Device Context Determination Using Probabilistic Sensor Fusion
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Solution Overview
Problem
Combining sensor measurements and system signals to determine device context is complex and inefficient, and not all devices have access to the same set of signals, necessitating an efficient method to acquire relevant information for context awareness.
Innovation Solution
A method that involves obtaining sensor measurements and system signals using a probabilistic model to generate outputs indicating changes in usage patterns, allowing devices to record additional data or cease unnecessary data recording, thereby improving accuracy and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sensor measurements and system signals are combined to determine device context, then context awareness accuracy is improved, but system complexity increases
Solution Approach 1:
The patent segments the context determination process into distinct modules: sensor measurement acquisition, system signal acquisition, probabilistic model processing, and context determination. Each module handles specific tasks independently, reducing overall system complexity while maintaining accurate context awareness through coordinated operation of these segmented components.
Solution Approach 2:
The patent introduces a probabilistic model as an intermediary layer between raw sensor measurements/system signals and final context determination. This intermediary processes and integrates multiple input sources, transforming complex raw data into meaningful context information, thereby improving accuracy while managing system complexity through structured intermediate processing.
2Measurement precision
If comprehensive sensor measurements and system signals are processed, then device context accuracy is improved, but energy consumption increases
Solution Approach 1:
The patent implements partial action by selectively processing only the necessary subset of sensor measurements and system signals required for current context determination, rather than continuously processing all available data. The system adjusts processing intensity based on context requirements, reducing energy consumption while maintaining sufficient accuracy for the given usage scenario.
Solution Approach 2:
The patent changes processing parameters dynamically based on device state and context requirements. The probabilistic model adjusts which sensors are activated, what sampling rates are used, and which system signals are processed, thereby optimizing the balance between context accuracy and energy consumption according to current operational needs.
3Productivity
If device adjusts operation based on context information, then operational efficiency is improved, but system complexity increases
Solution Approach 1:
The patent implements self-service by enabling the device to automatically adjust its operation based on determined context information without requiring external control. The system autonomously modifies sensor activation, processing intensity, and operational modes according to detected usage patterns and environmental conditions, improving efficiency while managing complexity through automated decision-making algorithms.
Data Source
AI summary
A processing apparatus including one or more processors and memory obtains one or more sensor measurements generated by one or more monitoring sensors of one or more devices, including one or more monitoring sensor measurements from a respective monitoring sensor of a respective device and obtains one or more system signals including a respective system signal corresponding to current operation of the respective device. The processing apparatus determines device context information for the respective device based on the one or more sensor measurements and the one or more system signals and adjusts operation of the device in accordance with the device context information.