Access Safety Validation Using Segmented Imaging and Neural Networks
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Solution Overview
Problem
Traditional access control systems relying on image processing techniques are computationally intensive and fail to provide timely safety device or PPE validation, especially in high-traffic environments, leading to potential safety risks and inefficient resource usage.
Innovation Solution
The use of multiple imaging devices and machine learning techniques, such as artificial neural networks, to quickly determine safety compliance by analyzing image data from both access locations and users, reducing computational burden and ensuring real-time validation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional image processing techniques are used to determine PPE usage, then safety validation can be performed, but the system becomes computationally intensive and fails to provide timely validation in high-traffic environments
Solution Approach 1:
The patent divides the image processing task into two distinct stages: a first imaging device captures images of the access location (e.g., barcode) to determine access conditions, and a second imaging device captures images of the user to determine safety parameters. This segmentation allows each device to specialize in specific detection tasks, improving overall processing efficiency and reliability without requiring one device to handle all computational burdens.
2Reliability
If traditional image processing techniques are used to determine PPE usage, then safety compliance can be checked, but the system wastes computation resources by processing images that do not include users or access attempts
Solution Approach 1:
The system performs preliminary detection using the first imaging device to determine access conditions (such as detecting barcodes or access location markers) before triggering the second imaging device to capture user images. This preliminary action filters out scenarios where no access attempt is occurring, preventing wasteful processing of irrelevant images and conserving computational resources while maintaining reliable safety compliance detection when needed.
3Productivity
If multiple imaging devices are used to capture images of access locations and users, then real-time safety determinations can be made, but the device complexity increases
Solution Approach 1:
The patent employs imaging devices that can serve multiple functions: the first imaging device captures access location information (barcodes, markers) and can also detect user presence, while the second imaging device captures user images for safety parameter determination. This multi-functionality reduces the need for entirely separate specialized devices, managing system complexity while maintaining real-time processing capability.
Solution Approach 2:
The system introduces a computing device as an intermediary that receives images from multiple imaging devices, determines access conditions and safety parameters, and generates alert signals. This centralized processing mediator simplifies the architecture by providing a single point of decision-making that coordinates the multiple imaging devices, reducing the complexity burden that would arise from distributed autonomous processing.
4Reliability
If traditional systems process all images to determine safety compliance, then comprehensive safety checks are performed, but the processing time increases and timely access control is compromised
Solution Approach 1:
The system implements partial processing by using the first imaging device to perform initial access condition determination (detecting barcodes, access location markers) without fully processing user safety images unless an access attempt is detected. This partial action approach performs comprehensive safety checks only when necessary, significantly reducing validation time in high-traffic environments while maintaining reliable safety checking when access attempts occur.
Data Source
AI summary
Systems, methods, and computer program products for access-related safety determinations are provided. An example method includes receiving first image data of a field of view of a first imaging device that includes an access location and determining an access condition of the access location based upon the first image data. In response to an attempt to access the access location by a first user, the method includes receiving second image data of a field of view of a second imaging device that includes the first user upon which to perform a safety determination. The method further includes generating a safety parameter for the first user that is indicative of a presence and a positioning of a safety device of the first user, comparing the safety parameter with a validation threshold, and generating an alert signal in an instance in which the safety parameter fails to satisfy the validation threshold.