Semi-autonomous Plant Processing via Image Recognition
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Solution Overview
Problem
Manual interventions in plant propagation and culturing processes are time-consuming and costly, requiring extensive sterilization and disinfection, which increases expenses, especially in high-throughput operations.
Innovation Solution
A semi-autonomous method using image recognition and neural networks to detect plant features, suggesting processing options to a person, who then selects the appropriate action, allowing the plant to be processed autonomously or automatically by machine-controlled means, reducing the need for manual handling and enabling remote operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual interventions are used for plant processing, then flexibility and decision-making quality are improved, but time consumption and costs increase
Solution Approach 1:
The processing method is segmented into distinct phases: autonomous machine handling for routine operations, image recognition for detection, and human decision-making only for critical processing options. This segmentation allows time-consuming manual interventions to be replaced by automated systems while preserving human judgment where needed.
Solution Approach 2:
An image recognition system acts as an intermediary between the plant material and the processing decision. The system captures images, identifies plant features and status, and presents processed information to the operator, reducing the time required for manual inspection while maintaining decision quality.
2Reliability
If extensive sterilization and disinfection are performed, then pathogen elimination is improved, but expenses increase
Solution Approach 1:
The system enables self-service processing where plants are handled autonomously by machines for routine operations. This reduces the frequency and extent of sterilization needed, as automated handling minimizes contamination risks compared to repeated manual interventions, thereby lowering expenses while maintaining pathogen elimination effectiveness.
Solution Approach 2:
Manual mechanical handling is replaced by automated processing means. This substitution reduces the need for extensive sterilization protocols, as automated systems can be more easily sterilized and maintained in controlled environments, reducing overall expenses while maintaining high reliability in pathogen elimination.
3Adaptability or versatility
If manual handling is performed, then adaptability to plant variations is improved, but productivity decreases
Solution Approach 1:
The image recognition system provides continuous feedback about plant features, status, and variations. This feedback loop enables the automated system to adapt its processing actions in real-time, maintaining adaptability to plant variations while operating at high speeds that manual handling cannot achieve, thereby increasing productivity.
Solution Approach 2:
The system changes processing parameters automatically based on image recognition data. Different plant variations are detected through image analysis, and the processing parameters (such as cutting position, force applied, or treatment type) are dynamically adjusted, maintaining adaptability while enabling high-throughput automated processing.
4Reliability
If sterilization procedures are implemented, then plant health is improved, but time and cost efficiency worsen
Solution Approach 1:
Sterilization procedures are performed preliminarily on the automated processing equipment and environment before plant processing begins. This preliminary action ensures plant health is maintained throughout the process without requiring repeated sterilization interruptions, thereby improving time and cost efficiency while maintaining reliable plant health protection.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This method significantly reduces time and costs by automating plant processing, facilitating efficient sterilization and disinfection, and allowing for precise and efficient treatment of plants, even in remote locations, with the potential for fully autonomous operations.
Implementation Method 1
at least one plant or a component of the plant is detected by image recognition
Data Source
AI summary
A method by means of which the processing of plants can be carried out in a more time- and cost-efficient manner. For this purpose, at least one plant or a component of the plant is detected by an image-recognition device. Using the patterns and features of the plants recognized by the image-recognition device, at least one option for processing the plant is suggested to a person. Upon selection of at least one option by the person, the plant or the component of the plant is autonomously or automatically processed by a processing means.