SYSTEMS AND METHODS FOR USING RADIO FREQUENCY SIGNALS AND SENSORS TO MONITOR ENVIRONMENTS

• US 20190197896A1
• Filed: 11/21/2018
• Published: 06/27/2019
• Est. Priority Date: 01/05/2016
• Status: Active Grant

• Current Assignee: Zainar, Inc.
• Original Assignee: Locix, Inc
• Inventors: Bakhishev, Teymur, Subramanian, Vivek, Pavate, Vikram, Ylamurto, Tommi
• Granted Patent: US 10,504,364 B2
• Time in Patent Office: Days
• CPC Class Codes: G06F 18/285 Selection of pattern recognition techniques, e.g. of classifiers in a multi-classifier system
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06V 20/52 Surveillance or monitoring of activities, e.g. for recognising suspicious objects recognising microscopic objects G06V20/69
• CPC Class Codes: G08G 1/142 external to the vehicles
• CPC Class Codes: H04B 17/23 Indication means, e.g. displays, alarms, audible means
• CPC Class Codes: H04B 17/27 for locating or positioning the transmitter
• CPC Class Codes: H04B 17/318 Received signal strength

Abstract

Systems and methods for using radio frequency signals and sensors to monitor environments (e.g., indoor building and adjacent outdoor environments) are disclosed herein. In one embodiment, a system for providing a wireless asymmetric network comprises a hub having one or more processing units and at least one antenna for transmitting and receiving radio frequency (RF) communications in the wireless asymmetric network and a plurality of sensor nodes each having a wireless device with a transmitter and a receiver to enable bi-directional RF communications with the hub in the wireless asymmetric network. The one or more processing units of the hub are configured to determine localization of the plurality of sensor nodes within the wireless asymmetric network, to monitor loading zones and adjacent regions within a building based on receiving information from at least two sensor nodes, and to determine for each loading zone whether a vehicle currently occupies the loading zone.

Claims

1. A system for providing a wireless asymmetric network, comprising:

a hub having one or more processing units and at least one antenna for transmitting and receiving radio frequency (RF) communications in the wireless asymmetric network;

a plurality of sensor nodes each having a wireless device with a transmitter and a receiver to enable bi-directional RF communications with the hub in the wireless asymmetric network to determine localization of the plurality of sensor nodes within the wireless asymmetric network, to monitor loading zones and adjacent regions within a building based on receiving information from at least two sensor nodes, and to determine for each loading zone whether a vehicle currently occupies the loading zone.

2. The system of claim 1, further comprising:

a remote device to communicate with at least one of the hub and the plurality of sensor nodes, wherein the remote device or hub is configured to determine whether an object is also located within a region of the building that is associated with each loading zone.

3. The system of claim 2, wherein the remote device or hub is further configured to use machine learning to classify the object based on sensed data of the object.

4. The system of claim 3, wherein the remote device or hub is further configured to determine a condition based on the identification and classification of the object.

5. The system of claim 4, wherein the determined condition comprises an error or alarm condition caused by an undesired object interfering with loading or unloading of a vehicle.

6. The system of claim 4, wherein the determined condition comprises a safe condition caused by a desired object in a region that is associated with a loading zone of a vehicle.

7. The system of claim 4, wherein the determined condition comprises a warning condition caused by an undesired object to be removed from its current location prior to an anticipated arrival of a vehicle in an adjacent loading zone.

8. The system of claim 2, wherein the remote device or hub is further configured to respond to the condition including communicating the condition to at least one of users, machines, and the vehicle.

9. The system of claim 1, wherein the plurality of sensor nodes include an indoor node to monitor an interior region of the building that is adjacent to a loading zone with the indoor node using at least one of a camera, RF signals, and RF identification tracking to monitor the interior region, wherein the plurality of sensor nodes include an outdoor node to monitor the loading zone with the outdoor node using at least one of a camera, RF signals, and tracking to monitor the loading zone.

10. The system of claim 9, wherein at least one of image data, RF data from the RF signals, and RF tracking data from the indoor node and at least one of image data, RF data from the RF signals, and RF tracking data from the outdoor node are utilized in combination to monitor a dynamically changing environment of the interior region and the loading zone.

11. A sensor node, comprising:

a memory for image data;

an image capturing device to capture image data of loading zones and adjacent regions of a building;

one or more processing units coupled to the image capturing device; and

radio frequency (RF) circuitry to transmit RF communications to and receive RF communications from other wireless nodes within a wireless network architecture, wherein the one or more processing units of the sensor node are configured to execute instructions for processing the image data to monitor the loading zones and the adjacent regions within the building based on image data from at least two wireless nodes and the image data being used to determine for each loading zone whether a vehicle currently occupies the loading zone.

12. The sensor node of claim 11, wherein the radio frequency (RF) circuitry to transmit image data to a remote device that is configured to determine whether an object is located within a region of the building that is associated with each loading zone.

13. The sensor node of claim 12, wherein the remote device is configured to use machine learning to classify the object based on the image data of the object.

14. The sensor node of claim 13, wherein the remote device is further configured to determine a condition based on the identification and classification of the object.

15. The sensor node of claim 11, wherein the sensor node is an indoor node to monitor an interior region of the building that is adjacent to a loading zone with the indoor node using at least one of the image capturing device, RF signals, and RF identification tracking to monitor the interior region, wherein the other nodes include an outdoor node to monitor the loading zone with the outdoor node using at least one of a camera, RF signals, and tracking to monitor the loading zone.

16. The sensor node of claim 15, wherein at least one of image data, RF data from the RF signals, and RF tracking data from the indoor node and at least one of image data, RF data from the RF signals, and RF tracking data from the outdoor node are utilized in combination to monitor a dynamically changing environment of the interior region and the loading zone.

17. A method for monitoring a wireless network architecture, comprising:

transmitting, with a plurality of sensor nodes each having a wireless device with a transmitter and a receiver, RF communications in the wireless network architecture to determine localization of the plurality of sensor nodes within the wireless network architecture;

monitoring, with the plurality of sensor nodes each having an image capturing device, loading zones and adjacent regions within a building based on receiving image data from at least two sensor nodes; and

determining for each loading zone whether a vehicle currently occupies the loading zone.

18. The method of claim 17, further comprising:

determining, with a remote device or a sensor node, whether an object is also located within a region of the building that is associated with each loading zone.

19. The method of claim 18, further comprising:

using machine learning to classify the object based on sensed image data of the object.

20. The method of claim 19, further comprising:

determining a condition based on the identification and classification of the object.

21. The method of claim 17, wherein the plurality of sensor nodes include an indoor node to monitor an interior region of the building that is adjacent to a loading zone with the indoor node using at least one of a camera, RF signals, and RF identification tracking to monitor the interior region, wherein the plurality of sensor nodes include an outdoor node to monitor the loading zone with the outdoor node using at least one of a camera, RF signals, and tracking to monitor the loading zone.

22. The method of claim 21, wherein at least one of image data, RF data from the RF signals, and RF tracking data from the indoor node and at least one of image data, RF data from the RF signals, and RF tracking data from the outdoor node are utilized in combination to monitor a dynamically changing environment of the interior region and the loading zone.