Neural Network Object Identification for Single-Pass Field Rock Removal
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Solution Overview
Problem
Current methods for removing rocks and other objects from agricultural fields are inefficient, often requiring multiple passes with manual operation and resulting in high labor costs and safety hazards due to the failure of existing implements to effectively clear fields.
Innovation Solution
The use of neural networks to identify objects in images collected by an image-collection vehicle, which guides an object-collection system to selectively pick up and remove objects from the field, improving accuracy and reducing manual labor.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional implements (rakes, windrowers, sieves) are used to clear fields of rocks, then field clearing can be performed mechanically, but the failure rate is high and multiple passes are required
Solution Approach 1:
The patent replaces traditional mechanical rock detection and removal systems with an AI-based neural network system that uses image processing to identify rocks and guide a collection mechanism, thereby improving detection accuracy and reducing multiple passes
Solution Approach 2:
The patent introduces an intermediary AI system between rock detection and removal that uses neural networks to analyze images and identify rocks, serving as a mediator that guides the collection mechanism with high precision
2Reliability
If manual operation and human intervention are used to pick rocks, then rocks can be removed from the field, but labor costs increase and work is slow
Solution Approach 1:
The patent implements a self-service system where the AI-based detection and collection mechanism operates autonomously to identify and remove rocks without human intervention, eliminating labor costs and reducing time loss
Solution Approach 2:
The patent performs preliminary rock identification using neural networks before collection, allowing the system to plan and execute rock removal in a single pass rather than requiring multiple passes or manual intervention
3Productivity
If traditional implements are used to clear fields, then mechanical rock removal is possible, but safety hazards arise from sparks contact with rotating metallic equipment
Solution Approach 1:
The patent replaces traditional mechanical rock clearing implements with an AI-guided collection system that uses image processing and controlled mechanisms, eliminating the sparks and safety hazards associated with rotating metallic equipment
4Reliability
If multiple passes with traditional implements are performed to clear fields, then more rocks can be removed, but productivity decreases and labor costs increase
Solution Approach 1:
The patent replaces traditional mechanical clearing implements with an AI-based system that achieves high detection accuracy in a single pass, eliminating the need for multiple passes and thereby maintaining both thoroughness and productivity
Data Source
AI summary
An object identification method is disclosed. The method includes training a first neural network for a first set of conditions regarding a first plurality of objects, training a second neural network for a second set of conditions regarding a second plurality of objects, receiving a plurality of target images associated with a third set of conditions in which to identify objects, analyzing the plurality of target images using the first and second neural networks to identify objects in the plurality of target images resulting in object identification information, and selecting the first neural network or the second neural network as a preferred neural network for the third set of conditions based on an analysis of the object identification information.