Patent Issued for Automated purchasing systems and methods (USPTO 11741447): United Services Automobile Association

2023 SEP 15 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- According to news reporting originating from Alexandria, Virginia, by NewsRx journalists, a patent by the inventors Bell, Curtis Mark (San Antonio, TX, US), Dziuk, Janelle Denice (Falls City, TX, US), Guerra, Oscar (San Antonio, TX, US), Jones, Jr., David M. (San, TX, US), Khmelev, Yevgeniy Viatcheslavovich (San Antonio, TX, US), Lake, Zachery C. (Aubrey, TX, US), Martinez, Noe Alberto (San Antonio, TX, US), Matheson, Cory A. (Celina, TX, US), Philbrick, Ashley Raine (San Antonio, TX, US), Post, Nathan Lee (Rockport, TX, US), filed on September 28, 2020, was published online on August 29, 2023.

The assignee for this patent, patent number 11741447, is United Services Automobile Association (San Antonio, Texas, United States).

Reporters obtained the following quote from the background information supplied by the inventors: “The development of Internet of things (IoT) technologies has brought a new revolution in the retail industry, which has a growing need to increase customer loyalty and to deliver an improved in-store experience. For example, the retail industry may use IoT technologies to provide a more efficient shopping experience, where items that are placed in a shopping cart can be automatically recognized, and customers can be billed accordingly. As a result, customers can avoid long queuing time at the checkout points.

“Conventional methods for shopping using IoT technologies may be expensive and computationally inefficient. For example, some conventional methods for automatic shopping may use video surveillance cameras as IoT sensors in retail environments to track how customers move around in the shopping space. The surveillance cameras and sensors may keep track of a customer’s movements, every product picked up and then placed in a bag/shopping cart, every label read and product replaced on the shelf, every hesitation, head nod, and the like. Retailers may gather enormous amount of data and monitor customers to provide such a shopping experience.

“Such conventional methods may require a large number of expensive surveillance cameras to be installed to cover every corner of the shopping space. Furthermore, the processing of the collected video data may include image recognition and face recognition, which may be power consuming and computational complex. Because of these technical shortcomings, stores utilizing conventional systems cannot accommodate multiple shoppers simultaneously walking around the shopping space and placing various items in their shopping carts. For instance, performing simultaneous and continuous facial recognition on multiple shopper in a crowded shopping isle is costly, inefficient, and may lead to inaccurate results. Therefore, stores utilizing conventional methods may only allow a limited number of customers in the shopping space. In addition, the surveillance cameras may pose security and privacy threats. Customers may have concerns regarding their privacy and may be uncomfortable about being monitored closely, which will inevitably lead to a negative user experience.

“Some other conventional methods may use RFID (radio-frequency identification) tags to provide an automatic shopping experience. For instance, each item may have an RFID tag. As a customer picks up items and places the items in a shopping cart, the item’s RFID tag may be automatically scanned by a RFID reader installed on a smart shelf or a smart cart. As a result, the retailer may provide an automatic shopping experience by automatically recognizing the items in a shopping cart based on the RFID tags. Such conventional methods may require an RFID attached to every single item, which is undesirable and expensive.”

In addition to obtaining background information on this patent, NewsRx editors also obtained the inventors’ summary information for this patent: “For the aforementioned reasons, what is needed is a system and method to automatically recognize items put in a shopping cart without requiring heavy computational resources, without requiring accumulation of extensive amounts of data, and without requiring expensive hardware devices. Embodiments disclosed herein address the above challenges by providing a system and method for recognizing the purchased items using weight sensors installed in shelves and shopping carts. Using the methods and systems disclosed herein, a store may provide an efficient automatic shopping experience while needing fewer hardware devices than required by the conventional methods and systems, which in turn increases efficiency of purchasing.

“The weight sensors are low-cost devices collecting (i.e., sensing) weight changes at shelves and shopping carts. The weight sensors may be installed in predetermined locations of shelves. Based on the sensed weight change in a specific location of the shelf, a server may be able to determine the identifier of the item being picked up from the shelf. The weight sensor in a shopping cart may detect a weight addition when an item is placed in the shopping cart. By matching the weight lifted from a shelf with the weight added into a shopping cart, the server may determine that the item picked up from the shelf is placed into the shopping cart. Based on the identifier of the item, the server may automatically recognize the item placed in the shopping cart.

“Furthermore, the server may need to correlate the customer with the items picked up from the shelf and placed in the shopping cart. For example, the server may need to identify who picked up the item from the shelf and placed the item in which cart. To do so, the server may associate the shopping cart with an electronic device of the customer. The server may also monitor the customer’s location by periodically receiving location identification signal from the customer’s electronic device. Based on the location of the customer, the server may determine the items and/or shelves located within a proximity of the customer. For example, the server may determine that the customer is near the shelf holding sparkling water. When the customer picks up a case of sparkling water and places the sparkling water in his/her shopping cart, the weight sensor of the associated shopping cart may detect the weight addition. The weight sensor of the shelf holding sparkling water may detect the weight change too. The server may receive the weight addition from the weight sensor on the shopping cart associated with the customer. The server may also receive the weight change from the weight sensor on the shelf the customer has visited (e.g., the shelf within the proximity of the customer’s location). The server may compare the weight addition and the weight change. If they match, the server may determine that the user has placed the item in his/her cart. Based on the specific location of the weight sensor that detects the weight change, the server may determine the identifier of the item. As a result, the server may determine what product the customer has placed in his/her shopping cart. Therefore, the methods and systems described herein provide an automatic shopping experience based on low-cost weight sensors.

“The weight sensors are only installed in predetermined locations of the shelves and the shopping carts. The number of required weight sensors is limited. Comparing with the RFID tags attached to every single item in conventional methods, the number of weight sensors is significantly less. In addition, the weight sensors are low-cost. Comparing with the expensive surveillance cameras in the conventional methods, the weight sensors are more cost-efficient. Because the weight sensors do not perform face recognition and image recognition, the systems and methods described herein are more computation efficient and less power consuming. Furthermore, because the weight sensors do not collect the customers’ image data, the systems and methods described herein are more secure and introduce less privacy concerns.

“In one embodiment, a method comprises associating, by a server, a shopping cart of a store with an electronic device upon the electronic device scanning a label on the shopping cart comprising an identifier of the shopping cart, the shopping cart having a first weight sensor configured to sense a weight addition associated with each item placed within the shopping cart; monitoring, by the server, locations of the electronic device by periodically receiving, from the electronic device, location identification signals; identifying, by the server, a shelf holding one or more items located within a first predetermined proximity of the electronic device based on the locations of the electronic device, the shelf having a set of second weight sensors installed in different sections of the shelf and configured to detect a weight change upon each item on the shelf is lifted; receiving, by the server, a notification comprising an amount of weight change from a second weight sensor within the set of second weight sensors, the amount of weight change associated with an item being lifted from the shelf; receiving, by the server, an indication comprising an amount of weight addition from the first weight sensor; when the amount of weight change matches the amount of weight addition, identifying, by the server, an identifier of the item being lifted from the shelf based on the section of the shelf where the second weight sensor is installed, wherein the server determines that the item being lifted from the shelf is placed within the shopping cart; when the electronic device is within a second predetermined proximity to an exit of the store based on the locations of the electronic device, determining, by the server, a payment amount based on identifiers of items placed within the shopping cart; and transmitting, by the server, the payment amount from a first account associated with a user operating the electronic device to a second account of a merchant associated with the store.”

The claims supplied by the inventors are:

“1. A method comprising: receiving, by an electronic device, beacon signals from a shopping cart of a store, wherein the shopping cart and the electronic device are within a first predetermined proximity; determining that the beacon signals are received by the electronic device during a preset time threshold; associating, by a server, the shopping cart with the electronic device responsive to determining that the electronic device received the beacon signals from the shopping cart during the preset time threshold, wherein the shopping cart comprises a first weight sensor configured to detect a weight addition; monitoring, by the server, locations of the electronic device by periodically receiving, from the electronic device, location identification signals; accessing a map from a database, wherein the map comprises locations of shelves of a shelving system, an arrangement of items of an item system, and a weight of the items of the item system; identifying, by the server, a shelf of the shelving system holding one or more items located within a second predetermined proximity of the electronic device based on the locations of the electronic device and the map, wherein the shelf comprises a set of second weight sensors installed in different sections of the shelf and configured to detect a weight change upon each item on the shelf is lifted; receiving, by the server, a notification comprising an amount of weight change from a second weight sensor within the set of second weight sensors, wherein the amount of weight change is associated with an item being lifted from the shelf, receiving, by the server, an indication comprising an amount of weight addition from the first weight sensor; when the amount of weight change matches the amount of weight addition, confirming, by the server, an identifier of the item being lifted from the shelf based on the section of the shelf where the second weight sensor is installed based at least in part on the map, wherein the server determines that the item being lifted from the shelf is placed within the shopping cart; determining, by the server, a check out status based on a third proximity of the electronic device to an exit of the store using the locations of the electronic device and based on the electronic device receiving the beacon signals from the shopping cart, wherein the check out status is ready to check out when the electronic device is within the third predetermined proximity of the exit and when the electronic device is receiving the beacon signals from the shopping cart; determining, by the server, a payment amount based on identifiers of items placed within the shopping cart based on determining the ready to check out status; and transmitting, by the server, the payment amount from a first account associated with a user operating the electronic device to a second account of a merchant associated with the store.

“2. The method of claim 1, wherein the server monitors the electronic device by periodically receiving location identification signals.

“3. The method of claim 1, wherein the identifier of the identified item corresponds to at least one of a category of the identified item, attributes of the identified item, and a price of the identified item.

“4. The method of claim 1, further comprising: comparing, by the server, the amount of weight change with a weight of the identified item, wherein the amount of weight change is based on signal from at least two weight sensors; and determining, by the server, a number of the item being picked up from the shelf.

“5. The method of claim 1, further comprising: displaying, by the server, an authentication prompt comprising a plurality of payment methods, each payment method corresponding to a different account; receiving, by the server, a selected payment method from the electronic device; and transmitting, by the server, the payment amount from an account corresponding to the selected payment method.

“6. The method of claim 1, further comprising: determining, by the server, user preferences based on historical data of items purchased by the user, wherein the items comprise one or more periodic purchases by the user.

“7. The method of claim 1, further comprising: determining, by the server, user preferences based on historical data of a group of existing users who share one or more attributes with the user.

“8. A system, comprising: a plurality of shopping carts, each individual shopping cart of the plurality comprising: a unique identifier; and at least one weight sensor; a shelving system comprising shelf weight sensors spatially distributed about shelves of the shelving system; a map comprising locations of shelves of the shelving system, an arrangement of items of an item system, and a weight of items of the item system, wherein the map is stored in a database; and a controller in communication with an electronic device of a user and the database, the controller configured to: access the map from the database; determine the electronic device is receiving beacon signals from an individual shopping cart of the plurality of shopping carts within a predetermined proximity, wherein the beacon signals comprise the unique identifier of the individual shopping cart of the plurality of shopping carts; determining that the electronic device is receiving the beacon signals over a preset time threshold; associate the electronic device with the unique identifier of the individual shopping cart of the plurality of shopping carts based on the electronic device receiving the beacon signals in the predetermined proximity and over the preset time threshold; determine user preferences based on a user profile of the user, wherein the user profile comprises one or more products determined to be purchased periodically by the user; receive a detected increase in weight from the at least one weight sensor of the individual shopping cart; receive a detected decrease in weight from a shelf weight sensor; associate an item with the individual shopping cart of the user based at least in part on a correlation between the detected increase in weight and the detected decrease in weight; confirm an identifier of the associated item with the individual shopping cart based at least in part on determining that the detected decrease in weight from the shelf weight sensors originates from a shelf location of the shelving system associated with the item using the map; and determine a check out status based on a location of the electronic device being within a predetermined proximity to an exit of a store and based on the electronic device receiving the beacon signals from the individual shopping cart, wherein the check out status is ready to check out when the electronic device is within the predetermined proximity of the exit and when the electronic device is receiving the beacon signals from the individual shopping cart; determine a payment amount based on identifiers of items placed within the shopping cart in response to determining the check out ready status; and transmit the payment amount from a first account associated with the user to a second account of a merchant associated with the store.

“9. The system of claim 8, wherein the controller is configured to associate the item with the individual shopping cart of the user further based on a location match between the shelf weight sensor and the individual shopping cart.

“10. The system of claim 8, wherein the controller is configured to associate the item with the individual shopping cart of the user further based on the detected increase in weight and the detected decrease in weight occurring within a predetermined time window.

“11. The system of claim 8, wherein the at least one weight sensor is coupled to wireless communication circuitry to transmit the detected increase in weight to the controller.”

There are additional claims. Please visit full patent to read further.

For more information, see this patent: Bell, Curtis Mark. Automated purchasing systems and methods. U.S. Patent Number 11741447, filed September 28, 2020, and published online on August 29, 2023. Patent URL (for desktop use only): https://ppubs.uspto.gov/pubwebapp/external.html?q=(11741447)&db=USPAT&type=ids

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