AI Insect Trap Identification for Selective Pest Capture
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Insect traps often indiscriminately capture insects without distinguishing between harmful and beneficial species, leading to unintentional harm and inefficiencies in pest management, and existing AI-based identification systems face challenges with data limitations and imbalanced datasets.
Innovation Solution
An insect trap system utilizing a computing device with AI vision-based technology to identify insect species and selectively trap or eliminate harmful pests, incorporating an entrance device, identification chamber, imaging device, elimination chamber, and release chamber, with machine learning models for accurate classification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If traditional insect traps are used to capture insects, then insect capture quantity is improved, but identification accuracy deteriorates because they cannot distinguish between harmful and beneficial species
Solution Approach 1:
The patent replaces traditional mechanical insect traps with an automated system that uses imaging devices and AI vision-based identification to distinguish between harmful and beneficial insects. The system uses cameras to capture insect images, processes them through machine learning models, and automatically controls trap activation based on identification results, eliminating the need for manual inspection and enabling precise species-specific targeting.
Solution Approach 2:
The system enables self-service through automated identification and decision-making. The AI-based identification system automatically analyzes captured insect images, determines species identity, and controls the trap mechanism without human intervention. The system serves itself by making real-time decisions about which insects to trap based on their identification, eliminating the need for continuous manual monitoring and control.
2Measurement precision
If AI-based identification systems are used to distinguish insect species, then identification accuracy is improved, but device complexity deteriorates due to data processing requirements
Solution Approach 1:
The patent introduces an intermediary processing layer between image capture and trap activation. The AI vision-based identification system serves as this intermediary, receiving raw images from cameras, processing them through machine learning models to determine species identity, and then transmitting control signals to the trap mechanism. This intermediary layer manages the complexity of data processing centrally, allowing the overall system to remain coordinated despite the sophisticated identification capabilities.
3Device complexity
If manual insect identification methods are used, then device complexity is reduced, but productivity deteriorates due to time-consuming processes
Solution Approach 1:
The system eliminates manual identification labor by implementing self-service through automated AI-based recognition. The vision-based system continuously captures images of insects, automatically identifies species through machine learning, and triggers appropriate trap responses without human involvement. This self-service capability dramatically increases productivity by processing multiple insects simultaneously and continuously, rather than requiring manual inspection and identification of each specimen.
Data Source
AI summary
An insect trap system includes an insect trap device and a computing device coupled to the insect trap device. The computing device includes a memory having instructions stored thereon for selectively trapping an insect in the insect trap device and one or more processors coupled to the memory and configured to execute stored instructions to determine an identity of an insect located within the insect trap device. The insect trap device is operated to selectively trap, based on the determined identity, the insect within the insect trap device. A method of selectively trapping an insect in an insect trap device is also disclosed.