Design and Construction of an Arduino-Driven Weight-Based Fish SortingTool

This research aims to design and develop a weight-based fish sorting tool that uses a strain gauge sensor under Arduino Uno control. We designed this tool to enhance the effectiveness and accuracy of the fish sorting process, focusing on three size categories: small, medium, and large. The system consists of a strain gauge sensor that measures the weight of the fish, an HX711 module that converts analog data to digital, a servo motor to move the fish, and a conveyor that moves the fish through the sorting process. We conducted testing to measure the accuracy of the system in determining the fish's weight and its success in classifying it based on its size. The test results show that this device has an average accuracy rate of 99.5%. However, minor differences in weight measurements suggest the need for further improvements. Overall, the fishing industry has enormous potential to implement this tool to increase productivity and reduce reliance on manual methods.

Authors

Publication Details

Journal
INTI JOURNAL.
Published
2024-10-01
DOI
https://doi.org/10.61453/intij.202438
Citations
1
Primary Topic
Water Quality Monitoring Technologies
Type
article
Field-Weighted Citation Impact
0.20
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article

Design and Construction of an Arduino-Driven Weight-Based Fish SortingTool

Md. Mostafa Kamal, Mustafa Kamal, Muhammad Khalidin Basyir
1 citations
INTI JOURNAL.
Water Quality Monitoring Technologies
0.20
article

Design and Construction of an Arduino-Driven Weight-Based Fish SortingTool

Md. Mostafa Kamal, Mustafa Kamal, Muhammad Khalidin Basyir
article en
1 citations

Abstract

This research aims to design and develop a weight-based fish sorting tool that uses a strain gauge sensor under Arduino Uno control. We designed this tool to enhance the effectiveness and accuracy of the fish sorting process, focusing on three size categories: small, medium, and large. The system consists of a strain gauge sensor that measures the weight of the fish, an HX711 module that converts analog data to digital, a servo motor to move the fish, and a conveyor that moves the fish through the sorting process. We conducted testing to measure the accuracy of the system in determining the fish's weight and its success in classifying it based on its size. The test results show that this device has an average accuracy rate of 99.5%. However, minor differences in weight measurements suggest the need for further improvements. Overall, the fishing industry has enormous potential to implement this tool to increase productivity and reduce reliance on manual methods.

INTI JOURNAL.Vol. 2024(1)
Openalex Percentile: Top 45%
Water Quality Monitoring Technologies
0.20
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