Computer Task Pattern Monitoring for Error Prevention
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Solution Overview
Problem
Users are prone to performing erroneous computer tasks due to factors such as inattention, boredom, distraction, and tiredness, leading to potential errors in task execution.
Innovation Solution
An iterative process is implemented to monitor computer tasks, identify deviations from established patterns, send alerts to computing devices, receive feedback, and update pattern scores to prevent erroneous task performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If users perform computer tasks continuously, then productivity is maintained, but error rate increases due to inattention and distraction
Solution Approach 1:
The system performs preliminary actions by establishing baseline patterns of correct task execution through monitoring and analysis before actual errors occur. It creates expected behavior models in advance, allowing real-time detection when deviations from these pre-established patterns occur, thus preventing errors before they impact productivity.
Solution Approach 2:
The system implements continuous feedback loops where task performance is monitored, compared against established patterns, and deviations are detected in real-time. When anomalies are identified, the system provides immediate feedback through alerts to users or administrators, enabling corrective action before erroneous tasks complete, thus maintaining both productivity and reliability.
2Reliability
If real-time monitoring of computer tasks is implemented, then task accuracy is improved, but system complexity increases
Solution Approach 1:
The system performs self-service by automatically learning and establishing task patterns through its own monitoring activities. It autonomously analyzes task execution, identifies normal behavior patterns, and sets baseline expectations without requiring external intervention. This self-configuration capability reduces the complexity burden on administrators while maintaining high task accuracy through continuous adaptive monitoring.
Solution Approach 2:
The system creates copies of normal task execution patterns and stores them as reference models. By replicating and archiving typical task flows, it enables efficient comparison against actual task execution without requiring complex real-time analysis of every task detail. This pattern copying approach simplifies the monitoring architecture while maintaining high detection accuracy for erroneous tasks.
3Reliability
If pattern analysis and deviation detection are performed continuously, then erroneous tasks are prevented, but computational resources are consumed
Solution Approach 1:
The system applies partial action by focusing computational resources only on detecting deviations from established patterns rather than analyzing every task parameter in depth. It uses pattern matching to identify anomalies, which requires significantly fewer computational resources than comprehensive task validation. This selective monitoring approach maintains effective error prevention while minimizing computational energy consumption.
Solution Approach 2:
The system performs preliminary pattern establishment and storage before actual deviation detection is needed. By pre-computing and caching expected task patterns, it eliminates the need for expensive real-time pattern generation during task execution. This advance preparation reduces the computational burden during operational phases while maintaining high error detection capability.
Data Source
AI summary
A method, computer program product, and computer system for preventing erroneous performance of computer tasks. An iterative process of at least two iterations is performed. Each iteration includes: monitoring computer tasks performed on computing devices; ascertaining whether a deviant computer task having a deviation from one pattern of multiple pattens in a pattern library is about to be performed by any computing device and if so: sending an alert identifying the deviant computer task to the one computing device, receiving feedback to the alert from the one computing device, and updating a pattern score of the one pattern based on the feedback and replacing the pattern score of the one pattern in the pattern library with the updated pattern score. It is ascertained, in one iteration that is not the last iteration, that the deviant computer task is about to be performed.