Amazon Technologies, Inc.

Alexander Edwards

Jon Robert Ducrou

Ryan David Hapgood

Lev Zelenskiy

Sheng-Wei Lin

Michael John Neville

Tony Li

Uladzimir Silchanka

James Eather

Ryan Koscianski

Paul C Hagar

Satheesh Narayanan Kolathur

Jenna Christine Owens

Stephen Waits

Todd Beckett

Scott Laporte

Systems, methods, and computer-readable media are disclosed for systems and methods for autonomous device authentication and compartment unlocking. Example methods may include determining, by a user device, an identifier associated with a target Bluetooth Low Energy peripheral device, receiving a beacon from a Bluetooth Low Energy peripheral device, and determining, using the beacon, that the Bluetooth Low Energy peripheral device is the target Bluetooth Low Energy peripheral device. Example methods may include establishing a connection with the target Bluetooth Low Energy peripheral device, and sending a signal to the target Bluetooth Low Energy peripheral device to implement an action, where the signal comprises a resource identifier, and where the target Bluetooth Low Energy peripheral device controls access to a plurality of resources, and uses the resource identifier to identify a resource of the plurality of resources at which to implement the action.

Autonomous device authentication and compartment unlocking

A user location in a parking lot or other designated area may be identified based on sensor data, such as from one or more sensors in or around the designated area. Also within the designated area, a transport location of a transport associated with an order of the user may be identified based on image data provided by one or more cameras remote from the transport. The transport can be controlled to move from the identified transport location to the identified user location.

Camera-controlled self-delivery cart

A customer offset may be determined with respect to a customer who has previously traveled to one or more merchant locations. A merchant location offset may be determined with respect to multiple customers who have each traveled to a particular merchant location. Upon determining that the customer is in transit to the merchant location, a generic ETA to the merchant location may be determined. A customer-based ETA for the customer with respect to the merchant location may be determined based on the generic ETA and the customer offset. Moreover, a merchant location-based ETA for the customer with respect to the merchant location may be determined based on the generic ETA and the merchant location offset. Based on the refined and more accurate ETAs, the merchant location may be instructed to begin assembling items for pick-up by the customer.

Customer and merchant location-based ETA determination

A customer may place an order for items to be picked up at a merchant location. Upon receiving an indication that the customer is initiating travel to the merchant location to pick up the items, multiple ETA data points for the customer may be determined while the customer is in transit to the merchant location. Based on the ETA data, it may be determined that the customer is likely to arrive after the merchant location closes, which may prevent the customer from being able to pick up the items from the merchant location. Alternative fulfillment options may be presented to the customer to enable the customer to obtain the items. The alternative fulfillment options may include picking up the items at an alternative merchant location, scheduling a delivery of the items, picking up the items from the merchant location at a subsequent time, or facilitating a cancelation of the order.

ETA-based item pick-up and fulfillment alternatives

Upon receiving an indication that a customer is initiating travel to a merchant location to pick up one or more items, sensor data may be obtained by, and received from, a customer device of the customer. After the customer has arrived at the merchant location, the customer may be greeted or otherwise interacted with and a corresponding interaction time may be determined. The service provider may identify one or more stop events based on the sensor data, where a stop event indicates that a customer stopped while in transit to the merchant location. A most recent stop event prior to the interaction time may constitute the customer arriving/stopping at the merchant location, and a corresponding arrival time may be estimated. A wait time of the customer may be determined based on a difference between the interaction time and the arrival time.

Sensor-based customer arrival detection

Systems and associated methods are disclosed for automatically configuring cameras to be associated with a known physical location in response to exposing the camera to a fiducial marker. In certain embodiments, boundaries for a zone of interest within images from the camera can be defined using the fiducial markers physically placed within the physical space.

Automatic camera configuration using a fiducial marker

Systems and associated methods are disclosed to reduce wait time experienced by customers during order fulfillment and pick-up. The system utilizes cameras and automatic license plate recognition (ALPR) to quickly identify vehicles associated with customer accounts and pending pick-up orders upon arrival. Proximity detectors provide an additional layer of vehicle detection. A concierge tool provides manual inputs from a user relating to vehicle or customer status. The system provides for synthesis and fusion of these diverse input types to accurately detect and identify arriving and departing customers.

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Brisbane, Australia

Alexander Edwards