CART CLUSTER DETECTION AND ESTIMATION

• US 20080316029A1
• Filed: 08/28/2008
• Published: 12/25/2008
• Est. Priority Date: 03/18/2005
• Status: Active Grant

• Current Assignee: Jesse M. James, Scott J. Carter, Stephen E. Hannah
• Original Assignee: Jesse M. James, Scott J. Carter, Stephen E. Hannah
• Inventors: Hannah, Stephen E., Carter, Scott J., James, Jesse M.
• Granted Patent: US 8,478,471 B2
• Time in Patent Office: Days
• US Class Current: 340/568.5
• CPC Class Codes: A47F 10/04 for storing or handling self-service hand-carts or baskets
• CPC Class Codes: B60K 25/08 from a ground wheel, e.g. engaging the wheel tread or rim
• CPC Class Codes: B60T 7/16 operated by remote control, i.e. initiating means not mounted on vehicle
• CPC Class Codes: B60T 7/18 operated by wayside apparatus
• CPC Class Codes: B62B 3/14 characterised by provisions for nesting or stacking, e.g. shopping trolleys collapsible shopping trolleys B62B3/027
• CPC Class Codes: B62B 3/1404 Means for facilitating stowing or transporting of the trolleys; Antitheft arrangements B62B5/0423 takes precedence
• CPC Class Codes: B62B 3/1412 mounted on the frame
• CPC Class Codes: B62B 3/1424 Electronic display devices
• CPC Class Codes: B62B 3/1492 Wheel arrangements
• CPC Class Codes: B62B 5/0003 Adaptations for loading in or on a vehicle
• CPC Class Codes: B62B 5/0423 braking or blocking when leaving a particular area
• CPC Class Codes: B62B 5/0438 hand operated
• CPC Class Codes: B62B 5/048 Hub brakes; drum brakes
• CPC Class Codes: G01C 21/12 executed aboard the object being navigated; Dead reckoning
• CPC Class Codes: G01C 21/206 specially adapted for indoor navigation
• CPC Class Codes: G06K 7/10366 the interrogation device being adapted for miscellaneous applications
• CPC Class Codes: G06Q 10/08 Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
• CPC Class Codes: G08B 13/2434 Tag housing and attachment details
• CPC Class Codes: G08B 13/2448 Tag with at least dual detection means, e.g. combined inductive and ferromagnetic tags, dual frequencies within a single technology, tampering detection or signalling means on the tag
• CPC Class Codes: G08B 13/246 Check out systems combined with EAS, e.g. price information stored on EAS tag anti-theft systems in point of sale systems G07G3/003
• CPC Class Codes: G08B 13/2462 : Asset location systems combined with EAS inventory, tracking, logistic G06Q10/00; entrance control systems G07C9/00
• CPC Class Codes: G08B 13/2474 : Antenna or antenna activator geometry, arrangement or layout loop antennae H01Q1/22
• CPC Class Codes: G08B 13/2477 : Antenna or antenna activator circuit
• CPC Class Codes: G08B 13/2482 : EAS methods, e.g. description of flow chart of the detection procedure
• CPC Class Codes: G08G 1/20 : Monitoring the location of vehicles belonging to a group, e.g. fleet of vehicles, countable or determined number of vehicles
• CPC Class Codes: H02K 7/1846 : structurally associated with wheels or associated parts dynamos arranged in the wheel hub of cycles B62J6/12
• CPC Class Codes: H04W 4/02 : Services making use of location information
• CPC Class Codes: H04W 4/024 : Guidance services
• CPC Class Codes: H04W 4/029 : Location-based management or tracking services
• CPC Class Codes: Y10T 29/49826 : Assembling or joining

Abstract

A vehicle tracking system includes a wheel containing sensor circuitry capable of sensing various types of conditions, such as wheel rotation, wheel vibration caused by skidding, and specific electromagnetic and/or magnetic signals indicative of particular wheel locations. The sensor circuitry is coupled to an RF transceiver, which may but need not be included within the wheel. The wheel may also include a brake mechanism. In one embodiment, the wheels are placed on shopping carts and are used to collect and monitor shopping cart status and location data via a wireless network. The collected data may be used for various purposes, such as locking the wheel of an exiting cart if the customer has not paid, estimating numbers of queued carts, stopping wheel skid events that occur during mechanized cart retrieval, store planning, and providing location-based messaging to customers.

Claims

1. A method of estimating a number of carts clustered together in an area that comprises a plurality of carts, the method comprising:

causing each of the plurality of carts to generate a radio frequency (RF) transmission;

at each respective cart, generating RSSI (Received Signal Strength Indication) values for the transmissions received from the other carts; and

collectively analyzing the RSSI values generated at the carts to estimate how many of the carts are clustered together.

2. The method of claim 1, wherein the method is performed at a checkout area to estimate a number of shopping carts queued at a register.

3. The method of claim 2, further comprising generating an alert message when said number of queued shopping carts exceeds a threshold.

4. The method of claim 1, wherein the method is performed to determine an approximate number of carts being retrieved by a mechanized cart retrieval unit.

5. The method of claim 4, further comprising automatically doing at least one of the following if the approximate number of carts being retrieved exceeds a selected threshold:

(1) changing a mode of operation of the mechanized cart retrieval unit, (2) activating an alarm.

6. The method of claim 1, further comprising using RSSI values generated by a receiver at a front of a cart queuing area to identify a first cart in an identified queue of carts, said receiver not being attached to any one of the carts.

7. The method of claim 1, wherein each cart generates the RF transmission via a respective RF transceiver.

8. The method of claim 7, wherein the RF transceivers are located in wheels of the carts.

9. The method of claim 1, wherein collectively analyzing the RSSI values comprising converting a group of RSSI values into a filtered RSSI values.

10. The method of claim 1, wherein collectively analyzing the RSSI values comprising calculating distance metrics for specific pairs of carts, and using a clustering algorithm to analyze the distance metrics.

11. A system configured to perform the method of claim 1, the system comprising a wheel assembly that includes communication circuitry configured to generate and report said RSSI values.

12. A system for detecting clusters of carts, comprising:

a plurality of wheels that are adapted to be attached to respective carts, each wheel including a radio frequency (RF) transceiver; and

a node configured to communicate bi-directionally with the plurality of wheels;

wherein the wheels are configured to measure signal strengths of transmissions from other wheels and to report said signal strengths to said node, and the node is programmed to collectively analyze the reported signal strengths to identify carts that are clustered together.

13. The system of claim 12, wherein the node is programmed to identify a set of carts that form a queue.

14. A shopping cart wheel assembly that supports a method of detecting clusters of shopping carts, said wheel assembly comprising:

a shopping cart wheel adapted to be attached to a shopping cart; and

communication circuitry, said communication circuitry configured to receive radio frequency transmissions from other shopping cart wheel assemblies of other shopping carts, and to report, via wireless transmissions, information about said transmissions received from the other shopping cart wheel assemblies, including data regarding signal strengths of said received transmissions, said communication circuitry thereby enabling an external system to detect clusters of shopping carts.

15. The shopping cart wheel assembly of claim 14, wherein the communication circuitry is housed within the wheel.

16. The shopping cart wheel assembly of claim 14, wherein the wheel assembly includes a caster that houses at least a portion of said communication circuitry.

17. The shopping cart wheel assembly of claim 14, in combination with a processing system that uses said information about the received transmissions to estimate numbers of shopping carts clustered together.