Voice-Controlled Heavy Machinery via Neural Network
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Solution Overview
Problem
Current methods for controlling and maintaining heavy machinery in industrial settings are costly and time-consuming, requiring physical systems and skilled personnel, with no efficient and cost-effective mechanism for remote operation and management.
Innovation Solution
A method and device for controlling devices through voice interaction using a trained neural network to identify features and perform actions based on user intent, with the neural network pre-trained on prior actions and features of the target device, allowing for remote operation within operational thresholds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If physical systems and skilled personnel are deployed for remote operation, then reliable control of heavy machinery is achieved, but system complexity and operational costs increase
Solution Approach 1:
The patent replaces physical mechanical control systems with a voice-based control system. The voice processing unit converts spoken commands into control signals, eliminating the need for complex physical interfaces and reducing system complexity while maintaining control reliability through automated voice recognition and processing.
Solution Approach 2:
The system enables unattended automated operation where the machinery can be controlled and monitored without constant human supervision. The control unit processes voice commands and executes operations autonomously, reducing the need for skilled personnel to be physically present while maintaining reliable operation.
2Reliability
If physical systems and personnel are used for on-site maintenance, then proper maintenance operations are performed, but time consumption and operational costs increase
Solution Approach 1:
The patent replaces physical on-site maintenance operations with remote voice-controlled operations. The voice processing unit receives maintenance commands and transmits control signals to the target device, enabling maintenance personnel to perform operations remotely without traveling to the site, thus reducing time consumption while maintaining maintenance quality.
Solution Approach 2:
The control unit acts as an intermediary between the voice processing unit and the target device. It receives voice commands, processes them into appropriate control signals, and transmits them to the target device, enabling efficient remote maintenance operations without direct physical intervention.
3Productivity
If automated control mechanisms are implemented, then operational efficiency improves, but requirement for trained personnel increases
Solution Approach 1:
The patent replaces complex automated control interfaces with simple voice-based commands. Instead of requiring trained personnel to navigate complex control systems, users can issue natural voice commands that are processed by the voice processing unit, maintaining high operational efficiency while significantly improving ease of operation.
Solution Approach 2:
The system is designed to understand and execute voice commands with minimal user training required. The voice processing unit and control unit work together to interpret natural language commands and translate them into appropriate control actions, enabling anyone to operate the system efficiently without extensive training.
Data Source
AI summary
A method and a system for controlling devices through voice interaction are disclosed. In an embodiment, the method may include identifying at least one feature of a target device and an action to be performed on the at least one feature, based on an intent and an object determined from a voice input received from a user. The method may further include determining a correspondence between the at least one feature and the action to be performed using a trained neural network. The method may further include comparing a current operational state of the at least one feature with an operational threshold of the at least one feature. The method may further include performing the action on the at least one feature based on the determined correspondence, when the current operational state is within limits of the operational threshold.