METHOD AND SENSOR NETWORK FOR ATTRIBUTE SELECTION FOR AN EVENT RECOGNITION

• US 20120036242A1
• Filed: 01/27/2010
• Published: 02/09/2012
• Est. Priority Date: 01/27/2009
• Status: Abandoned Application

• Current Assignee: Freie Universitaet Berlin
• Original Assignee: Freie Universitaet Berlin
• Inventors: Wittenburg, Georg, Dziengel, Norman, Wartenburger, Christian
• Application Number:
  US13/146,623
• Publication Number:
  US 20120036242A1
• Time in Patent Office: Days
• US Class Current: 709/222
• 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

A method for attribute selection for an event recognition in sensor networks is provided. The method comprising the following steps: in a configuration phase providing a quantity of attributes by sensor nodes of a sensor network, which characterize an event to be recognized, together with information on the topological origin of the attributes within the sensor network, and selecting a sub-quantity from the quantity of attributes, wherein the selection is made in consideration of the information on the topological origin of the attributes, and in an execution phase performing an event recognition for an event to be currently recognized on the basis of attributes which belong to a selected sub-quantity.

Claims

1-24. -24. (canceled)

25. A method for attribute selection for an event recognition in sensor networks, with the following steps:

in a configuration phase,

providing a quantity of attributes by sensor nodes of a sensor network, which characterize an event to be recognized, together with information on the topological origin of the attributes within the sensor network, and

selecting a sub-quantity from the quantity of attributes, wherein the selection is made in consideration of the information on the topological origin of the attributes,

in an execution phase,

performing an event recognition for an event to be currently recognized on the basis of attributes which belong to a selected sub-quantity.

26. The method according to claim 25, wherein selecting a sub-quantity comprises making a weighting to the effect that such attributes of the total quantity of the attributes determined are weighted more in which corresponding attributes also are determined by other network nodes.

27. The method according to claim 25, wherein selecting a sub-quantity comprises a weighting to the effect that such attributes of the total quantity of the attributes determined are weighted more which originate from a node which already has contributed other attributes for selection.

28. The method according to claim 25, wherein selecting a sub-quantity comprises carrying out an iterative selection process on the total quantity of the attributes determined.

29. The method according to claim 25, wherein selecting a sub-quantity comprises carrying out a cross-validation on the total quantity of the attributes determined.

30. The method according to claim 25, wherein providing a quantity of attributes which characterize an event to be recognized comprises the following steps within the configuration phase:

providing a plurality of sensor nodes of the sensor network,

executing an event to be recognized,

on each of the sensor nodes detecting measurement values which are triggered by the event to be recognized,

on each of the sensor nodes determining a plurality of attributes which characterize the event from the measurement values,

forming the quantity of attributes which characterize an event to be recognized from the sum of attributes determined on the sensor nodes.

31. The method according to claim 25, wherein in the configuration phase a multi-dimensional reference attribute vector is formed from the attributes of the selected attribute sub-quantity, with which a multi-dimensional current attribute vector determined in the execution phase is compared for event recognition.

32. The method according to claim 31, wherein in the configuration phase a plurality of multi-dimensional reference attribute vectors are formed for a plurality of events to be recognized.

33. The method according to claim 31, wherein the execution phase comprises the attributes:

providing the reference attribute vectors determined in the configuration phase,

providing information on an attribute selection made in the configuration phase,

for an event to be currently recognized determining merely attributes on all or some of the sensor nodes which belong to the attribute selection made,

representing these attributes as multi-dimensional current attribute vector, and

making a classification by comparing the current attribute vector with the reference attribute vectors.

34. The method according to claim 25, wherein the selection is made by a central system component which communicates with the individual sensor nodes in a wireless manner.

35. The method according to claim 25, wherein after completion of the configuration phase information on the quantity of the attributes is transmitted into the sensor nodes, which is used in the reference attribute vectors independent of the relative position of the network nodes, and the remaining attributes in the network nodes are neither calculated nor sent.

36. The method according to claim 25, wherein after completion of the configuration phase information furthermore is transmitted into the sensor nodes, which for each sensor node represented in the reference vector relates to a projection from the attribute vector space into the reference attribute vector space dependent on the relative position of the sensor node.

37. The method according to claim 25, wherein acceleration measurement values are detected as measurement values corresponding with an event.

38. The method according to claim 25, wherein as attributes which characterize an event histogram values and/or minimum values and/or maximum values and/or mean values and/or slope values for defined time intervals and/or intensity changes for defined time intervals are determined.

39. The method according to claim 25, wherein the information on the topological origin of the attributes is encoded in the network addresses of the sensor nodes.

40. The method according to claim 25, wherein the information on the topological origin of the attributes is provided by defining space coordinates for each sensor node.

48. A computer program with program code for carrying out the method according to claim 25, when the computer program is executed on a computer.

41. A sensor network with a plurality of sensor nodes, wherein the sensor network can be configured for carrying out a configuration phase and for carrying out an execution phase,

wherein in the configuration phase the sensor network is configured to

provide a quantity of attributes by the sensor nodes of the sensor network, which characterize an event to be recognized, together with information on the topological origin of the attributes within the sensor network, and

select a sub-quantity from the quantity of attributes, wherein the selection is made in consideration of the information on the topological origin of the attributes,

and wherein in the execution phase the sensor network is configured to

perform an event recognition for an event to be currently recognized on the basis of attributes which belong to a selected sub-quantity.

42. The sensor network according to claim 41, comprising a central system component which selects the sub-quantity from the total quantity of the attributes determined.

43. The sensor network according to claim 41, wherein the sensor network is configured to select a sub-quantity by making a weighting to the effect that such attributes of the total quantity of the attributes determined are weighted more which are also determined by other network nodes.

44. The sensor network according to claim 41, wherein the sensor network is configured to select a sub-quantity by making a weighting to the effect that such attributes of the total quantity of the attributes determined are weighted more which originate from a node which already has contributed other attributes for selection.

45. The sensor network according to claim 41, further comprising a module which for selecting a sub-quantity performs an iterative selection process on the total quantity of the attributes determined.

46. The sensor network according to claim 45, wherein the module comprises a module for carrying out a cross-validation on the total quantity of the attributes determined.

47. The sensor network according to claim 41, wherein the sensor network is configured to encode information on the topological origin of the attributes into the network addresses of the sensor nodes.