Apple inc. (20240104907). DATA SELECTION simplified abstract
Contents
DATA SELECTION
Organization Name
Inventor(s)
Fernando A. Mujica of Los Altos CA (US)
Vijay Srivatsan of Los Altos CA (US)
Muhammad Umair Siddique of Kanata (CA)
DATA SELECTION - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240104907 titled 'DATA SELECTION
Simplified Explanation
The present disclosure relates to techniques for determining whether to use sensor fusion and/or a voting mechanism based on select data, such as sensor data and/or depth values.
- Sensor fusion is a method of combining data from multiple sensors to improve accuracy and reliability.
- A voting mechanism involves multiple sensors making independent decisions and then combining those decisions to reach a final result.
- Different types of decisions may require different responses, such as prioritizing one sensor over another based on the situation.
Potential Applications
This technology could be applied in various fields such as autonomous vehicles, robotics, and augmented reality systems where accurate and reliable sensor data is crucial.
Problems Solved
This technology helps in improving the accuracy and reliability of data by utilizing sensor fusion and voting mechanisms, leading to better decision-making processes.
Benefits
The benefits of this technology include enhanced data accuracy, improved decision-making capabilities, and increased reliability in various applications.
Potential Commercial Applications
Potential commercial applications of this technology include autonomous vehicles, industrial automation, smart home systems, and healthcare devices.
Possible Prior Art
One example of prior art in this field is the use of sensor fusion in navigation systems to improve accuracy and reliability of location data.
What are the specific techniques used for determining whether to use sensor fusion in this technology?
The specific techniques used for determining whether to use sensor fusion in this technology involve analyzing the quality and reliability of sensor data, comparing the data from multiple sensors, and assessing the benefits of combining the data for improved accuracy.
How does this technology address the issue of conflicting sensor data in decision-making processes?
This technology addresses the issue of conflicting sensor data in decision-making processes by implementing a voting mechanism where multiple sensors make independent decisions and then combine those decisions to reach a final result. This helps in resolving conflicts and improving the overall reliability of the decision-making process.
Original Abstract Submitted
the present disclosure generally relates select data (e.g., sensor data and/or depth values generated using sensor data). in some examples, techniques for determining whether to use sensor fusion are provided. in some examples, techniques for determining whether to use a voting mechanism are provided. in some examples, techniques for responding to different types of decisions are provided.
