MODE OF TRANSPORT DETERMINATION

• US 20100292921A1
• Filed: 06/13/2008
• Published: 11/18/2010
• Est. Priority Date: 06/13/2007
• Status: Abandoned Application

• Current Assignee: Carbon Zero Limited
• Original Assignee: Carbon Zero Limited
• Inventors: Burch, Nicholas, Zachariah, Andreas
• Application Number:
  US12/664,215
• Publication Number:
  US 20100292921A1
• Time in Patent Office: Days
• US Class Current: 701/209
• CPC Class Codes: G06Q 10/00 Administration; Management
• CPC Class Codes: G06Q 50/30 Transportation; Communications
• CPC Class Codes: G06Q 50/40 Business processes related to the transportation industry shipping G06Q10/083

Abstract

A method of determining a mode of transport for a portion of a user'"'"'s journey is described. The method comprises: receiving, at a portable device being carried by a user, position data for current locations of the user over a period of time; determining, from the position data, a characteristic of the speed for the journey portion; identifying possible modes of transport on the basis of pre-established ranges of speed characteristics for particular modes of transport; and selecting a most likely mode of transport from the identified possible modes of transport based on the proximity of the user'"'"'s position data to known public transport nodes. The method can also be used to determine the carbon footprint of a user using a portable device.

Claims

1. A processor-implemented method of determining a mode of transport for a portion of a users journey, the method comprising:

receiving, at a portable device being carried by a user, position data for current locations of the user over a period of time;

determining, from the position data a characteristic of the speed for the journey portion;

identifying possible modes of transport on the basis of pre-established ranges of speed characteristics for particular modes of transport; and

selecting a most likely mode of transport from the identified possible modes of transport based on the proximity of the user'"'"'s position data to known public transport nodes.

2. The processor-implemented method of claim 1, wherein the selecting step comprises:

querying a database of location data for known public transport nodes each having an associated proximity,

identifying any public transport nodes within the associated proximity of the user'"'"'s position data; and

storing the identified nodes in a travel status log.

3. The processor-implemented method of claim 2, wherein the known public transport nodes are categorised by type of public transport, and the associated proximity of each node depends on the category of public transport associated with that node.

4. The processor-implemented method of claim 1, further comprising:

identifying event-related data from the received position data, the determined characteristic of speed, and/or the identified public transport nodes;

the event-related data comprising a transport difference characteristic which can be used to distinguish between different modes of transport;

storing the event-related data; and

using the event-related data to modify the most likely mode of transport as determined from the results of the selecting step.

5. The processor-implemented method of claim 4, wherein the using step comprises using rules-based logic to eliminate certain possible modes of transport on the basis of the event-related data, wherein each logic rule defines a particular characteristic of one or more modes of transport.

6. The processor-implemented method of claim 4, wherein:

the event-related data is selected from the group comprising;

individual journey legs, durations of position data signal loss, rate of change in direction of travel, and stationary moments; and

the using step comprises using the event-related data during the selecting step in order to assist in the accurate determination of the user'"'"'s mode of transport for a current journey leg.

7. The processor-implemented method of claim 4, wherein:

the event-related data is selected from the group comprising;

individual journey legs, durations of position data signal loss, rate of change in direction of travel, and stationary moments; and

the using step comprises using the event-related data to correct a previously determined mode of transport determined by the selecting step.

8. The processor-implemented method of claim 1, further comprising:

sensing an additional user device in the local vicinity of the user implementing the method of claim 1;

communicating with the additional user device to determine the additional user device'"'"'s current selected mode of transport; and

correcting the user'"'"'s selected mode of transport, if the position data for both the user and the additional user correlate with each other for a required time period, there is a difference between the selected modes of transport for the user and the additional user, and if the selected mode of transport established for the additional user, is deemed to be more reliable than the selected mode of transport for the user.

9. The processor-implemented method of claim 1, further comprising:

receiving additional sensor data; and

using the additional sensor data during the selecting step in order to enable more accurate determination of the user'"'"'s mode of transport for a journey leg.

10. The processor-implemented method of claim 1, further comprising:

receiving additional sensor data; and

using the additional sensor data to correct a previously determined mode of transport determined by the selecting step.

11. The processor-implemented method of claim 9, wherein the additional sensor data is data provided by a device selected from one of the group comprising:

a heart rate monitor, an accelerometer, wireless communication device, and a near field communications device.

12. The processor-implemented method of claim 1, further comprising identifying altitude and/or direction data, wherein the selecting step utilises the identified altitude and/or direction data.

13. The processor-implemented method of claim 9, wherein the using step comprises using rules-based logic to eliminate certain possible modes of transport on the basis of the additional sensor data or the direction/altitude data.

14. The processor-implemented method of claim 1, wherein the receiving step comprises receiving location data derived from received satellite positioning data or received mobile telecommunication triangulation positioning data.

15. The processor-implemented method of claim 1, further comprising:

presenting the determined mode of transport for a portion of the user'"'"'s journey, and

enabling the user to input a different mode of transport to override the selection if the portion of the user'"'"'s journey has been incorrectly determined.

16. The processor-implemented method of claim 15, wherein the presenting step is implemented on a display and the enabling step is effected through a haptic interface.

17. The method of claim 1, further comprising receiving user input data, via a graphical user interface of the portable device, wherein the user input data comprises personal user locations frequently visited by the user;

and

using the personal user locations during the selecting step in order to enable more accurate determination of the user'"'"'s mode of transport for a journey leg.

18. The processor-implemented method of claim 1, comprising

receiving user preference data, via the graphical user interface, the user preference data detailing features of a typical user journey:

and

using the user preference data during the selecting step in order to enable more accurate determination of the user'"'"'s mode of transport for a journey leg.

19. The processor-implemented method of claim 1, comprising:

specifying relationships between public transport nodes, the relationships being specified for nodes which are linked by a common mode of public transport having a route for that mode of transport connecting the nodes; and

using the specified relationships during the selecting step in order to enable more accurate determination of the user'"'"'s mode of transport for a journey leg.

21. A processor implemented method of determining a carbon footprint of a user, the method comprising:

a method of determining a mode of transport for a portion of a user'"'"'s journey according to any preceding claim;

calculating the environmental impact of each leg of the journey for each different type of mode of transport; and

presenting the results of the calculating step to the user.

22. The processor-implemented method of claim 21, wherein the presenting step comprises presenting the results graphically on a screen of the portable device.

23. The processor-implemented method of claim 21, wherein the presenting step comprises presenting the results in one of a plurality of different user-selected units, at least one of the plurality of different units being in a readily comprehendible unit of an everyday object, for example volume being expressed in the size of a bus.

24. The processor-implemented method of claim 21, further comprising finding an alternative route for a user journey which results in a lower overall environmental impact.

20. The processor-implemented method of, further comprising:

querying a database of location data for known public transport nodes each having an associated proximity;

identifying any public transport nodes within the associated proximity of the user'"'"'s position data;

storing the identified nodes in a travel status log;

predicting one or more likely next public transport nodes the user will be within the proximity of if the determined mode of transport is correct;

checking that an actual next identified public transport node is one of the one or more expected public transport nodes in order to verify a determined mode of transport is correct; and

correcting the determined mode of transport, if the next identified public transport node is not one of the one or more expected public transport nodes.

25. An apparatus for determining a mode of transport for a portion of a user'"'"'s journey, the apparatus comprising:

a portable device being carried by a user, the device incorporating receiving means for receiving position data for current locations of the user over a period of time;

a determining module arranged to determine from the position data, a characteristic of the speed for the journey portion;

an identifying module arranged to identify possible modes of transport on the basis of pre-established ranges of speed characteristics for particular modes of transport; and

a selecting module arranged to select a most likely mode of transport from the identified possible modes of transport based on the proximity of the user'"'"'s position data to known public transport nodes.

26. The apparatus of claim 25, wherein the determining module, identifying module and selecting module are also provided within the portable device.

27. The apparatus of claim 25, wherein the apparatus comprises a mobile telecommunications device.

28. The apparatus of claim 25, further comprising means for determining the environmental impact of the portion of the journey, and means for displaying the environmental impact to the user.

29. A processor-implemented method of recording a user'"'"'s air travel, the method comprising:

receiving, at a portable device being carried by a user, position data for current locations of the user over a period of time;

identifying, from the position data, whether the user is in the vicinity of an airport;

determining when a flight takes place;

inferring a measure for the distance of that flight; and

storing the determined distances of all of the flights the user takes in a travel status log.

30. The processor-implemented method of claim 29, wherein the determining step comprises:

monitoring whether the portable device is switched off in the vicinity of a first airport, and is subsequently turned on in the vicinity of a second airport;

calculating the speed at which the user traveled between the first and second airports; and

confirming the user traveled via an aircraft when the calculated speed is only possible via an aircraft.

31. The processor-implemented method of claim 30, wherein the inferring step comprises calculating a direct distance value for the distance between the first and second airports or using a route specific distance value retrieved from an air travel route database, the route specific distance value being attributed to a realistic flight plan for specific routes.