Cognitive Suit Context Map Actuation for Dynamic Risk Mitigation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current smart garments and textiles lack a mechanism to dynamically adjust to changing risks and constraints within a user's operational space as they move, failing to provide effective protection in high-risk environments.
Innovation Solution
A computer-implemented method generates a risk and constraint labeled context map using three-dimensional reconstruction, virtual reality, and semi-supervised learning to drive an inflatable/deflatable actuation apparatus in a cognitive suit, deploying mitigation strategies based on sensed risks and constraints along the user's trajectory.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If protective garments are worn to protect workers in high-risk spaces, then worker safety is improved, but worker mobility and job performance are worsened due to incumbrance
Solution Approach 1:
The protective garment transforms from a static protective layer to a dynamic system that actively responds to environmental hazards. Sensors continuously monitor the operational space, and the garment's protective mechanisms are activated only when risks are detected, allowing the worker to move freely during safe periods while maintaining protection when needed.
Solution Approach 2:
The protective garment incorporates embedded sensors and processing capabilities that enable it to autonomously detect hazards, assess risks, and deploy protective measures without constant human intervention. The system self-monitors the worker's environment and activates protection mechanisms based on detected conditions, reducing the burden on the worker while maintaining safety.
2Measurement precision
If sensors are embedded in smart garments to detect user condition and environment, then detection capability is improved, but the system lacks dynamic response to changing risks along user trajectory
Solution Approach 1:
The system continuously collects data from embedded sensors about the worker's environment and condition, processes this information in real-time, and uses the feedback to dynamically adjust protective measures. The feedback loop enables the garment to respond to changing risks by activating or deactivating protective mechanisms based on current sensor readings and predicted trajectory analysis.
Solution Approach 2:
The system performs preliminary risk assessment by analyzing the worker's trajectory and predicting potential hazards before the worker actually encounters them. This allows the protective garment to activate mitigation strategies in advance, such as inflating protective airbags or alerting the worker to upcoming dangers, rather than merely reacting after contact is made.
3Reliability
If the cognitive suit actuates to deploy mitigation strategies in response to sensed risks, then protection effectiveness is improved, but the system reacts only after risks are within sensor range rather than proactively
Solution Approach 1:
The cognitive suit uses trajectory prediction and environmental mapping to identify potential hazards before the worker enters their detection range. By analyzing the worker's movement pattern and the three-dimensional context map, the system activates protective measures in advance, such as deploying airbag protection or issuing warnings, thereby eliminating the reactive delay and providing proactive protection.
Solution Approach 2:
The system introduces an intermediary processing layer that bridges the gap between sensor detection and protective action. This intermediary analyzes sensor data, predicts future risks based on trajectory, and triggers mitigation strategies before the actual hazard contact occurs, effectively reducing the response time delay by acting on predicted rather than current states.
Data Source
AI summary
Generating a risk and constraint labeled context map of an operational space is provided. The risk and constraint labeled context map of the operational space corresponding to a user of a cognitive suit is generated to drive the cognitive suit contextually using three-dimension reconstruction, virtual reality, and semi-supervised learning. Labeled risks and constraints in the risk and constraint labeled context map are associated with cognitive suit actuation events to deploy a set of mitigation strategies to address the labeled risks and constraints. An apparatus embedded in the cognitive suit is actuated to deploy the set of mitigation strategies in response to sensing a labeled risk or labeled constraint proximate to the user along a trajectory of the user in the operational space.