IP Library Granted Patent US 11,607,144
Granted Patent B2
US 11,607,144 · App. 15/382,763 · Granted Mar 21, 2023

Sensor based context management

Inventors: Timo Eriksson (Vantaa, FI); Mikko Martikka (Vantaa, FI); Erik Lindman (Vantaa, FI)
Assignee: Suunto Oy
A61B5/0245A61B5/0006A61B5/0022A61B5/02438A61B5/1118A61B5/352A61B5/681G01C22/006G01P15/0802G06V40/23G16H40/67A61B5/7275A61B2503/10
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Quick Facts
Patent No.
US 11,607,144
App. No.
15/382,763
Granted
Mar 21, 2023
Kind
B2
Abstract

According to an example aspect of the present invention, there is provided an apparatus comprising a memory configured to store first-type sensor data, at least one processing core configured to compile a message based at least partly on the first-type sensor data, to cause the message to be transmitted from the apparatus, to cause receiving in the apparatus of a machine readable instruction, and to derive an estimated activity type, using the machine readable instruction, based at least partly on sensor data

Claims (51)

1. A mobile user device comprising:

a memory configured to store first-type sensor data obtained during an activity session; and

at least one processing core configured to compile a message based at least partly on the first-type sensor data, to cause the message to be transmitted from the mobile user device to a server external to the mobile user device, to cause receiving, responsive to the message, in the mobile user device, from the server, of a machine readable instruction configured to differentiate an activity type in either an indoor or an outdoor activity context and comprising an executable program or an executable script, and to derive an estimated activity type, using the executable program or the executable script, based at least partly on sensor data, for the activity session which is ongoing or ended, wherein the activity type is selected from: rowing, paddling, cycling, jogging, walking, hunting, swimming, paragliding, orienteering, and running.

2. The mobile user device according to claim 1 , wherein the machine readable instruction comprises a set of at least two machine-readable characteristics, wherein each of the machine-readable characteristics characterizes sensor data produced during a predefined activity type.

3. The mobile user device according to claim 1 , wherein the at least one processing core is configured to derive the estimated activity type at least in part by comparing, using the executable program or the executable script, the first-type sensor data, or a processed form of the first-type sensor data, to reference data.

4. The mobile user device according to claim 1 , wherein the first-type sensor data comprises acceleration sensor data.

5. The mobile user device according to claim 1 , wherein the memory is further configured to store second-type sensor data, and wherein the at least one processing core is configured to derive the estimated activity type, using the executable program or the executable script, based at least in part on the second-type sensor data.

6. The mobile user device according to claim 4 , wherein the second-type sensor data is of a different type than the first-type sensor data.

7. The mobile user device according to claim 5 , wherein the second-type sensor data comprises at least one of: sound sensor data, microphone-derived data and vibration sensor data.

8. The mobile user device according to claim 5 , wherein the at least one processing core is configured to derive the estimated activity type at least in part by comparing the second-type sensor data, or a processed form of the second-type sensor data, to reference data, the reference data comprising reference data of a first type and a second type.

9. The mobile user device according to claim 1 , wherein the at least one processing core is configured to present the estimated activity type to a user for verification.

10. The mobile user device according to claim 1 , wherein the at least one processing core is configured to cause the memory to store, in a sequence of estimated activity types, the estimated activity type and a second estimated activity type.

11. The mobile user device according to claim 1 , wherein the at least one processing core is configured to cause the memory to delete the machine readable instruction responsive to a determination that an activity session has ended.

12. A server apparatus comprising at least one processing core, at least one memory including computer program code, the at least one memory and the computer program code being configured to, with the at least one processing core, cause the server apparatus at least to:

receive a message from a mobile user device external to the server apparatus, the message comprising information characterizing first-type sensor data obtained during an activity session;

determine, based at least partly on the first-type sensor data, an indoor or outdoor activity context, and

transmit, responsive to the message, to the mobile user device a machine-readable instruction configured to cause activity type determination in the determined indoor or outdoor activity context, wherein the machine readable instruction comprises an executable program or an executable script, wherein the activity type is selected from: rowing, paddling, cycling, jogging, walking, hunting, swimming, paragliding, orienteering, and running.

13. A method, comprising:

storing first-type sensor data obtained during an activity session in a mobile user device;

compiling a message based at least partly on the first-type sensor data;

causing the message to be transmitted from the mobile user device to a server external to the mobile user device;

causing receiving, responsive to the message, in the mobile user device, from the server, of a machine readable instruction configured to differentiate activity type in either an indoor or an outdoor activity context and comprising an executable program or an executable script, and

deriving an estimated activity type, using the executable program or the executable script, based at least partly on sensor data, for the activity session which is ongoing or ended, wherein the activity type is selected from: rowing, paddling, cycling, jogging, walking, hunting, swimming, paragliding, orienteering, and running.

14. The method according to claim 13 , wherein the machine readable instruction comprises a set of at least two machine-readable characteristics, wherein each of the machine-readable characteristics characterizes sensor data produced during a predefined activity type.

15. The method according to claim 13 , estimated activity type is derived at least in part by comparing, using the executable program or the executable script, the first-type sensor data, or a processed form of the first-type sensor data, to reference data.

16. The method according to claim 13 , wherein the first-type sensor data comprises acceleration sensor data.

17. The method according to claim 13 , further comprising storing second-type sensor data and wherein the estimated activity type is derived, using the executable program or the executable script, based at least in part on the second-type sensor data.

18. The method according to claim 17 , wherein the second-type sensor data is of a different type than the first-type sensor data.

19. The method according to claim 17 , wherein the second-type sensor data comprises at least one of: sound sensor data, microphone-derived data and vibration sensor data.

20. The method according to claim 17 , wherein the estimated activity type is derived at least in part by comparing the second-type sensor data, or a processed form of the second-type sensor data, to reference data, the reference data comprising reference data of a first type and a second type.

21. The method according to claim 13 , further comprising presenting the estimated activity type to a user for verification.

22. The method according to claim 13 , further comprising storing, in a sequence of estimated activity types, the estimated activity type and a second estimated activity type.

23. A non-transitory computer readable medium having stored thereon a set of computer readable instructions that, when executed by at least one processor, cause a mobile user device to at least:

store first-type sensor data obtained during an activity session;

compile a message based at least partly on the first-type sensor data;

cause the message to be transmitted from the mobile user device to a server external to the mobile user device;

cause receiving, responsive to the message, in the mobile user device, from the server, of a machine readable instruction configured to differentiate activity type in either an indoor or an outdoor activity context comprising an executable program or an executable script, and

derive an estimated activity type, using the executable program or the executable script, based at least partly on sensor data, for the activity session which is ongoing or ended, wherein the activity type is selected from: rowing, paddling, cycling, jogging, walking, hunting, swimming, paragliding, orienteering, and running.

24. A mobile user device for identification of user activity comprising:

a memory configured to store first-type sensor data relating to an activity session;

at least one processing core configured to:

compile a message based at least partly on the first-type sensor data,

cause the message to be transmitted from the mobile user device to a server external to the mobile user device,

cause receiving in the mobile user device from the server a response to the message as a machine readable instruction configured to differentiate activity type in either an indoor or an outdoor activity context and comprising at least two machine-readable characteristics, wherein each of the at least two machine-readable characteristics characterizes sensor data produced during a predefined activity type, the at least two machine-readable characteristics comprising reference data specific to a context where the mobile user device is operating, and

derive an estimated activity type, using the reference data specific to the context, based at least partly on sensor data by comparing the sensor data to the reference data specific to the context, for the activity session which is ongoing or ended, wherein the activity type is selected from: rowing, paddling, cycling, jogging, walking, hunting, swimming, paragliding, orienteering, and running.

25. A non-transitory computer readable medium having stored thereon a set of computer readable instructions that, when executed by at least one processor, cause a mobile user device to at least:

store first-type sensor data relating to an activity session;

compile a message based at least partly on the first-type sensor data,

cause the message to be transmitted from the mobile user device to a server external to the mobile user device,

cause receiving in the mobile user device from the server a response to the message as a machine readable instruction configured to differentiate activity type in either an indoor or an outdoor activity context and comprising at least two machine-readable characteristics, wherein each of the at least two machine-readable characteristics characterizes sensor data produced during a predefined activity type, the at least two machine-readable characteristics comprising reference data specific to a context where the mobile user device is operating, and

derive an estimated activity type, using the reference data specific to the context, based at least partly on sensor data by comparing the sensor data to the reference data specific to the context, for the activity session which is ongoing or ended, wherein the activity type is selected from: rowing, paddling, cycling, jogging, walking, hunting, swimming, paragliding, orienteering, and running.

Assignments (3)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 3, 2022
From: AMER SPORTS DIGITAL SERVICES OY
To: SUUNTO OY
Reel/Frame 059847/0281 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 15, 2017
From: SUUNTO OY
To: AMER SPORTS DIGITAL SERVICES OY
Reel/Frame 044130/0477 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Mar 16, 2017
From: ERIKSSON, TIMO; MARTIKKA, MIKKO; LINDMAN, ERIK
To: SUUNTO OY
Reel/Frame 042021/0884 →
Continuity (1)
Related Publication 20170176213A1 · Jun 22, 2017