WIRELESS MOTION SENSOR NETWORK FOR MONITORING MOTION IN A PROCESS, WIRELESS SENSOR NODE, REASONING NODE, AND FEEDBACK AND/OR ACTUATION NODE FOR SUCH WIRELESS MOTION SENSOR NETWORK

• US 20120109872A1
• Filed: 01/18/2010
• Published: 05/03/2012
• Est. Priority Date: 01/16/2009
• Status: Abandoned Application

• Current Assignee: Inertia Technology B.V.
• Original Assignee: Inertia Technology B.V.
• Inventors: Havinga, Paul Johannes Mattheus, Marin-Perianu, Raluca Sandra, Marin-Perianu, Mihai
• Application Number:
  US13/144,672
• Publication Number:
  US 20120109872A1
• Time in Patent Office: Days
• US Class Current: 706/52
• 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
• CPC Class Codes: H04L 67/125 involving control of end-device applications over a network

Abstract

Wireless motion sensor network for monitoring motion in a process comprising at least one wireless sensor node for measuring at least one physical quantity related to motion or orientation, feature extraction means for deriving a feature for the measured quantities, a wireless transmitter connected to the feature extraction means for transmitting the derived feature, and the wireless receiver receiving derived features from other sensor nodes, the network further comprising a reasoning node for collecting features transmitted by the at least one wireless sensor node comprising a collaborative reasoning engine for determining further features based on features received by a wireless receiver wherein the further features are determined by calculation and/or a rule set; and the wireless motion sensor network comprising a feedback and/or actuation means for intervening in or influencing a monitored process based on the output of the collaborative reasoning engine.

Claims

1. Wireless motion sensor network for monitoring motion in a process comprising:

at least one wireless sensor nodes comprising;

at least one sensor for measuring at least one physical quantity related to motion or orientation,

feature extraction means connected to the at least one sensor for deriving a feature from the measured quantities,

a wireless transmitter connected to the feature extraction means for transmitting the derived feature, and

wireless receiver for receiving derived features from other sensor nodes,

a reasoning node for collecting features transmitted by the at least one wireless sensor node, comprising;

a wireless receiver for receiving transmitted features,

a collaborative reasoning engine for determining further features based on features received by the wireless receiver, wherein the further features are determined by calculation and/or a rule set comprising at least one rule,

feedback and/or actuation means for intervening in or influencing the monitored process comprising;

communication means for receiving output of a collaborative reasoning engine from a reasoning node,

feedback means for providing a feedback signal to an user based on the output of the collaborative reasoning engine, and/or

an actuator for controlling a process input based on the output of the collaborative reasoning engine.

2. Wireless motion sensor network according to claim 1, wherein the sensor node further comprises:

semantic property derivation means for deriving a semantic property based on at least one of;

raw sensor data, a derived feature, a confidence measure computed from at least one feature, and the proximity to other sensor nodes, and wherein

the wireless transmitter is connected to the semantic property derivation means for transmitting the derived semantic property

the wireless receiver is further configured to receive semantic properties from other sensor nodes;

the sensor node further comprising;

clustering means connected to the semantic properties derivation means and the wireless receiver for dynamically forming clusters with other sensor nodes based upon common semantic properties.

3. Wireless motion sensor network according to claim 2, wherein the dusters as formed according to claim 2 form a first hierarchical level, and wherein the sensor nodes are configured to form a higher level cluster by clustering the nodes of two lower level clusters that have at least nine sensor node in common.

4. Wireless motion sensor network according to claim 2, wherein the collaborative reasoning engine only combines derived features originating from sensor nodes from a common cluster.

5. Wireless motion sensor network according to claim 1, wherein the sensor node and reasoning node are combined into a single node.

6. Wireless motion sensor network according to claim 1, wherein the reasoning node and the feedback and/or actuation node are combined into a single node.

7. Wireless motion sensor network according to claim 1, wherein a sensor node determines whether the node is in one of the following states when the sensor node undergoes a repetitive motion:

a static reference position characterised by a sensor output showing or at least hinting at the absence of motion

an extreme position characterised by a sensor output showing or at least hinting at the sensor having reached a minimum or a maximum position within a range of motion; and

a continuous motion characterised by a sensor output showing or at least hinting at the sensor being in motion between two extreme positions.

8. Wireless motion sensor network according to claim 7, wherein a sensor node calibrates a sensor or a feature during a determined static reference position by making use of the knowledge that the sensor node is motionless.

9. Wireless motion sensor network according to claim 7, wherein the sensor node calibrates a sensor or a feature by assuming a value at a determined extreme position.

10. Wireless motion sensor network according to claim 1, wherein the sensor node further comprises a local reasoning engine connected to the feature extraction means for determining a confidence measure expressing the confidence that a particular situation has occurred based upon a reasoning process, the local reasoning engine being further connected to the wireless transmitter for transmitting the confidence measure.

11. Wireless motion sensor network according to claim 1, wherein a determined feature is expressed as a fuzzy variable comprising at least one fuzzy value.

12. Wireless motion sensor network according to claim 11, wherein a fuzzy variable of a feature is used in the collaborative reasoning engine of a reasoning node as an antecedent to a fuzzy if-then implication that outputs a fuzzy output.

13. Wireless mot on sensor network according to claim 11, wherein multiple fuzzy variables are aggregated into a single fuzzy output through a fuzzy inference process.

14. Wireless motion sensor network according to claim 11, wherein a fuzzy output is defuzzified to a crisp output.

15. Wireless motion sensor network according to claim 1, wherein a sensor node determines an amount of turn by determining the angle between a first orientation of the sensor node and a second orientation of the sensor node, and wherein

the sensor determines a composite measure (Σ

) comprised of the weighted summation of the magnitude of the observed acceleration (A) and the determined amount of turn (θ

), wherein the weighting is performed with a weighting function (f(θ

)) dependent on the amount of turn (θ

); and

the composite measure (Σ

) is provided as a feature.

16. Wireless motion sensor network according to claim 15, wherein the angle between the first orientation and the second orientation of the sensor node are determined by taking a first compass reading and a second compass reading and calculating the arccosine of the dot product of the first and second compass readings.

17. Wireless motion sensor network according to claim 15, wherein the composite measure (Σ

) is used as the semantic property that is input to the clustering means of at least two sensor nodes in order to determine whether the at least two sensor nodes should form a cluster based on the similarity of motion.

18. Wireless motion sensor network according to claim 1, wherein the collaborative reasoning means take a number of features as input that are redundant or even overlapping, wherein the features are aggregated by determining a majority quantification, the majority quantification expressing an amount for the features that is supported by the majority of the input features.

19. Wireless motion sensor network according to claim 18, wherein the majority quantification is done in fuzzy logic and the result is used in fuzzy inference during collaborative reasoning.

20. Wireless motion sensor network according to claim 18 wherein the temporal knowledge, for example temporal order constraints, is used in the collaborative reasoning in addition to the derived features.

21. Wireless motion sensor network according to claim 20, wherein the temporal knowledge, for example the temporal order constraints, is expressed by means of fuzzy variables.

22. Wireless sensor node for use in a wireless motion sensor network for monitoring motion in a process comprising:

at least one wireless sensor nodes comprising;

at least one sensor for measuring at least one physical quantity related to motion or orientation,

feature extraction means connected to the east one sensor for deriving a feature from the measured quantities,

a wireless transmitter connected to the feature extraction means for transmitting the derived feature, and

a wireless receiver for receiving derived features from other sensor nodes,

a reasoning node for collecting features transmitted by the at least one wireless sensor node, comprising;

a wireless receiver for receiving transmitted features,

a collaborative reasoning engine for determining further features based on features received by the wireless receiver, wherein the further features are determined by calculation and/or a rule set comprising at least one rule,

feedback and/or actuation means for intervening in or influencing the monitored process comprising;

communication means for receiving output of a collaborative reasoning engine from a reasoning node,

feedback means for providing a feedback signal to an user based on the output of the collaborative reasoning engine, and/or

an actuator for controlling a process input based on the output of the collaborative reasoning engine.

23. Reasoning node for use in a wireless motion sensor network for monitoring motion in a process comprising:

at least one wireless sensor nodes comprising;

at least one sensor for measuring at least one physical quantity related to motion or orientation,

feature extraction means connected to the at least one sensor for deriving a feature from the measured quantities,

a wireless transmitter connected to the feature extraction means for transmitting the derived feature, and

a wireless receiver for receiving derived features from other sensor nodes,

a reasoning node for collecting features transmitted by the at least one wireless sensor node, comprising;

a wireless receiver for receiving transmitted features,

a collaborative reasoning engine for determining further features based on features received by the wireless receiver, wherein the further features are determined by calculation and/or a rule set comprising at least one rule,

feedback and/or actuation means for intervening in or influencing the monitored process comprising;

communication means for receiving output of a collaborative reasoning engine from a reasoning node,

feedback means for providing a feedback signal to an user based on the output of the collaborative reasoning engine, and/or

an actuator for controlling a process input based on the output of the collaborative reasoning engine.

24. Feedback and/or actuation node for use in a wireless motion sensor network for monitoring motion in a process comprising:

at least one wireless sensor nodes comprising;

at least one sensor for measuring at least one physical quantity related to motion or orientation,

feature extraction means connected to the at least one sensor for deriving a feature from the measured quantities,

wireless transmitter connected to the feature extraction means for transmitting the derived feature, and

a wireless receiver for receiving derived features from other sensor nodes,

a reasoning node for collecting features transmitted by the at least one wireless sensor node, comprising;

a wireless receiver for receiving transmitted features,

a collaborative reasoning engine for determining further features base on features received by the wireless receiver, wherein the further features are determined by calculation and/or a rule set comprising at least one rule,

feedback and/or actuation means for intervening in or influencing monitored process comprising;

communication means for receiving output of a collaborative reasoning engine from a reasoning node,

feedback means for providing a feedback signal to an user based on the output of the collaborative reasoning engine, and/or

an actuator for controlling a process input based on the output of the collaborative reasoning engine.