Workspace Context Modeling for Real-Time SOP Violation Detection
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Solution Overview
Problem
Conventional safety compliance systems rely on manual entry of safety incidents, leading to errors and lack proactive monitoring and predictive analysis, failing to ensure compliance with safety standard operating procedures (SOPs) and preventing accidents.
Innovation Solution
A system and method that creates a context model for a workspace by defining domain-dependent safety violation rules for digitally augmented assets, using sensor-based data to monitor and automatically trigger SOP violations, enabling real-time compliance monitoring and predictive analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If manual entry of safety incidents is used, then system complexity is reduced, but measurement precision and reliability of safety data deteriorate due to human errors
Solution Approach 1:
The patent replaces manual mechanical entry processes with automated sensor-based detection systems. Sensors continuously monitor workspace conditions and automatically record safety incidents, eliminating human error in data collection while maintaining system functionality.
Solution Approach 2:
The safety monitoring system performs self-service by automatically detecting, recording, and analyzing safety incidents without human intervention. The system uses embedded sensors and algorithms to autonomously track compliance with safety SOPs and generate reports.
2Device complexity
If manual entry of safety incidents is used, then device complexity is reduced, but loss of time for tracking historical information increases
Solution Approach 1:
The system implements continuous monitoring of safety conditions through deployed sensors that operate without interruption. Historical safety data is continuously captured and stored, eliminating gaps in tracking and enabling immediate access to historical information when needed.
Solution Approach 2:
The system performs preliminary recording of safety incidents as they occur, rather than relying on subsequent manual entry. By capturing data at the moment of incidence through automated sensors, the system eliminates delays in historical data availability.
3Device complexity
If manual entry systems are used, then device complexity is reduced, but productivity deteriorates due to lack of predictive analysis and proactive compliance
Solution Approach 1:
The system implements feedback loops where sensor data is continuously analyzed against safety SOPs, and alerts are generated when compliance deviations are detected. This proactive feedback mechanism enables timely corrective actions, preventing safety incidents and their associated productivity losses.
Solution Approach 2:
The system performs preliminary analysis of safety trends and predicts potential violations before they occur. By identifying patterns in sensor data, the system can alert operators to upcoming compliance issues, allowing preventive measures to be taken before productivity is impacted.
Data Source
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AI summary
This disclosure relates generally to safety improvement in a workspace. The method includes creating a context model associated with the workspace by defining contextual domain and a plurality of safety violation rules for safety standard operating procedures (SOPs) of digitally augmented assets corresponding to the physical entities present in the workspace. Further, the method includes monitoring, in real-time, states of each of the digitally augmented assets by obtaining sensor-based data from a sensor devices deployed in a smart space environment implemented in the workspace. SOP violations are triggered as events on a comparison of the states of digitally augmented assets with the safety violation rules using the context model.