Actor Type Detection via Sensor Variance Analysis
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Solution Overview
Problem
The integration of IoT devices into everyday life raises security and safety concerns due to the inability to distinguish between human and machine control, leading to potential misuse and discomfort among humans interacting with automated systems.
Innovation Solution
A method using sensors to monitor activity performance, compare it to machine-generated reference readings, and determine the type of actor based on variance analysis, with the option to simulate human behavior by adding random elements to machine behavior, enhancing security and user comfort.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If devices are made more automated to improve efficiency and economic benefit, then productivity increases, but security and safety issues arise due to inability to distinguish machine from human control
Solution Approach 1:
The system changes the 'behavioral signature' characteristics of machine operations by adding randomized elements, making machine behavior indistinguishable from human behavior. This allows automated devices to maintain high productivity while appearing to be under human control, thus resolving the security concern without reducing efficiency
Solution Approach 2:
The system creates a copy of human behavioral patterns by analyzing human operation data and generating reference readings that simulate human-like variability. This copy is then used to mask machine operations, allowing automated systems to maintain productivity while presenting a human-like interface that resolves security and safety concerns
2Productivity
If devices are made more automated to improve efficiency, then productivity increases, but human comfort decreases due to discomfort with automated devices
Solution Approach 1:
The system modifies the observable characteristics of machine operations by adding behavioral variability that mimics human imperfections. This makes automated devices more acceptable to humans while maintaining their automated efficiency, as users are more comfortable interacting with systems that behave like humans rather than perfectly predictable machines
Solution Approach 2:
The system copies human behavioral patterns including natural variations, pauses, and imperfections in operation. This creates a more comfortable user experience while maintaining automated efficiency, as users feel more at ease interacting with systems that replicate familiar human behaviors rather than starkly artificial automated responses
Data Source
AI summary
Determining a type of actor performing an activity includes monitoring the performance of the activity via at least one sensor to produce activity readings over a dimension. The activity readings are then compared to reference readings that are generated based on a machine performing same activity. The comparison of the reference readings to the activity readings is used to determine a variance between the activity readings and reference readings. Once the variance is determined, the variance is compared with a threshold value to determine the type of actor performing the activity.