IP Library Patent Application 13665005
Patent Application
App. No. 13/665,005

SYSTEM AND METHOD FOR PEER COMPARISON OF VEHICLES AND VEHICLE FLEETS

Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US None
App. No.
13/665,005
Abstract

A computer system and method for in at least one computer and a computer readable storage medium or media including computer code: receiving GPS event data transmitted from a plurality of GPS devices, each GPS device associated with a vehicle; storing in GPS event database operatively coupled to at least one of the processors, the GPS event data and peer comparison data; analyzing the GPS event data to derive a plurality of operational metrics for a plurality of the vehicles; determining if the GPS data for a statistically significant number of vehicles meets a credibility criterion for a peer comparison; and identifying at least one trend for the operational metrics for a GPS event history using the GPS event data, the at least one trend including a trend for peer comparison. The peer criterion can include a criterion defined by at least one of a geographical area and an industrial segment.

Claims (127)

1 . A computer system including at least one computer processor and computer readable storage medium or media including computer code and at least one storage device in which is stored GPS data for a plurality of vehicles the system comprising:

a memory including

a GPS event database including

GPS event data transmitted from a plurality of GPS devices, each GPS device associated with a vehicle, and stored over a period of time, and

a peer comparison database including peer comparison data associated with the vehicles;

a credibility criterion;

the one or more processors programmed at least to

receive GPS event data transmitted from a plurality of GPS devices, each GPS device associated with a vehicle, the event GPS event data including location information for the vehicle;

store the GPS event data in the GPS event database operatively coupled to at least one of the processors;

analyze the GPS event data to derive a plurality of operational metrics for a plurality of the vehicles; and

identify at least one trend for the operational metrics for a GPS event history using the GPS event data, the at least one trend including a trend for peer comparison.

2 . The computer system of claim 1 , wherein the one or more processors are further programmed at least to:

provide, for a graphic user interface, a representation including a representation of the peer comparison for at least one operational metric.

3 . The computer system of claim 1 , wherein the one or more processors are further programmed at least to:

identify a trend for an operational metric for the plurality of vehicles, the operational metric including an operational metric selected from the group of: engine on/off, vehicle mileage, idling, speed, performance against a criterion, employee performance; driver behavior; industry segment performance, geographical area performance, and fleet performance.

4 . The computer system of claim 1 , wherein the operational metric includes an average operational metric.

5 . The computer system of claim 4 , wherein the average operational metric includes an average per day per vehicle metric.

6 . The computer system of claim 1 , wherein the peer comparison data comprises:

geographic data associated with the vehicles; and

industrial data associated with the vehicles.

7 . The computer system of claim 1 , wherein the memory comprises:

wherein the criterion includes a threshold credibility criterion.

8 . The computer system of claim 7 , wherein the memory comprises:

wherein the criterion includes a maintenance credibility criterion.

9 . The computer system of claim 1 , wherein the memory comprises:

a filter criterion.

10 . The computer system of claim 9 , wherein the memory comprises:

the filter criterion includes an outlier exclusion.

11 . The computer system of claim 1 , wherein the one or more processors are further programmed to:

create a periodic record of the GPS event data stored for the vehicle;

determine a bounding area associated with the periodic record of the GPS event data for the vehicle;

identify a geographical area associated with the bounding area.

12 . The computer system of claim 11 , wherein the one or more processors are further programmed to:

link an industry segment identifier associated with the vehicle to the periodic record;

process a plurality of the periodic records to determine if a number of vehicles meets the credibility criterion for a peer comparison analysis.

13 . The computer system of claim 12 , wherein the one or more processors are further programmed to:

filter any periodic records meeting a filter criterion.

14 . The computer system of claim 13 , wherein the one or more processors are further programmed at least to:

identify the at least one trend for a peer comparison for the operational metric from the periodic records.

15 . The computer system of claim 1 , wherein the peer comparison includes a peer comparison metric.

16 . The computer system of claim 15 , wherein the system is configured to make the selection of a peer comparison metric a function of a prior selected peer comparison metric.

17 . The computer system of claim 15 , wherein the peer comparison metric includes a peer comparison parameter selected from the group consisting essentially of a geographical parameter and an industrial parameter.

18 . The computer system of claim 1 , wherein the representation of the peer comparison includes a graphic representation selected from the group of a ranking graphic and a trending graphic.

19 . The computer system of claim 1 , wherein the one or more processors are further programmed at least to:

identify an average operational metric for a plurality of the vehicles over a period of time.

20 . The computer system of claim 2 , wherein the one or more processors axe further programmed at least to:

provide, for the graphic user interface, a comparison the GPS event history for at a plurality of vehicles in a fleet using the GPS event data against GPS event history for at a plurality of vehicles for a peer comparison metric.

21 . The computer system of claim 2 , wherein the one or more processors are further programmed at least to:

analyze the GPS event history for at least one driver's performance for at least one operational metric; and

provide, for the graphic user interface, a comparison of the driver's performance against the peer comparison metric.

22 . A computer system including at least one computer processor and computer readable storage medium or media including computer code and at least one storage device in which is stored GPS data for a plurality of vehicles the system comprising:

a memory including

a GPS event database including

GPS event data transmitted from a plurality of GPS devices, each GPS device associated with a vehicle, and stored over a period of time, and

peer comparison data associated with the vehicles;

a credibility criterion;

a filter criterion;

the one or more processors programmed at least to

receive GPS event data transmitted from a plurality of GPS devices, each GPS device associated with a vehicle, the event GPS event data including location information for the vehicle;

store the GPS event data in the GPS event database operatively coupled to at least one of the processors;

create a periodic record of the GPS event data stored for the vehicle;

determine a bounding area associated periodic record of the GPS event data for the vehicle;

identify a geographical area associated with the bounding area;

link an industry segment identifier associated with the vehicle to the periodic record;

process a plurality of the periodic records to determine if a number of vehicles meets the credibility criterion for a peer comparison analysis;

filter any periodic records meeting a filter criterion;

analyze the GPS event data to derive a plurality of operational metrics for a plurality of the vehicles; and

identify at least one trend for the operational metrics for a GPS event history using the GPS event data, the at least one trend including a trend for peer comparison; and provide, for a graphic user interface, a representation including a representation of the peer comparison for at least one operational metric.

23 . A method comprising, in at least one computer and a computer readable storage medium or media including computer code:

receiving GPS event data transmitted from a plurality of GPS devices, each GPS device associated with a vehicle;

storing in GPS event database operatively coupled to at least one of the processors, the GPS event data and peer comparison data;

analyzing the GPS event data to derive a plurality of operational metrics for a plurality of the vehicles;

determining if the GPS data for a statistically significant number of vehicles meets a credibility criterion for a peer comparison; and

identifying at least one trend for the operational metrics for a GPS event history using the GPS event data, the at least one trend including a trend for peer comparison.

24 . The method of claim 23 wherein method further comprises:

providing, for a graphic user interface, a representation including a representation of the at least one trend.

25 . The method of claim 23 wherein method further comprises:

identifying a trend for an operational metric for the plurality of vehicles, the operational metric including an operational metric selected from the group of: engine on/off, vehicle mileage, idling, speed, performance against a criterion, employee performance;

driver behavior; industry segment performance, geographical area performance, and fleet performance.

26 . The method of claim 23 wherein the operational metric includes an average operational metric.

27 . method of claim 26 wherein the average operational metric includes an average per day per vehicle metric

28 . The method claim 23 , wherein the peer comparison data comprises:

geographic data associated with the vehicles; and

industrial data associated with the vehicles.

29 . The method claim 23 , wherein the method further comprises:

determining if the GPS data for a statistically significant number of vehicles meets a threshold credibility criterion.

30 . The method claim 29 , wherein the method further comprises:

determining if the GPS data for a statistically significant number of vehicles meets maintenance credibility criterion once the threshold credibility criterion is met.

31 . The method claim 23 , wherein the method comprises:

filtering out the GPS data from the a statistically significant number of vehicle based on a filter criterion.

32 . The method claim 31 , wherein the filter criterion includes an outlier exclusion.

33 . The method of claim 23 wherein method further comprises:

creating a periodic record of the GPS event data stored for the vehicle;

determining a bounding area associated with the periodic record of the GPS event data for the vehicle;

identifying a geographical area associated with the bounding area.

34 . The method of claim 33 wherein method further comprises:

linking an industry segment identifier associated with the vehicle to the periodic record;

processing a plurality of the periodic records to determine if a number of vehicles meets the credibility criterion for a peer comparison analysis.

35 . The method of claim 34 , wherein method further comprises:

filtering any periodic records meeting a filter criterion.

36 . The method of claim 34 wherein method further comprises:

identifying the at least one trend for a peer comparison for the operational metric from the periodic records.

37 . The method claim 23 wherein the peer comparison includes a peer comparison metric.

38 . The method claim 27 , further comprising:

configuring the computer to make selection of a peer comparison metric a function of a prior selected peer comparison metric.

39 . The method claim 37 wherein the peer comparison metric includes a peer comparison parameter selected from the group consisting essentially of a geographical parameter and an industrial parameter.

40 . The method claim 24 wherein the method further comprises

providing the graphic representation of the peer comparison, wherein the graphic includes a graphic representation selected from the group of a ranking graphic and a trending graphic.

41 . The method claim 23 wherein the method further comprises

identifying an average operational metric for a plurality of the vehicles over a period of time.

42 . The method claim 24 wherein the method further comprises:

providing, for the graphic user interface, a comparison the GPS event history for at a plurality of vehicles in a fleet using the GPS event data against GPS event history for at a plurality of vehicles for a peer comparison metric.

43 . The method claim 24 wherein the method further comprises:

analyzing the GPS event history for at least one driver's performance for at least one operational metric; and

providing, for the graphic user interface, a comparison of the driver's performance against the peer comparison metric.

44 . The method claim 25 wherein the method further comprises:

providing, for a graphic user interface, a graphic representation of the trend, the trend including a trend showing performance against an benchmark derived from the peer comparison data.

45 . The method of claim 44 wherein method further comprises:

comparing the GPS event history for at least one vehicle using the GPS event data against industry data;

providing, for the graphic user interface, the representation of the trend, the trend including a trend showing performance against the benchmark.

46 . A method comprising, in at least one computer and a computer readable storage medium or media including computer code:

establishing a criterion for gathering data for a statistically significant number of vehicles;

acquiring GPS vehicle data for a statistically significant number of vehicles for a peer comparison criterion;

periodically processing the GPS vehicle data; and

presenting the processed data for a trending analysis based on the GPS data from the statistically significant number of vehicles.

47 . The method of claim 33 , further comprising:

wherein the peer criterion includes at criterion defined by at least one of a geographical area and an industrial segment.

Assignments (7)
CHANGE OF NAME Recorded Apr 13, 2021
From: VERIZON CONNECT IRELAND LIMITED
To: VERIZON CONNECT DEVELOPMENT LIMITED
Reel/Frame 055911/0506 →
CHANGE OF NAME Recorded Apr 11, 2018
From: FLEETMATICS IRELAND LIMITED
To: VERIZON CONNECT IRELAND LIMITED
Reel/Frame 045509/0801 →
MERGER Recorded Jan 17, 2017
From: FLEETMATICS DEVELOPMENT LIMITED
To: FLEETMATICS IRELAND LIMITED
Reel/Frame 041535/0084 →
RELEASE OF SECURITY INTEREST Recorded Oct 25, 2016
From: CITIBANK, N.A., AS ADMINISTRATIVE AGENT
To: FLEETMATICS DEVELOPMENT LIMITED
Reel/Frame 040118/0119 →
SECURITY INTEREST Recorded Jan 30, 2015
From: FLEETMATICS DEVELOPMENT LIMITED
To: CITIBANK, N.A., AS ADMINISTRATIVE AGENT
Reel/Frame 034852/0700 →
CHANGE OF NAME Recorded Jan 30, 2015
From: FLEETMATICS IRL LIMITED
To: FLEETMATICS DEVELOPMENT LIMITED
Reel/Frame 034852/0406 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Mar 28, 2013
From: MITCHELL, PETER
To: FLEETMATICS IRL LIMITED
Reel/Frame 030105/0367 →