Mosquito Sex Sorting Using Imaging and Robotic Picking
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Solution Overview
Problem
The labor-intensive and costly process of sex sorting mosquitoes, particularly in large-scale mosquito SIT programs, is hindered by the challenges of accurately sorting male and female mosquitoes, especially when they are active or in the presence of other insects, leading to inefficiencies and high operational costs.
Innovation Solution
A method and apparatus using imaging and a robot arm to classify and sort mosquitoes by sex, leveraging a trained neural network and robot arm to identify and handle individual mosquitoes in a stationary phase, such as during emergence or after cooling, enabling efficient mechanical sex-sorting.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual sex sorting of mosquitoes is performed, then sorting accuracy can be maintained, but labor costs and operational complexity increase significantly
Solution Approach 1:
The patent replaces manual mechanical sorting with an automated imaging and classification system. A camera captures images of mosquitoes, and a trained neural network automatically classifies them by sex, eliminating the need for manual inspection while maintaining high sorting accuracy.
Solution Approach 2:
The patent uses optical copying through imaging to create a digital representation of the mosquitoes. The camera captures visual information, and the neural network processes these images to classify mosquitoes, replacing direct manual handling with indirect optical detection and digital processing.
2Productivity
If automated imaging and robot arm sorting is implemented, then labor costs decrease and productivity increases, but system complexity and initial investment increase
Solution Approach 1:
The patent replaces manual mechanical sorting operations with an automated system combining imaging, neural network classification, and robot arm manipulation. This substitution enables high-throughput processing while reducing human labor requirements.
Solution Approach 2:
The system performs self-service through automated classification and sorting. The neural network automatically processes images and makes classification decisions, while the robot arm autonomously handles mosquito transfer based on classification results, minimizing human intervention.
3Ease of operation
If mosquitoes are sorted during active adult phase, then classification can be performed, but mosquitoes may move or fly away reducing sorting efficiency
Solution Approach 1:
The patent applies preliminary cooling to mosquitoes before classification to reduce their activity. By lowering the temperature, mosquitoes become less active and remain in position longer, allowing sufficient time for imaging and classification without losing the target specimens.
Solution Approach 2:
The patent changes the temperature parameter of the mosquito environment to control mosquito activity. By adjusting temperature, the system optimizes the balance between keeping mosquitoes alive and maintaining them in a relatively stationary state for accurate imaging and classification.
Data Source
AI summary
Method and apparatus for mechanical sex-sorting of mosquitoes by extracting a class of mosquitoes from unsorted mosquitoes comprises obtaining unsorted mosquitoes, obtaining images of individual mosquitoes in a stationary phase, electronically classifying the individuals from the images into male mosquitoes and/or female mosquitoes, and possibly also unclassified objects; obtaining co-ordinates of individuals of at least one of the male mosquito and female mosquito classifications, and using a robot arm to reach an individual identified by the obtained coordinates to store or remove the individuals, thereby to provide sex-sorted mosquitoes.