Amazon Technologies, Inc.

Hannah McClellan Richards

Samuel Stevens Heyworth

Amirali Virani

Douglas James Herrington

Nirav Praful Desai

Marc Brandon Hensley

Daniel Benjamin Rausch

Stephan Josef Andrizzi

Nicole Dare

Jai Prakash Chabria

Paul Warren Smart

Apoorva Iyer

Amir Pelleg

Laura Allison Ridlehoover

Jeffrey Rosenberg

Nitish Kumar

Jessica Protasio

Kenneth DeLand

Anindya Guha

Dave Jonathan Lefkow

Jae Pum Park

John B Shaw

Kara Cavallaro

David C Buuck

Charles Robert Watson

Daniel Osias

Lara Marie Sosnosky

Ivy Cunningham

Liza Marie Walsh

Jeff Gelfuso

Allison Kramer

Devon Merritt

Jon Appleby

Christa Stephens Glenn

Avani Parakh

Ivan Loughlen

Melissa Leigh Allen-Arredondo

Brett David Tracy

Heather Zorn

Joshua Golden Edwards

Lindsey Ann Bauer

Techniques for selecting a delivery method based on sensor data of an automatic replenishment device (ARD) are described. In an example, a computer system is communicatively coupled with the ARD and receives the sensor data from the ARD. The sensor data is generated by a sensor of the ARD and indicates an amount of an item that is stored by the ARD. The computer system maintains, in a profile, a consumption rate based on the sensor data. The computer system determines that the amount of the item is less than a threshold amount based on the consumption rate and, based on this amount, identifies available delivery methods for a delivery of a replacement amount of the item. The computer system selects one of the delivery methods based on the consumption rate and causes the delivery of the replacement amount of the item based on the selected delivery method.

Managing shipments based on data from a sensor-based automatic replenishment device

The disclosed techniques relate to improving sensor data collection/reporting at an automatic replenishment device (ARD). For example, sensor data associated with the item stored at an ARD may be collected. The ARD can calculate a change in the amount of the item stored by the ARD from the sensor data. If the change is over a reporting threshold, the sensor data (or the amount of change) may be transmitted to a back-end system. Reporting may not occur if additional sensor data (e.g., accelerometer data and/or images captured at the ARD) is not commensurate with a user interaction. If the difference is under the reporting threshold or unlikely due to user interaction, the ARD may refrain from transmitting the sensor data. These techniques conserves power at the ARD, relieves the back-end system from needless processing, and enables more accurate indications of the amount of the item stored by the ARD.

Sensor-related improvements to automatic replenishment devices

Systems, methods, and computer-readable media are described for creating custom user interface ('UI') controls. A networked computing service may determine that an action performed by a user of the service is likely to be repeated, based on previous actions performed by the user and/or other users, parameters of the action including characteristics of an item associated with the action, and other criteria. The networked computing service may generate, or recommend generation of, a custom UI control that automates performance of the action. The networked computing service may automatically determine parameters of the action, and may determine alternative parameters and/or alternative actions if the action cannot be performed using the determined parameters. Custom UI controls may be associated with various computing devices and/or other electronic devices, and categories of custom UI controls may be determined and displayed.

Creation of custom user interface controls that are associated with physical devices

Utilizing the techniques disclosed herein, sensor data inaccuracies may be corrected such that calculated fill levels more accurately reflect the actual fill level of the item within an automatic replenishment device (ARD). For example, the ARD may include a sensor configured to collect the sensor data (e.g., a distance between the sensor and an item contained within the ARD). Sensor data associated with an item within the ARD may be received. A measurement offset value specific to the item may be identified. An estimated fill level of the item within the ARD may be calculated based at least in part on the distance measured between the sensor and the item and the measurement offset value specific to the item.

Product specific correction for a sensor-based device

A reorder device having an item tag reader and one or more sensors may facilitate the automatic reordering of an item for a customer. The item may be associated with an item tag that is placed on (or near) the reorder device. The reorder device may detect the item tag and transmit such data to an entity device, which may associate the reorder device and the item. The reorder device may periodically obtain weight measurements of the item that is placed on the reorder device, as well as a timestamp that indicates a time at which the weight measurements are obtained. Such data may be provided to the entity device, and an entity associated with the entity device may determine whether weight measurement satisfies an item threshold value. If so, additional inventory of the item may be ordered and delivered to the customer, without additional input from the customer.

Sensor data-based reordering of items

Techniques for consolidation of items based on sensor data is provided. For example, an amount of an item may be identified using an electronic sensor associated with an automatic replenishment device. When the amount of the item is greater than a first reorder threshold, the item may not be ordered on behalf of the user until the amount of the item reaches the first reorder threshold. However, when an order for a different item is placed, either by accessing a network document to proactively order the different item or through a reorder schedule based on a consumption rate of the different item, the amount of the first item may be compared with a second reorder threshold. When the amount of the first item is less than the second reorder threshold, a notification may be provided to the user for additionally ordering the second item with the first item.

Predictive consolidation system based on sensor data

Systems, methods, and computer-readable media are described for performing actions based on user activation of custom user interface ('UI') controls. A user of a networked computing service may activate a custom UI control by selecting the custom UI control (such as by touching the custom UI control displayed on a touchscreen display) to trigger the networked computing service to perform a predefined action associated with the custom UI control. In the event that the predefined action cannot be performed, the networked computing service may identify an alternative action that may be performed instead of the predefined action, optionally request user confirmation of the alternative action, and perform the alternative action.

Adaptive performance of actions associated with custom user interface controls

Systems, methods, and computer-readable media are described for selecting and displaying custom user interface ('UI') controls. A user of a networked computing service may create custom UI controls that perform user-specified actions, and the networked computing service may present these custom UI controls as part of its user interface. The networked computing service may determine which of a set of custom UI controls to present based on criteria such as frequency or recency of recurring usage, a context or a category associated with the custom UI controls, user preferences, the status of a pending action, usage of similar custom UI controls by other users, or other criteria. The networked computing service may present an interface that enables further customization or modification of the custom UI controls.

Growing community of inventors

Seattle, WA, United States of America

Hannah McClellan Richards