Behavioral Processing Unit for Real-Time Operator State Analysis
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Solution Overview
Problem
Processing signals and states representative of diverse content in computing devices is resource-demanding, leading to increased processing time, storage demands, and complexity, particularly in applications involving human decision-making based on operator's physical, mental, and emotional states.
Innovation Solution
Incorporation of a behavioral processing unit (BPU) with machine learning acceleration circuitry to efficiently process sensor data and generate behavioral profile content, reducing the burden on general-purpose processors by handling operations on larger parameter sets, such as neural networks, and providing real-time decision-making support.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Power
If general-purpose processors process sensor data and behavioral content, then processing capability is provided, but processing time and resource consumption increase
Solution Approach 1:
The patent divides the processing system into two segments: a behavioral processing unit (BPU) specialized for behavioral content and sensor data processing, and a general-purpose processor for other tasks. This segmentation allows the BPU to handle specific processing tasks efficiently while reducing the burden on the general-purpose processor, thereby decreasing overall processing time and resource consumption.
Solution Approach 2:
The BPU acts as an intermediary between sensors and the general-purpose processor. It pre-processes sensor data and generates behavioral profile content before passing results to the general-purpose processor, reducing the amount of data and computational load that the general-purpose processor must handle, thus improving processing efficiency.
2Measurement precision
If comprehensive sensor data processing is performed, then behavioral profile accuracy improves, but device complexity increases
Solution Approach 1:
The BPU serves as an intermediary that handles the complexity of comprehensive sensor data processing and machine learning operations. By offloading these complex tasks to the specialized BPU, the system achieves high behavioral profile accuracy without significantly increasing the complexity burden on the overall device architecture.
Solution Approach 2:
The patent replaces general-purpose computational mechanics with specialized hardware mechanics in the BPU. The BPU uses dedicated circuitry and machine learning acceleration techniques to perform complex behavioral analysis, substituting software-based processing on general-purpose processors with hardware-based specialized processing, thereby improving accuracy while managing device complexity.
3Adaptability or versatility
If machine learning operations on large parameter sets are performed, then behavioral analysis capability improves, but processing speed decreases
Solution Approach 1:
The BPU replaces software-based machine learning operations on general-purpose processors with hardware-based machine learning acceleration circuitry. This substitution enables efficient processing of large parameter sets and complex neural network operations, maintaining high behavioral analysis capability while achieving real-time processing speeds through specialized hardware optimization.
Solution Approach 2:
The BPU changes the operational parameters of processing by using dedicated hardware circuits optimized for specific machine learning operations. This allows parallel processing of multiple parameters simultaneously, changing the processing mode from sequential software execution to parallel hardware execution, thereby improving processing speed while maintaining comprehensive behavioral analysis capability.
Data Source
AI summary
Subject matter disclosed herein may relate to systems, devices, and/or processes for processing signals and/or states representative of behavioral content in a computing device.