Proximity Sensor Segmentation for Electronic Device Intention Recognition
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Solution Overview
Problem
Current electronic devices lack an effective method to recognize the proximity intention of external objects and perform operations accordingly, relying on limited sensing capabilities and modes.
Innovation Solution
An electronic device equipped with multiple sensors and a processor that determines proximity states using different sensor sets in various modes, allowing for detailed proximity analysis and intention recognition, enabling context-based operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple sensor sets are used to determine detailed proximity states, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The sensor system is segmented into multiple sensor sets (first sensor set, second sensor set, third sensor set) that are activated at different stages of proximity detection. The first sensor set determines initial proximity state, the second sensor set determines detailed proximity state when external object is in first proximity region, and the third sensor set determines detailed proximity state when external object is in second proximity region. This segmentation allows high measurement precision through specialized sensors for each detection stage while managing overall system complexity.
Solution Approach 2:
The sensor system dynamically switches between different sensor sets based on the detected proximity state. When the external object enters the first proximity region, the system transitions from the first sensor set to the second sensor set. When the external object enters the second proximity region, the system transitions to the third sensor set. This dynamic adaptation enables high measurement precision for detailed proximity detection while reducing complexity by only activating relevant sensors for each state.
2Adaptability or versatility
If different sensor sets are activated based on proximity state, then adaptability is improved, but device complexity increases
Solution Approach 1:
The system dynamically adapts sensor activation based on detected proximity states. The processor determines the proximity state using the first sensor set, then selectively activates the second sensor set when the external object is in the first proximity region, and activates the third sensor set when the external object is in the second proximity region. This dynamic adaptation enhances versatility for different proximity scenarios while managing control complexity through state-based decision logic.
Solution Approach 2:
The system changes the operational parameters of the sensor system based on proximity state. Different sensor sets are selected and activated depending on whether the external object is in the first proximity region or the second proximity region. This parameter change approach enables high adaptability to different proximity conditions while controlling complexity through predefined state transitions.
3Measurement precision
If detailed proximity state determination is performed for all external objects, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The proximity detection process is segmented into sequential stages: first determining proximity state with the first sensor set, then determining detailed proximity state with the second sensor set only when needed, and finally determining detailed proximity state with the third sensor set when the external object is in the second proximity region. This segmentation achieves high measurement precision for detailed proximity detection while minimizing time loss by avoiding unnecessary detailed detection for all external objects.
Solution Approach 2:
The system performs preliminary action by first determining the proximity state using the first sensor set before activating more complex sensor sets for detailed measurement. This preliminary detection stage filters out external objects that do not require detailed proximity analysis, thereby achieving high measurement precision when needed while reducing overall detection time by avoiding unnecessary detailed measurement for all objects.
Data Source
AI summary
Provided are an electronic device and method for performing an operation based on proximity of an external object with respect to the electronic device. In an embodiment, an electronic device includes a plurality of sensors including first, second, and third sensor sets. A processor configured to determine a proximity state of an external object using the first sensor set, wherein the proximity state indicates whether the external object exists near the electronic device and includes a first proximity state and a second proximity state. In response to the external object being in the first proximity state, determine a detailed proximity state of the external object using the second sensor set, and in response to the external object being in the second proximity state, determine the detailed proximity state of the external object with respect to the electronic device using the third sensor set.