Automated Insect Detection and Removal via Image Analysis
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Solution Overview
Problem
The proliferation of insects such as thrips, mites, and aphids in food and crops is exacerbated by the decreased effectiveness of pesticides, making it difficult to detect and remove these pests, especially those invisible to the untrained eye, and large-scale methods often harm the food or materials being treated.
Innovation Solution
A computer image analysis system that magnifies images of substrates to detect insects using trained processors to recognize their characteristics, triggering an action head for removal or disposal, and can be mounted on movable platforms or drones for wide-area scanning and mitigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If pesticides are used to control insects, then insect population is reduced, but effectiveness decreases over time and pesticide resistance develops
Solution Approach 1:
The patent replaces chemical pesticides with a mechanical/optical system consisting of image capturing devices, processors, and action heads that physically remove insects through suction, impact, or other mechanical means, thereby eliminating pesticide resistance issues
Solution Approach 2:
The system enables self-service insect control by using automated image recognition and response mechanisms that detect and eliminate insects without human intervention or chemical substances, making the control process self-sufficient and environmentally friendly
2Reliability
If large scale heating is used to eliminate insects, then insect infestation is reduced, but the food or material to be cleansed is harmed
Solution Approach 1:
The system applies localized treatment by targeting only the specific locations where insects are detected through image capturing devices, using action heads to eliminate pests at precise coordinates without exposing the entire food or material to harmful heating or chemical treatments
Solution Approach 2:
The system extracts and removes only the harmful insect elements from the food or material through targeted action heads that suction, impact, or otherwise eliminate pests while leaving the underlying substrate intact and undamaged
3Measurement precision
If manual inspection is used to detect insects, then detection accuracy for visible insects is achieved, but invisible or small insects cannot be detected
Solution Approach 1:
The system creates optical copies or digital representations of the inspected surface through image capturing devices, allowing enhanced visualization and analysis of insects that are too small or invisible to human eyes, thereby extending detection capabilities beyond manual inspection limits
Solution Approach 2:
The system transitions from two-dimensional visual inspection to multi-dimensional analysis by capturing images at different magnifications, angles, and potentially using multiple spectral ranges, enabling detection of insects across various size scales that would be imperceptible in normal viewing conditions
4Measurement precision
If automated image analysis system is deployed, then detection precision and response speed are improved, but device complexity increases
Solution Approach 1:
The system achieves universality by integrating multiple functions into a single platform: image capturing devices for detection, processors for analysis and recognition, and action heads for elimination, allowing one system to perform detection, identification, and treatment across various insect types and substrates
Solution Approach 2:
The system merges previously separate functions (inspection, detection, analysis, and treatment) into an integrated automated platform where image capturing devices, processors, and action heads work as a unified system, reducing operational complexity despite increased technological integration
Data Source
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AI summary
A device for pollinating plants such as flowering trees. The device is a movable platform such as a drone that has an image capturing device that is in communication with image recognition software. Images of plants are analyzed to detect objects that are consistent with pollen-receiving plants and/or plant areas. Once such plant object is detected, the device automatically disperses pollen in the proximity of the detected plant or plant object.