System and method of utilizing 3D vision for asset management and tracking

1. A system for determining a load status of an asset container, comprising:

a first tape node having a first low-power wireless-communications interface and a first camera, the first tape node operable to capture and transmit a first image; and

a second tape node, comprising:

a second camera;

a second low-power wireless-communication interface;

a processor; and

memory communicatively coupled with the processor and storing machine-readable instructions that, when executed by the processor, cause the processor to:

receive, from the first tape node, the first image;

capture a second image using the second camera;

perform computer vision techniques on the first and second images to generate the load status of the asset container; and

transmit the load status to a nearby node.

2. The system of claim 1 , wherein the computer vision techniques include one of stereoscopy, multi-stereoscopy, and time-of-flight sensing.

3. The system of claim 1 , the memory storing further machine-readable instructions that, when executed by the processor, further cause the processor to:

determine that the first camera is in an acceptable position to capture the first image to use for the computer vision techniques for generating the load status;

identify that the second tape node is within the asset container; and

receive confirmation that the second camera of the second tape node is in a position that enables the second camera to capture an acceptable second image to use for the computer vision techniques for generating the load status.

4. The system of claim 1 , wherein the nearby node is a client device running a client application of the wireless sensing system, wherein the transmitting the load status includes a notification that includes instructions for a human operator to load the asset container with assets that increase the load of the asset container.

5. The system of claim 1 , wherein the first and second cameras capturing the first and second images are responsive to the first tape node receiving a signal from a third tape node adhered to a door of the asset container indicating an accelerometer embedded within the third tape node is exceeding a threshold, the memory storing further machine-readable instructions that, when executed by the processor, further cause the processor to:

receive, from the third tape node, the signal indicating the accelerometer is exceeding a threshold.

6. The system of claim 1 , wherein the capturing of the first and second images occur in predetermined time intervals or at predetermined locations.

7. The system of claim 1 , the memory storing further machine-readable instructions that, when executed by the processor, further cause the processor to:

synchronize the capture of the second image with the capture of the first image by communicating a time with the second tape node to begin capture of the first and second images.

8. The system of claim 1 , the memory storing further machine-readable instructions that, when executed by the processor, further cause the processor to:

receive an instruction from a third tape node to capture the second image.

9. A system for determining a load status of an asset container, comprising:

a first tape node having a first low-power wireless-communications interface and a first camera operable to capture a first image;

a second tape node comprising:

a second camera;

a second low-power wireless-communication interface;

a processor; and

memory communicatively coupled with the processor and storing machine-readable instructions that, when executed by the processor, cause the processor to:

receive, from the first tape node, the captured first image;

capture a second image using the second camera;

transmit, to a wireless node having another low-power wireless-communications interface, the captured first and second images to generate a load status of the asset container;

receive, from the wireless node and based on computer vision techniques on the first and second images, the load status of the asset container; and

transmit a notification to a nearby node that includes the load status of the asset container.

10. The system of claim 9 , the memory storing further machine-readable instructions that, when executed by the processor, cause the processor to:

identify the first tape node; and

receive, from the first tape node, confirmation that the first camera of the first tape node is in a position that enables the first camera to capture an acceptable first image to use for the computer vision techniques for generating the load status.

11. The system of claim 9 , wherein the wireless node is a stationary gateway adhered to the asset container.

12. The system of claim 9 , wherein the nearby node is a client device running a client application of the system, wherein the notification includes instructions for a human operator to load additional assets to the asset container.

13. The system of claim 9 , wherein the first and second cameras capturing the first and second images are responsive to the second tape node receiving a signal from a third tape node adhered to a door of the asset container indicating an accelerometer of the third tape node is exceeding a threshold, the memory storing further machine-readable instructions that, when executed by the processor, further cause the processor to:

receive, from the third tape node, the signal indicating the accelerometer is exceeding a threshold.

14. A method for determining a load status of an asset container, comprising:

receiving, by a first tape node adhered to a first surface, a first image of an interior of the asset container;

receiving, by the first tape node, a second image of the interior of the asset container captured by an embedded camera of a second tape node adhered to a second surface; and

determining, by performing computer vision techniques on the first and second images, a load status of the asset container; and

transmit the load status of the asset container to a nearby node.

15. The method of claim 14 , wherein the computer vision techniques include one of stereoscopy, multi-stereoscopy, and time-of-flight sensing.

16. The method of claim 14 , wherein the first image was received by the first tape node from a first camera, further comprising:

determining, by the first tape node, that the first camera is in an acceptable position to capture the first image to use for the computer vision techniques for determining the load status;

identifying, by the first tape node, that the second tape node is within the asset container; and

receiving confirmation that the embedded camera of the second tape node is in a position that enables the embedded camera to capture an acceptable second image to use for the computer vision techniques for determining the load status.

17. The method of claim 14 , further comprising: receiving, by the first tape node, a signal from a third tape node adhered to a door of the asset container indicating an accelerometer of the third tape node has measured an acceleration exceeding a threshold, wherein the first and second images are captured responsive to the first tape node receiving the signal from the third tape node.

18. The method of claim 14 , the method further comprising:

synchronizing the capture of the second image with a capture of the first image by communicating a time with the second tape node to begin capture of the first and second images.

19. The method of claim 14 , wherein the performing the computer vision techniques on the first and second images further comprises:

transmitting, by the first tape node, to a third tape node, the first and second images for the third tape node to perform the computer vision techniques; and

receiving, from the third tape node, the determined load status of the asset container.