Context-Aware Sensor Fusion Module for Selective Disabling
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Solution Overview
Problem
Current sensor fusion modules in information handling devices consume excessive battery power and processing resources, are fragile, and often execute functions unintentionally due to global power management schemes that do not account for specific device contexts, leading to inefficient resource usage and potential sensor damage.
Innovation Solution
A context-aware fusion module that selectively disables sensors based on input from various sensors, such as a dynamometer and gyrometer, to manage device state and prevent unnecessary resource consumption and sensor damage, by mapping sensor inputs to specific disabling conditions and implementing appropriate actions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sensors are continuously active to provide comprehensive sensor fusion data, then measurement precision and application performance are improved, but energy consumption and processing resource usage increase
Solution Approach 1:
The system dynamically adjusts sensor operation states based on real-time device context. The fusion module continuously monitors device state (e.g., stationary, being carried, orientation) and selectively activates or deactivates sensors accordingly, transforming the static sensor activation model into a dynamic one that adapts to changing conditions.
Solution Approach 2:
Different sensors are selectively enabled or disabled based on specific device states and contextual requirements. Instead of uniformly activating all sensors, the system applies local quality by tailoring sensor activation to specific situations—for example, enabling the camera only when the device is detected to be held horizontally, or disabling the microphone when the device is in a closed state.
2Ease of operation
If global power management schemes are used to control sensors, then ease of operation is improved, but reliability deteriorates due to fragile and unintentional function execution
Solution Approach 1:
The fusion module implements continuous feedback by monitoring device state through sensor inputs and adjusting sensor activation accordingly. The system creates a closed-loop control mechanism where sensor data feeds back into the decision-making process for sensor activation, enabling the system to respond appropriately to changing conditions and avoid fragile, unintentional function execution.
Solution Approach 2:
The fusion module autonomously manages sensor activation without requiring explicit user intervention. The system self-services by automatically determining which sensors should be active based on device state and contextual information, making power management decisions independently while improving reliability through context-aware logic.
3Measurement precision
If all sensors remain active to ensure no data is missed, then measurement precision is improved, but loss of energy increases due to unnecessary resource consumption
Solution Approach 1:
The system applies partial action by activating only the subset of sensors necessary for the current device state and application requirements. Instead of maintaining all sensors in an active state, the fusion module selectively enables sensors based on contextual needs, performing just enough sensing to maintain measurement precision while avoiding excessive energy consumption from unnecessary sensor operation.
Data Source
AI summary
An embodiment provides a method, including: receiving, at an information handling device, input of a sensor; mapping, using a processor, the sensor input to a sensor disabling condition; selecting, using a processor, a sensor based on the mapping; and disabling, using a processor, the sensor according to the sensor disabling condition. Other aspects are described and claimed.