Smart Device Task Completion Detection via Event Signature Matching
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Solution Overview
Problem
Automation processes are hindered by personnel shortages and theft of assets, where existing technologies lack the ability to autonomously determine task completion and respond appropriately, such as notifying delivery services or triggering countermeasures for theft detection.
Innovation Solution
A smart device that analyzes sensed data to match event signatures with a library, enabling it to autonomously determine task completion and initiate actions like M2M communication for delivery or triggering countermeasures, such as dye spraying or camera activation, upon positive comparison.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automation procedures are implemented to reduce personnel reliance, then productivity and efficiency are improved, but the system becomes more complex and requires advanced sensing and analysis capabilities
Solution Approach 1:
The system segments the automation task into distinct phases: sensing phase (collecting data from multiple sensors), analysis phase (processing sensed data to identify events), and action phase (executing predetermined actions). This segmentation allows each component to be optimized independently while maintaining overall system efficiency.
Solution Approach 2:
The system performs preliminary actions by pre-programming event signatures and predetermined actions before deployment. When sensors detect conditions matching stored event signatures, the system automatically executes pre-determined actions without requiring real-time human decision-making, thereby improving productivity while managing complexity through advance preparation.
2Speed
If the device autonomously determines task completion through event signature analysis, then response time and operational speed are improved, but measurement precision and reliability of determination are challenged
Solution Approach 1:
The system continuously monitors sensed conditions and compares them against stored event signatures, creating a feedback loop that validates task completion determinations. Multiple sensors provide redundant feedback signals that cross-validate each other, improving both the speed and precision of task completion detection through collective verification.
Solution Approach 2:
The system uses a universal event signature comparison mechanism that can identify multiple different task completion scenarios using the same analytical framework. By storing diverse event signatures representing various completion conditions, the system maintains high measurement precision across different task types while responding quickly to any completion event.
3Reliability
If multiple sensors and event signature libraries are integrated to enhance detection capability, then reliability of theft detection is improved, but device complexity and energy consumption increase
Solution Approach 1:
The system employs periodic sampling of sensor data rather than continuous monitoring, analyzing sensed conditions at predetermined intervals. This periodic operation reduces energy consumption while maintaining reliable theft detection by capturing sufficient data points to identify event signatures. The system can increase sampling frequency when suspicious conditions are detected, dynamically balancing energy use and detection reliability.
4Adaptability or versatility
If the system performs multiple predetermined actions upon task completion, then operational versatility and adaptability are improved, but device complexity and difficulty of operation increase
Solution Approach 1:
The system performs self-service by automatically executing predetermined actions based on event signature matching without requiring external intervention. The device independently determines task completion and initiates appropriate actions such as notifications or countermeasures, reducing operational complexity despite offering versatile response options. Users benefit from this self-service capability while the system manages its own operational complexity.
Data Source
AI summary
A method and apparatus is provided for initiating procedures whereby a smart device is able to analyze situational data sensed by the device, compare one or more event signatures representative of the sensed data with one or more sets of event signatures in a library of event signatures to logically determine completion of a job function and to then cause a specific action to be taken.


