Intel corporation (20240185129). METHODS AND APPARATUS TO FACILITATE COLLABORATIVE LEARNING IN A MULTI-SENSOR ENVIRONMENT simplified abstract
Contents
- 1 METHODS AND APPARATUS TO FACILITATE COLLABORATIVE LEARNING IN A MULTI-SENSOR ENVIRONMENT
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 METHODS AND APPARATUS TO FACILITATE COLLABORATIVE LEARNING IN A MULTI-SENSOR 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 What are the limitations of this technology in real-world applications?
- 1.11 How does this technology compare to existing solutions for collaborative learning in multi-sensor environments?
- 1.12 Original Abstract Submitted
METHODS AND APPARATUS TO FACILITATE COLLABORATIVE LEARNING IN A MULTI-SENSOR ENVIRONMENT
Organization Name
Inventor(s)
Priyanka Mudgal of Portland OR (US)
Caleb Mark Mcmillan of Forest Grove OR (US)
Rita Hanna Wouhaybi of Portland OR (US)
Mark David Yarvis of Portland OR (US)
Jennifer Williams of Hillsboro OR (US)
Greeshma Pisharody of Portland OR (US)
METHODS AND APPARATUS TO FACILITATE COLLABORATIVE LEARNING IN A MULTI-SENSOR ENVIRONMENT - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240185129 titled 'METHODS AND APPARATUS TO FACILITATE COLLABORATIVE LEARNING IN A MULTI-SENSOR ENVIRONMENT
Simplified Explanation
The abstract of the patent application describes methods, apparatus, systems, and articles of manufacture for facilitating collaborative learning in a multi-sensor environment. The example computer-readable medium includes instructions for validating and mitigating conflicting data from different devices.
- The patent application involves facilitating collaborative learning in a multi-sensor environment.
- The computer-readable medium contains instructions for validating one device based on data from another validated device.
- It also includes instructions for mitigating conflicting data from a second device based on the validated data.
Potential Applications
This technology could be applied in educational settings, virtual reality environments, and collaborative workspaces.
Problems Solved
This technology solves the problem of conflicting data from multiple devices in a collaborative learning environment.
Benefits
The benefits of this technology include improved collaboration, enhanced learning experiences, and more efficient data management in multi-sensor environments.
Potential Commercial Applications
Potential commercial applications of this technology include educational software, virtual reality platforms, and collaborative work tools.
Possible Prior Art
One possible prior art for this technology could be existing collaborative learning platforms that do not address conflicting data from multiple devices effectively.
What are the limitations of this technology in real-world applications?
One limitation of this technology in real-world applications could be the need for compatible devices and sensors to ensure seamless collaboration and data validation.
How does this technology compare to existing solutions for collaborative learning in multi-sensor environments?
This technology offers a more efficient and effective way to manage conflicting data from different devices in a collaborative learning environment compared to existing solutions.
Original Abstract Submitted
methods, apparatus, systems, and articles of manufacture to facilitate collaborative learning in a multi-sensor environment are disclosed. an example computer readable medium comprises instructions at least one programmable circuit to after determining that first data from a first device conflicts with second data from a second device: validate the first device based on third data from a validated device; and mitigate the second device based on the third data.
