Autonomous Tethering for Real-Time Fall Risk Prevention
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Solution Overview
Problem
Current manual safety measures for preventing falls in work areas are inadequate as they rely on workers' judgment for anchor point selection and strength, limiting visibility of the work area, and requiring unsafe movements, leading to potential liability and high workers' compensation costs.
Innovation Solution
The use of autonomous devices equipped with machine vision and IoT capabilities to map the work area, identify anchor points, and dynamically adjust safety configurations in real-time to secure tethers for users, ensuring active fall prevention and mitigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual safety measures are used for fall prevention, then workers can perform tasks with basic safety equipment, but the safety effectiveness is limited due to reliance on worker judgment and manual operations
Solution Approach 1:
The autonomous device performs safety monitoring and anchor point identification automatically without requiring worker intervention. The system self-manages the complex tasks of mapping, analyzing, and determining safety configurations, freeing workers from manual safety operations while enhancing safety effectiveness through automated, consistent decision-making.
Solution Approach 2:
The patent replaces manual mechanical operations with autonomous robotic systems. The autonomous device uses computer vision, sensors, and automated manipulation to perform tasks that previously required manual worker actions, such as identifying anchor points, monitoring fall risks, and adjusting safety equipment, thereby reducing reliance on worker judgment while maintaining system manageability.
2Measurement precision
If workers manually select anchor points and adjust safety equipment, then the safety system remains simple to operate, but the accuracy and adaptability of safety configurations are insufficient
Solution Approach 1:
The patent replaces manual worker operations with an autonomous device equipped with computer vision, LIDAR, and sensor arrays. These technologies enable precise identification of anchor points and real-time monitoring of worker position and fall risk, achieving high measurement precision while the centralized autonomous control maintains operational simplicity through automated decision-making.
Solution Approach 2:
The autonomous device serves as an intermediary between the worker and the safety equipment. It processes complex environmental data, identifies suitable anchor points, and automatically adjusts tether tension and positioning, thereby achieving high precision safety configurations without requiring the worker to understand or manually operate complex safety systems.
3Reliability
If workers perform unsafe movements to access anchor points, then the safety equipment can be deployed, but the process introduces additional fall risks and reduces overall safety
Solution Approach 1:
The autonomous device performs preliminary mapping and identification of safe anchor points before the worker begins tasks. By pre-establishing safe attachment points and monitoring the worker's position in real-time, the system eliminates the need for workers to perform unsafe movements to access anchor points, thereby preventing additional fall risks while maintaining high fall prevention reliability.
Solution Approach 2:
The autonomous device independently identifies and validates safe anchor points using sensors and computer vision, without requiring worker intervention or exposure to hazardous areas. The system self-manages the process of selecting and verifying anchor point safety, thereby eliminating the harmful factor of workers performing unsafe movements while ensuring reliable fall prevention.
4Reliability
If real-time monitoring and dynamic safety adjustments are implemented, then fall prevention effectiveness is enhanced, but the system complexity and computational requirements increase
Solution Approach 1:
The patent employs an autonomous device with integrated computer vision, LIDAR, sensors, and automated manipulation systems to perform real-time monitoring and dynamic safety adjustments. This automated system handles the computational complexity of processing multiple data streams and making real-time decisions, thereby enhancing fall prevention effectiveness while managing system complexity through centralized autonomous control rather than distributed manual operations.
Data Source
AI summary
A method for providing active fall prevention assistance to a user. The method includes one or more computer processors mapping a work area where a user performs a plan of tasks. The method further includes determining a safety configuration related to the user and the task. The method further includes instructing an autonomous device to attach a first tether between a first anchor point and a safety harness secured to the user. The method further includes analyzing real-time images of the work area and the user while the user performs the task. The method further includes determining that the user is at risk of falling. The method further includes responding to determining that the user is at risk of falling by instructing the autonomous device to attach a second tether between a second anchor point and the safety harness secured to the user.