Biometric Operator Recognition for Mobile Machine Control
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Solution Overview
Problem
Mobile construction and work machines often operate with varying skill levels among operators, posing challenges in ensuring safe and efficient operation, particularly in environments where multiple operators use the same machine without adequate control over their proficiency or attentiveness.
Innovation Solution
A pattern recognition system captures images of operators and processes them to identify and authenticate the operator, generating control signals to adjust machine settings and subsystems based on their skills, attentiveness, and other characteristics, ensuring appropriate functionality and safety measures are enabled or locked.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If multiple operators use the same machine without biometric recognition, then ease of operation is improved, but operational safety and reliability deteriorate due to varying skill levels and lack of operator-specific controls
Solution Approach 1:
The system performs preliminary identification and authentication of the operator using biometric recognition (image capture, facial recognition, or other biometric characteristics) before allowing machine operation. This preliminary action enables the system to pre-load operator-specific settings, skill-level restrictions, and safety parameters, ensuring that reliable operator-specific controls are in place before the operator begins work.
2Reliability
If biometric recognition and operator-specific control signals are implemented, then operational safety and reliability are improved, but device complexity increases due to additional sensing and processing systems
Solution Approach 1:
The control system is designed with multi-functionality to handle various operator identification methods (image capture, facial recognition, other biometric characteristics) and to manage diverse operator-specific parameters (skill level, authorized functions, sensitivity settings). This universal approach consolidates multiple functions into a single integrated system, reducing overall complexity compared to implementing separate specialized systems for each function.
Solution Approach 2:
The system automatically performs operator identification, authentication, and configuration without requiring manual setup or intervention. The biometric recognition system self-identifies the operator, retrieves their profile, and automatically applies the appropriate control signals and machine settings, eliminating the need for operators to manually configure their preferences or for administrators to manually set up each operator's profile.
3Productivity
If operator-specific control signals are generated based on biometric identification, then productivity and operational efficiency are improved, but loss of time occurs during operator authentication and system configuration
Solution Approach 1:
The system performs preliminary authentication and configuration actions quickly using automated biometric recognition, storing operator profiles in advance so that when an operator approaches or begins work, their identification and system configuration occur rapidly without manual intervention, minimizing authentication time while maintaining security.
Data Source
AI summary
A pattern recognition system receives an image captured by an image capture device, of an operator and the operator is identified. Operator information is accessed, based upon the identified operator, and a control signal is generated to control a mobile machine, based upon the operator information.