Access Control Localization for Intent-Based Door Authentication

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Solution Overview

Problem

Conventional physical access control systems (PACS) face challenges in providing a seamless user experience due to delayed responses and the need for manual credential presentation, and they struggle with accurately determining user intent, leading to potential unauthorized access.

Innovation Solution

Implementing a two-step authentication process using BLE for initial credential transfer and UWB for precise localization, caching credentials until intent is confirmed, and utilizing a neural network to predict user intent based on historical data and sensor information.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of operation

If manual credential presentation is required, then system security is maintained, but user experience deteriorates due to delayed response and operational complexity

Engineering Contradiction:

Improveuser experienceVSAvoidresponse delay

Core Design Contradiction:

Ease of operationVSLoss of time

Solution Approach 1:

The system performs preliminary credential detection and intent analysis before the user reaches the access point. The neural network continuously monitors credential location and user behavior patterns in advance, preparing authentication decisions beforehand to eliminate response delays when the user arrives at the door.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system enables automatic credential detection and intent determination without requiring manual user actions. The neural network autonomously analyzes sensor data, tracks credential location, and makes authentication decisions, freeing the user from manual credential presentation and improving ease of operation.

Inventive Principle:

Principle #25Self-service

2Productivity

If automated intent detection is implemented, then user experience is improved, but system reliability deteriorates due to potential unauthorized access

Engineering Contradiction:

Improveaccess efficiencyVSAvoidaccess security

Core Design Contradiction:

ProductivityVSReliability

Solution Approach 1:

The system continuously collects feedback from multiple sensors (location, motion, biometric data) and feeds this information back to the neural network for real-time intent reassessment. This continuous feedback loop allows the system to dynamically adjust authentication decisions based on current user behavior, maintaining high security while enabling efficient automated access.

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The system performs preliminary authentication checks and credential verification before granting access. The neural network analyzes historical data and current sensor readings in advance to pre-validate user intent, adding a security layer that prevents unauthorized access while maintaining automated efficiency.

Inventive Principle:

Principle #10Preliminary action

3Measurement precision

If multiple sensors and neural networks are deployed, then intent detection accuracy is improved, but device complexity increases

Engineering Contradiction:

Improveintent detection accuracyVSAvoidsystem complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The system segments the intent detection function into modular components: credential detection module, sensor data collection module, neural network processing module, and authentication decision module. Each component handles a specific aspect of intent detection, making the complex system more manageable and maintainable while preserving high detection accuracy through specialized processing in each segment.

Inventive Principle:

Principle #1Segmentation

4Reliability

If continuous credential tracking is performed, then access security is improved, but energy consumption increases

Engineering Contradiction:

Improveaccess control securityVSAvoidenergy consumption

Core Design Contradiction:

ReliabilityVSUse of energy by moving object

Solution Approach 1:

The system performs credential tracking and intent analysis periodically rather than continuously. The neural network assesses user intent at scheduled intervals and triggers authentication only when intent is detected, reducing energy consumption while maintaining security by periodically verifying credential status and user behavior patterns.

Inventive Principle:

Principle #19Periodic action

Data Source

PatentUS12495299B2Physical access control systems with localization-based intent detection

Publication Date: 2025.12.09 ASSA ABLOY AB

AI summary

Systems and techniques for a are described herein. In an example, an access control system may regulate access to an asset. The access control system is adapted to receive a credential for the asset from a key device associated with a user using a first wireless connection. The access control system may be further adapted to store the credential in a cache of memory. The access control system may be further adapted to establish a second wireless connection with the key device. The access control system may be further adapted to request a validation of the credential from an authorization service in response to establishing the second wireless connection with the key device. The access control system may receive a validation token from the authorization service. The access control system may be further adapted to store the validation token in the cache.