Amazon Technologies, Inc.

Microsoft Technology Licensing, LLC

George Strajan

William Evan Welbourne

Sara Parker Hillenmeyer

Charles Edwin Ashton Brett

Aniruddha Basak

Hongyang Wang

Hersh Sridhar Iyer

Akshay Kumar

Yu Liu

Paul Aksenti Savastinuk

Suriya Narayanan

Nitinkumar Shah

Tomasz Kaminski

Robert Badawy

Kunal Pramod Ghogale

Ian Beck

Amir Salimi

Sunny Singh

Marc Wetter

Chandra Prakash Konkimalla

Yishuai Li

Dustin D Clark

Devin Leslie Carraway

Zhaoqi Chen

Suresh Kumar Reddy Kotapalle

Tushar Joshi

Meet Prakash Vadera

Siyuan Liu

Arpit Jain

Rajesh Bangaru Ravindranath

Kathleen Patricia Champion

Giuseppe Leonardo Mancone

Systems and methods for dynamic smart device demonstration include receiving a user request to initiate a smart device demonstration. Device groups for the devices in the environment in question are determined and/or generated and utilized to determine what devices and functionalities are to be included in a given smart device demonstration. Then data representing device functionality descriptions are utilized to output those descriptions in synchronization with device state transitions of the smart devices, which demonstrate the described functionality.

Dynamic smart device demonstration

Systems and methods for usage-based device naming and grouping are disclosed. For example, trigger events that indicate when a device should be renamed, added to a device group, and/or added to a routine may be determined. Usage data representing usage of the device may be received and utilized to determine if a trigger event occurs. When a trigger event occurs, a recommendation for renaming, grouping, etc. may be determined and sent to a user device. Upon acceptance of the recommendation, the device may be renamed, grouped, and/or added to a routine.

Usage-based device naming and grouping

Systems and methods for activity-based device recommendations are disclosed. For example, historical usage data associated with a device may indicate that the device is likely to be associated with a given state at a given time. When the device is not in the anticipated state, a recommendation to transition the device state, for example, may be sent. Additionally, a determination of the activity state associated with the device, such as an active state, an asleep state, and/or an away state may be utilized to determine the recommendation to surface, to determine whether to send a recommendation, and when and/or how to send the recommendation.

Activity-based device recommendations

Systems and methods for device control using near real time learning are disclosed. For example, an automatic action is performed by a target device in response to a predefined condition being met. Thereafter, context data is gathered and utilized to determine whether a negative user reaction has been provided in response to performance of the automatic action. When a negative user reaction is determined, mitigating actions may be taken close in time to when the context data is received to prevent further negative user reactions.

Device control using near real time modeling

A development system comprises, in one example, a customization component configured to detect user development inputs to develop elements of a computing system, the elements comprising types modeled in the computing system, a display system configured to generate user interface displays, and a visualization system configured to identify a set of customized elements, a set of non-customized elements, and a customization type for each of the customized elements. The visualization system comprises a display system controller configured to control the display system to generate an integrated view user interface display that visually distinguishes the set of customized elements from the set of non-customized elements and indicates the customization types for the customized elements.

Visualization framework for customizable types in a development environment

Growing community of inventors

Seattle, WA, United States of America

George Strajan