Intel corporation (20240320164). METHODS AND APPARATUS TO AUTOMATICALLY PROVISION PERIPHERAL DATA simplified abstract
Contents
- 1 METHODS AND APPARATUS TO AUTOMATICALLY PROVISION PERIPHERAL DATA
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 METHODS AND APPARATUS TO AUTOMATICALLY PROVISION PERIPHERAL DATA - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Key Features and Innovation
- 1.6 Potential Applications
- 1.7 Problems Solved
- 1.8 Benefits
- 1.9 Commercial Applications
- 1.10 Questions about Automatic Provisional Peripheral Data
- 1.11 Original Abstract Submitted
METHODS AND APPARATUS TO AUTOMATICALLY PROVISION PERIPHERAL DATA
Organization Name
Inventor(s)
Sean J. W. Lawrence of Bangalore (IN)
Peter Mark Ewert of Hillsboro OR (US)
Sajal Kumar Das of Bangalore (IN)
Sathyanarayana Nujella of Fremont CA (US)
Srikanth Potluri of Folsom CA (US)
METHODS AND APPARATUS TO AUTOMATICALLY PROVISION PERIPHERAL DATA - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240320164 titled 'METHODS AND APPARATUS TO AUTOMATICALLY PROVISION PERIPHERAL DATA
Simplified Explanation
The patent application describes methods and systems for automatically selecting and forwarding input signals from peripheral devices to specific applications based on context information.
- Uses machine learning model to select between different applications based on context information.
- Automatically forwards input signals from peripheral devices to the selected application.
Key Features and Innovation
- Utilization of machine learning model for application selection.
- Automatic provisioning of peripheral data based on context information.
Potential Applications
- Smart home automation systems.
- Industrial automation processes.
- Personalized user interfaces for electronic devices.
Problems Solved
- Streamlining the process of handling input signals from peripheral devices.
- Enhancing user experience by automatically directing input signals to relevant applications.
Benefits
- Improved efficiency in processing peripheral data.
- Enhanced user interaction with electronic devices.
- Personalized and context-aware application selection.
Commercial Applications
Automatic Application Selection System for Peripheral Devices: Enhancing User Experience and Efficiency This technology can be utilized in various industries such as smart home automation, industrial automation, and consumer electronics to streamline the handling of input signals from peripheral devices, improving user experience and efficiency.
Questions about Automatic Provisional Peripheral Data
How does the machine learning model determine which application to select based on context information?
The machine learning model analyzes the context information associated with the applications and input signals to make an informed decision on which application to select.
What are the potential implications of this technology in the consumer electronics market?
This technology can lead to the development of more intuitive and user-friendly electronic devices, enhancing user experience and increasing efficiency in handling peripheral data.
Original Abstract Submitted
methods, apparatus, systems, and articles of manufacture to automatically provisional peripheral data are disclosed. an example apparatus includes at least one programmable circuit to use a machine learning model to select a first application or a second application based on context information associated with at least one of the first application, the second application, or an input signal from a peripheral device; and forward the input signal to the selected one of the first application or the second application.
