Google llc (20240127808). AUTOMATED ASSISTANT THAT UTILIZES RADAR DATA TO DETERMINE USER PRESENCE AND VIRTUALLY SEGMENT AN ENVIRONMENT simplified abstract
Contents
- 1 AUTOMATED ASSISTANT THAT UTILIZES RADAR DATA TO DETERMINE USER PRESENCE AND VIRTUALLY SEGMENT AN ENVIRONMENT
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 AUTOMATED ASSISTANT THAT UTILIZES RADAR DATA TO DETERMINE USER PRESENCE AND VIRTUALLY SEGMENT AN ENVIRONMENT - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Original Abstract Submitted
AUTOMATED ASSISTANT THAT UTILIZES RADAR DATA TO DETERMINE USER PRESENCE AND VIRTUALLY SEGMENT AN ENVIRONMENT
Organization Name
Inventor(s)
Varn Khanna of Vallejo CA (US)
Chintan Trehan of San Jose CA (US)
AUTOMATED ASSISTANT THAT UTILIZES RADAR DATA TO DETERMINE USER PRESENCE AND VIRTUALLY SEGMENT AN ENVIRONMENT - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240127808 titled 'AUTOMATED ASSISTANT THAT UTILIZES RADAR DATA TO DETERMINE USER PRESENCE AND VIRTUALLY SEGMENT AN ENVIRONMENT
Simplified Explanation
The patent application describes an automated assistant that can adjust its responses based on radar data indicating user presence in different segments of an environment. This allows for more accurate and contextually relevant interactions with users.
- Automated assistant adjusts responses based on radar data indicating user presence
- Virtual segmentation of environment enables application of specific operational parameters
- Input detection features can be enabled for segmented portions where users are detected
- Parameters like confidence thresholds and speech processing biasing can be customized for different segments
Potential Applications
This technology could be applied in smart home devices, virtual assistants, security systems, and automated customer service platforms.
Problems Solved
This technology helps mitigate false positives in detecting user presence and improves the accuracy of responses in dynamic environments.
Benefits
- Enhanced user experience with personalized and context-aware interactions - Improved efficiency in responding to user inputs - Better utilization of resources by focusing on relevant segments of the environment
Potential Commercial Applications
- Home automation systems - Virtual assistant devices - Security and surveillance systems - Customer service chatbots
Possible Prior Art
One possible prior art could be the use of motion sensors in smart home devices to detect user presence and adjust settings accordingly.
What are the specific operational parameters that can be applied to different segments of the environment?
The specific operational parameters that can be applied to different segments of the environment include enabling input detection features, adjusting confidence thresholds, and biasing speech processing for more accurate responses.
How does the automated assistant determine which segment of the environment to apply certain operational parameters?
The automated assistant determines which segment of the environment to apply certain operational parameters based on radar data indicating user presence in that particular segment. By virtually segmenting the environment, the assistant can tailor its responses accordingly.
Original Abstract Submitted
implementations relate to an automated assistant that can determine whether to respond to inputs in an environment according to whether radar data indicates a user is present. when user presence is detected, the automated assistant can virtually segment the environment and apply certain operational parameters to certain segments of the environment. for instance, the automated assistant can enable an input detection feature, such as warm word detection, for a segmented portion of the environment in which a user is detected. in this way, false positives can be mitigated for instances in which environmental and/or user sounds are detected by the automated assistant but do not originate from a particular segment of the environment. other parameters, such as varying confidence thresholds and/or speech processing biasing, can be temporarily enforced for different segments of an environment in which a user is detected.
