicle, the steering wheel of the vehicle, or a steering column of the vehicle.

11. The system of claim 9, wherein the network computer performs actions, further comprising:

employing a modeling engine to update the one or more vehicle models based in part on the sensor information; and

communicating the one or more updated vehicle models to one or more client computers associated with one or more users.

12. The system of claim 9, further comprising:

employing the sensor computer to capture sensor data during operation of the vehicle;

employing the sensor computer to compare the sensor data to one or more vehicle baselines models; and

when the comparison indicates an anomaly, communicating the sensor information to a client computer operated by a user of the vehicle, wherein the sensor information is based in part on the sensor data captured by the sensor computer.

13. The system of claim 9, further comprising:

mapping one or more portions of the signal information to one or more trouble codes, wherein the one or more trouble codes are associated with one or more vehicle systems that generate vibrations, including one or more of tires, wheels, alignment, suspension, engine, electric motor, or brakes.

14. The system of claim 9, wherein the sensor information, further comprises, one or more metrics associated with the current operation of the vehicle, wherein the metrics include one or more of, timestamps, road shocks, straight line driving, harshness, acceleration, deceleration, trip length, hard starts, hard stops, accidents, highway driving, city driving, being stopped, enroute, or travel speeds.

15. The system of claim 9, further comprising, employing a natural language engine to provide one or more response actions based on one or more chat inputs from one or more users of the vehicle.

16. The system of claim 9, wherein the network computer performs actions, further comprising:

collecting vehicle information from one or more data sources;

providing one or more intents that are associated with one or more responses; and

updating a natural language engine to use the one or more intents and the one or more associated responses.

17. A network computer for monitoring vehicle operations, comprising:

a transceiver that communicates over a network;

a memory that stores at least instructions; and

one or more processors that execute instructions that perform actions, including;

when sensor information based on sensor data captured by a sensor computer installed in a vehicle is provided, performing further actions, including;

storing the sensor information in a memory;

employing a local analysis engine to compare the sensor information to one or more vehicle models and one or more machine learning models that are based in part on one or more knowledge bases that include information from a plurality of other vehicles and determined habits of an operator of the vehicle, wherein the one or more vehicle models and the one or more machine learning models are updated with the information provided by the one or more knowledge bases and associated with the vehicle; and

providing one or more reports based on the comparison, wherein the one or more reports are distributed to one or more registered subscribers.

18. The network computer of claim 17, wherein the sensor computer is installed, to directly capture the sensor information, on one or more of a dashboard of the vehicle, the steering wheel of the vehicle, or a steering column of the vehicle.

19. The network computer of claim 17, further comprising:

employing a modeling engine to update the one or more vehicle models based in part on the sensor information; and

communicating the one or more updated vehicle models to one or more client computers associated with one or more users.

20. The network computer of claim 17, further comprising:

employing the sensor computer to capture sensor data during operation of the vehicle;

employing the sensor computer to compare the sensor data to one or more vehicle baselines models; and

when the comparison indicates an anomaly, communicating the sensor information to a client computer operated by a user of the vehicle, wherein the sensor information is based in part on the sensor data captured by the sensor computer.

21. The network computer of claim 17, further comprising:

mapping one or more portions of the signal information to one or more trouble codes, wherein the one or more trouble codes are associated with one or more vehicle systems that generate vibrations, including one or more of tires, wheels, alignment, suspension, engine, electric motor, or brakes.

22. The network computer of claim 17, wherein the sensor information, further comprises, one or more metrics associated with the current operation of the vehicle, wherein the metrics include one or more of, timestamps, road shocks, straight line driving, harshness, acceleration, deceleration, trip length, hard starts, hard stops, accidents, highway driving, city driving, being stopped, enroute, or travel speeds.

23. The network computer of claim 17, further comprising, employing a natural language engine to provide one or more response actions based on one or more chat inputs from one or more users of the vehicle.

24. A processor readable non-transitory storage media that includes instructions for monitoring vehicle operations, wherein execution of the instructions by one or more processors performs actions, comprising:

when sensor information based on sensor data captured by a sensor computer installed in a vehicle is provided, employing a network computer to perform further actions, including;

storing the sensor information in a memory;

employing a local analysis engine to compare the sensor information to one or more vehicle models and one or more machine learning models that are based in part on one or more knowledge bases that include information from a plurality of other vehicles and determined habits of an operator of the vehicle, wherein the one or more vehicle models and the one or more machine learning models are updated with the information provided by the one or more knowledge bases and associated with the vehicle; and

providing one or more reports based on the comparison, wherein the one or more reports are distributed to one or more registered subscribers.

25. The media of claim 24, wherein the sensor computer is installed, to directly capture the sensor information, on one or more of a dashboard of the vehicle, the steering wheel of the vehicle, or a steering column of the vehicle.

26. The media of claim 24, further comprising:

employing a modeling engine to update the one or more vehicle models based in part on the sensor information; and

communicating the one or more updated vehicle models to one or more client computers associated with one or more users.

27. The media of claim 24, further comprising:

employing the sensor computer to capture sensor data during operation of the vehicle;

employing the sensor computer to compare the sensor data to one or more vehicle baselines models; and

when the comparison indicates an anomaly, communicating the sensor information to a client computer operated by a user of the vehicle, wherein the sensor information is based in part on the sensor data captured by the sensor computer.

28. The media of claim 24, further comprising:

mapping one or more portions of the signal information to one or more trouble codes, wherein the one or more trouble codes are associated with one or more vehicle systems that generate vibrations, including one or more of tires, wheels, alignment, suspension, engine, electric motor, or brakes.

29. The media of claim 24, wherein the sensor information, further comprises, one or more metrics associated with the current operation of the vehicle, wherein the metrics include one or more of, timestamps, road shocks, straight line driving, harshness, acceleration, deceleration, trip length, hard starts, hard stops, accidents, highway driving, city driving, being stopped, enroute, or travel speeds.

30. The media of claim 24, further comprising, employing a natural language engine to provide one or more response actions based on one or more chat inputs from one or more users of the vehicle.