Hazard Response Task Allocation Using Simulated Worker Behavior
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Solution Overview
Problem
Conventional training methods for hazardous events in industrial environments lack the ability to evaluate trainees' understanding of risks, are difficult to perform in real environments, pose safety risks, and do not allow for qualitative and quantitative evaluation, making it challenging to assign workers effectively to handle specific scenarios.
Innovation Solution
A system and method that utilizes a computer-simulated environment, such as a metaverse, to create immersive training scenarios with multimodal AR elements, sensors to track trainee responses, and a behavior matrix to allocate tasks based on performance, ensuring safe and effective training without real-world hazards.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional drills are conducted in real hazardous environments, then trainees can experience realistic scenarios, but personal safety of personnel is endangered
Solution Approach 1:
The patent creates virtual copies of hazardous environments using VR/AR technology and digital twins. These virtual replicas reproduce the visual, auditory, and interactive characteristics of real hazardous scenarios without the actual dangers, allowing trainees to experience realistic training while remaining in safe virtual spaces.
Solution Approach 2:
The system introduces an intermediary layer between the trainee and the hazardous environment through wearable devices, sensors, and virtual reality interfaces. This intermediary technology mediates the interaction, allowing trainees to engage with simulated hazards while physical safety is maintained through the buffer of virtual reality equipment.
2Ease of manufacture
If conventional training methods are used, then training can be conducted simply, but the ability to evaluate trainee understanding and performance is lacking
Solution Approach 1:
The system implements continuous feedback loops where sensors track trainee actions, physiological responses, and decision-making patterns. This data is processed to provide real-time feedback during training and comprehensive performance evaluations afterward, enabling precise measurement of understanding and skill acquisition while maintaining structured training procedures.
Solution Approach 2:
The training system integrates multiple functions into a unified platform: virtual reality simulation, physiological monitoring, behavioral tracking, performance analysis, and evaluation reporting. This multi-functional system achieves both ease of implementation through a single integrated solution and precise evaluation through comprehensive data collection capabilities.
3Measurement precision
If immersive training scenarios are created, then trainee behavior can be accurately evaluated, but system complexity increases
Solution Approach 1:
The complex evaluation system is segmented into modular components: virtual environment modules, sensor tracking modules, data processing modules, and evaluation algorithms. Each module handles specific aspects of behavior tracking and analysis, making the overall complex system manageable through independent, standardized components that can be configured for different training scenarios.
4Measurement precision
If real-world hazardous drills are conducted, then actual hazard response can be practiced, but training organization time is reduced and knowledge consolidation is limited
Solution Approach 1:
The virtual training system enables periodic repetition of hazardous scenarios that would be impractical in real life. Trainees can repeatedly experience the same hazard scenarios with varying parameters and conditions, allowing thorough practice and knowledge consolidation without the time constraints and safety risks of real-world drills.
Data Source
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AI summary
Disclosed is system (100) and method (400) for accurately allocating tasks to workers on occurrence of a hazardous event in industrial environment. The method comprises executing, by the processing unit (302), simulated training session in computer simulated environment (102). The workers (114-1 to 114-N) participate in training session via user devices (202). The method comprises acquiring data from sensors (204-1 to 204-N) associated with the workers. The sensors acquire data pertaining to performance of workers in training session. The method comprises generating behavior matrix for workers in training session. The behavior matrix is designed based on a response of worker to hazardous event in training session. The method comprises mapping workers to tasks defined in training session. The method comprises allocating, tasks to each of the workers when hazardous event occurs in the real-world in industrial environment based on the mapping.