Amazon Technologies, Inc.

Jay Patel

William Evan Welbourne

Sven Eberhardt

Charles Edwin Ashton Brett

Aniruddha Basak

Sara Parker Hillenmeyer

Lizhen Peng

Zeya Chen

Yunfeng Jiang

Akshay Kumar

Hongyang Wang

Vinay Kotikalapudi Sriram

Systems and methods for intelligent device grouping are disclosed. An environment, such as a home, may have a number of voice-enabled devices and accessory devices that may be controlled by the voice-enabled devices. One or more models, such as linguistics model(s) and/or device affinity models may be utilized to determine which accessory devices are candidates for inclusion in a device group, and a recommendation for grouping the devices may be provided. Device-group naming recommendations may also be generated and may be sent to users.

Intelligent device grouping

This disclosure describes, in part, techniques for utilizing global models to generate local models for electronic devices in an environment, and techniques for utilizing the global models and/or the local models to provide notifications that are based on anomalies detected within the environment. For instance, a remote system may receive an identifier associated with an electronic device and identify a global model using the identifier. The remote system may then receive data indicating state changes of the electronic device and use the data and the global model to generate a local model associated with the electronic device. Using the global model and/or local model, the remote system can identify anomalies associated with the electronic device and, in response to identifying an anomaly, notify the user. The remote system can further cause the electronic device to change states after receiving a request from the user.

State detection and responses for electronic devices

Described are systems, methods, and apparatus that gathers environment condition data from different sensors at various locations within an area, aggregates the environment condition data to produce aggregated environment condition scores for the area and provides the aggregated environment condition scores to different locations within the area. While sensor data from a single sensor/device, such as a camera may provide low quality environment information, by collecting and aggregating information from multiple sensors and/or locations in the area, highly accurate aggregated environment condition scores for environment conditions may be realized. The aggregated environment condition scores may be provided to various locations within the area as representative of the environment condition at that point in time within the area, regardless of whether those locations have sensors. The aggregated environment condition scores may be used by other devices at those locations to automate one or more actions, such as adjusting lighting conditions, closing garage doors, adjusting window blind positions, etc.

Aggregating sensor data for environment conditions

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Seattle, WA, United States of America

Jay Patel