Sensor Selection for Power Reduction in Information Processing
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Solution Overview
Problem
Existing information processing apparatuses with multiple sensors face challenges in reducing power consumption during simultaneous sensing operations, particularly in portable terminal equipment.
Innovation Solution
An information processing apparatus that includes an identification processing section to identify the subject for sensing based on sensing information from multiple sensors, and a control section to selectively drive sensors for obtaining new sensing information, optimizing power usage by limiting sensor activation to only those necessary for the identified subject.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple sensors are driven simultaneously to obtain sensing information, then the sensing capability and measurement precision are improved, but the power consumption increases
Solution Approach 1:
The patent implements dynamic sensor selection where the control section determines which sensors to activate based on real-time sensing requirements. The system transitions from a static all-sensors-on approach to a dynamic selective activation approach, where sensors are enabled or disabled according to the specific sensing task at hand, thereby optimizing power consumption while maintaining measurement precision.
Solution Approach 2:
The patent changes the operational parameters of the sensor system by introducing variable sensor activation states. Instead of maintaining a fixed configuration where all sensors are always active, the system varies the activation state of individual sensors based on the identified subject and sensing requirements, achieving a balance between sensing capability and power consumption.
2Reliability
If all sensors are activated for sensing, then the reliability and accuracy of subject identification are improved, but the amount of data and processing requirements increase
Solution Approach 1:
The patent extracts only the necessary sensing information by selectively activating specific sensors based on the identified subject type. Instead of collecting data from all sensors regardless of relevance, the system extracts and processes only the sensing data required for the current sensing task, reducing data volume while maintaining identification accuracy.
Solution Approach 2:
The patent applies partial action by activating only the subset of sensors needed for the current sensing requirement rather than all sensors. The control section determines the appropriate level of sensing action based on the subject type, enabling partial sensor activation that suffices for reliable identification without the excess data generation of full-sensor activation.
3Adaptability or versatility
If multiple sensors operate simultaneously, then the versatility of sensing applications is improved, but the heat generation and electromagnetic noise increase
Solution Approach 1:
The patent implements dynamic sensor selection where the control section determines which sensors to activate based on real-time sensing requirements. The system transitions from a static all-sensors-on approach to a dynamic selective activation approach, where sensors are enabled or disabled according to the specific sensing task at hand, thereby optimizing power consumption while maintaining measurement precision.
Solution Approach 2:
The patent changes the operational parameters of the sensor system by introducing variable sensor activation states. Instead of maintaining a fixed configuration where all sensors are always active, the system varies the activation state of individual sensors based on the identified subject and sensing requirements, achieving a balance between sensing capability and power consumption.
Data Source
AI summary
An information processing apparatus includes an identification processing section identifying a subject for sensing on the basis of pieces of sensing information obtained from at least some of multiple sensors, and a control section selecting a sensor for obtaining new sensing information from among the multiple sensors.


