Digital Twin Access Control for Physical Stability Monitoring
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Solution Overview
Problem
Existing security control systems fail to effectively manage access and ensure physical stability within enclosed surroundings, leading to accidents and damage due to unstable conditions caused by improper object placement and hazardous materials.
Innovation Solution
A system utilizing digital twin simulation and real-time monitoring to evaluate physical stability parameters, determining suitability for worker activities and assigning appropriate security rules for access control, incorporating IoT sensors and AI for predictive safety measures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional security control systems are used, then access control is simple, but physical stability cannot be effectively monitored leading to accidents
Solution Approach 1:
The patent creates a digital twin (virtual copy) of the physical enclosed surrounding to monitor and simulate physical stability parameters. This digital replica allows comprehensive stability monitoring without adding physical monitoring equipment throughout the actual space, thus improving reliability while avoiding excessive device complexity
Solution Approach 2:
The patent replaces traditional mechanical/manual security control systems with an AI-based digital simulation system. The AI controller analyzes digital twin data to automatically determine access permissions, substituting manual security checks with intelligent automated decision-making that can assess physical stability conditions
2Reliability
If digital twin simulation and real-time monitoring are implemented, then physical stability is effectively monitored, but system complexity increases
Solution Approach 1:
The digital twin serves multiple functions simultaneously: it monitors physical stability parameters, simulates potential accidents, predicts hazards, and provides data for access control decisions. This multi-functionality consolidates what would otherwise require separate systems into a single unified platform, improving reliability without proportionally increasing complexity
Solution Approach 2:
The AI controller automatically analyzes digital twin data and makes access control decisions without requiring constant human intervention. The system self-adjusts security rules based on real-time stability assessments, reducing the operational complexity of managing the monitoring system
3Object-affected harmful factors
If AI-based predictive safety measures are used, then worker safety is enhanced, but computational requirements and system complexity increase
Solution Approach 1:
The digital twin simulates and predicts potential accidents and hazards before they occur in the physical space. By performing preliminary virtual simulations of instability scenarios, the system identifies potential harmful factors in advance, allowing preventive measures to be taken before actual accidents happen, thus enhancing safety without requiring complex real-time intervention systems
Data Source
AI summary
Embodiments of the disclosure provide systems and methods for implementing enhanced access control of an enclosed surrounding. Access control to an enclosed surrounding is implemented using digital twin simulation, real-time monitoring and identifying physical stability parameters of the enclosed surrounding. The system evaluates multiple physical stability parameters of an enclosed surrounding, based on a digital twin simulation, to identify a degree of stability or safety inside the enclosed surrounding. The system identifies types of protection needed, and assigns an appropriate security rule for entering the enclosed surrounding. The system can receive a user input of testing parameters for a proposed action within the enclosed surrounding and evaluate the received testing parameters, based on the digital twin simulation, to trigger alerts and provide a plan for the user to safely perform the proposed action.