CONTEXTUALLY AWARE MONITORING OF ASSETS

• US 20110133888A1
• Filed: 08/17/2010
• Published: 06/09/2011
• Est. Priority Date: 08/17/2009
• Status: Active Grant

• Current Assignee: Savi Technology Incorporated
• Original Assignee: Deal Magic Inc.
• Inventors: Quinn, Nicholas James, Stevens, Timothy Dirk, Cova, Nicholas D.
• Granted Patent: US 9,177,282 B2
• Time in Patent Office: Days
• US Class Current: 340/8.1
• CPC Class Codes: G06Q 10/08 Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
• CPC Class Codes: G06Q 10/0833 Tracking
• CPC Class Codes: G06Q 50/28 Logistics, e.g. warehousing, loading, distribution or shipping

Abstract

An apparatus, method and system for contextually aware monitoring of a supply chain are disclosed. In some implementations, contextually aware monitoring can include monitoring of the supply chain tradelane with tracking devices including sensors for determining location, velocity, heading, vibration, acceleration (e.g., 3D acceleration), or any other sensor that can monitor the environment of the shipping container to provide contextual awareness. The contextual awareness can be enabled by geofencing and recursive algorithms, which allow dynamic modification of the tracking device behavior. Dynamic modification can reduce performance to save power (e.g., save battery usage) and lower costs. Dynamic modification can increase performance where it matters in the supply chain for improved reporting accuracy or frequency or recognition of supply chain events. Dynamic modification can adapt performance such as wireless communications to the region or location of the tracking device.

Claims

1. A computer-implemented method, comprising:

receiving tracking data for an asset from a tracking device coupled to the asset, the tracking data including a location of the asset and a timestamp corresponding to the location;

utilizing a Hidden Markov Model to assess a shipping context of the asset based on the received tracking data;

determining that a dynamic behavior of the tracking device is to be adjusted based on the shipping context; and

adjusting the dynamic behavior of the tracking device for the asset.

2. The method of claim 1, wherein adjusting the dynamic behavior of the tracking device, comprises:

adjusting a frequency of collecting location data to increase granularity of the location data, or to reduce power consumption by the tracking device.

3. The method of claim 1, wherein adjusting the dynamic behavior of the tracking device, comprises:

adjusting a frequency of sending communication reports to reduce a latency of the reports, or to reduce power consumption by the tracking device.

4. The method of claim 1, wherein adjusting the dynamic behavior of the tracking device comprises:

using higher accuracy modes of a navigation receiver in the tracking device to increase accuracy of the location data, or lower accuracy modes of the navigation receiver to reduce power consumption by the tracking device.

5. The method of claim 1, wherein adjusting the dynamic behavior of the tracking device comprises:

selecting a communication channel from a plurality of available communication channels; and

sending communication reports on the selected communication channel.

6. The method of claim 5, wherein it is determined whether it is cost-effective to report the event at the particular time is based at least in part on a type of the event and the cost and resources required for reporting.

7. The method of claim 5, wherein the list of preferred communication channels and the list of excluded communication channels correspond to a particular geographic region in which the asset is currently located.

8. The method of claim 1, wherein determining the shipping context comprises:

determining an occurrence of a supply chain event.

9. The method of claim 8, wherein the supply chain event is at least one of a gate in to a supply chain node or gate out from a supply chain node.

10. The method of claim 1, wherein determining the shipping context comprises:

determining an occurrence of change of custody of the asset being shipped.

11. The method of claim 1, wherein determining the shipping context comprises:

determining an updated dynamic estimated time of arrival of the asset at the destination.

12. The method of claim 1, wherein determining the shipping context comprises:

determining an occurrence of a stuck shipment exception condition.

13. The method of claim 1, further comprising:

accumulating data from multiple tracking devices; and

downloading contextual data to each tracking device.

14. A computer-implemented method, comprising:

receiving tracking data for an asset from a tracking device coupled to the asset, the tracking data including a location of the asset and a timestamp corresponding to the location;

utilizing nested geofences to assess a shipping context of the asset based on the received tracking data;

determining that a dynamic behavior of the tracking device is to be adjusted based on the shipping context; and

adjusting the dynamic behavior of the tracking device for the asset.

15. A computer-implemented method, comprising:

receiving sensor data for an asset from a tracking device coupled to the asset, the sensor data including one or more of vibration data, velocimeter data, and accelerometer data of the asset and a timestamp corresponding to the sensor data;

utilizing pattern matching to assess a shipping context of the asset based on the received sensor data;

determining that a dynamic behavior of a tracking device coupled to the asset is to be adjusted; and

adjusting the dynamic behavior of the tracking device for the asset.

16. The method of claim 15, wherein determining the shipping context comprises:

determining an occurrence of a supply chain event.

17. The method of claim 16, wherein the supply chain event is at least one of a crane load to a ship or a crane unload from a ship.

18. A computer-implemented method, comprising:

receiving tracking data for an asset from a tracking device coupled to the asset, the tracking data including a location of the asset and a timestamp corresponding to the location;

receiving sensor data for an asset from the tracking device, the sensor data including one or more of vibration data, velocimeter data, and accelerometer data of the asset at the location;

determining if the shipment is stationary or in motion;

if the shipment is stationary, selecting a vibration or acceleration pattern matching model;

if the shipment is in motion, selecting at least one of a Hidden Markov model with historical data for a tradelane of the shipment, or a nested geofence model without historical data for the tradelane of the shipment;

assessing a shipping context of the asset based on the selected model and the received tracking or sensor data;

determining that a dynamic behavior of the tracking device is to be adjusted; and

adjusting the dynamic behavior of the tracking device for the asset.

19. A system for tracking an asset based on shipping context, the system comprising:

a communication interface configured for communicating with a tracking device coupled to the asset, the communication interface configured for receiving tracking data for the asset from the tracking device, the tracking data including a location of the asset and a timestamp corresponding to the location;

a processor coupled to the communication interface and configured for;

utilizing a Hidden Markov Model to assess a shipping context of the asset based on the received tracking data;

determining that a dynamic behavior of the tracking device is to be adjusted based on the shipping context; and

adjusting the dynamic behavior of the tracking device for the asset.

20. A system for tracking an asset based on shipping context, the system comprising:

a communication interface configured for receiving tracking data for an asset from a tracking device coupled to the asset, the tracking data including a location of the asset and a timestamp corresponding to the location;

a processor coupled to the communication interface and configured for;

utilizing nested geofences to assess a shipping context of the asset based on the received tracking data;

determining that a dynamic behavior of the tracking device is to be adjusted based on the shipping context; and

adjusting the dynamic behavior of the tracking device for the asset.

21. A system for tracking an asset based on shipping context, the system comprising:

a communication interface configured for receiving sensor data for an asset from one or more sensors from a tracking device coupled to the asset, the sensor data including one or more of vibration data, velocimeter data, and accelerometer data of the asset and a timestamp corresponding to the sensor data;

a processor coupled to the communication interface and configured for;

utilizing pattern matching to assess a shipping context of the asset based on the received sensor data;

determining that a dynamic behavior of a tracking device coupled to the asset is to be adjusted; and

adjusting the dynamic behavior of the tracking device for the asset.

22. A system for tracking an asset based on shipping context, the system comprising:

a communication interface configured for receiving tracking data for an asset from a tracking device coupled to the asset, the tracking data including a location of the asset and a timestamp corresponding to the location, and for receiving sensor data for an asset from the tracking device, the sensor data including one or more of vibration data, velocimeter data, and accelerometer data of the asset at the location;

a processor coupled to the communication interface and configured for;

determining if the shipment is stationary or in motion based on the sensor data or location data;

if the shipment is stationary, selecting a vibration or acceleration pattern matching model;

if the shipment is in motion, selecting at least one of a Hidden Markov model with historical data for a tradelane of the shipment, or a nested geofence model without historical data for the tradelane of the shipment;

assessing a shipping context of the asset based on the selected model and the received tracking or sensor data;

determining that a dynamic behavior of the tracking device is to be adjusted; and

adjusting the dynamic behavior of the tracking device for the asset.