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     Research Journal of Applied Sciences, Engineering and Technology


The Use of Vision in a Sustainable Aquaculture Feeding System

Jer-Vui Lee, Joo-Ling Loo, Yea-Dat Chuah, Pek-Yee Tang, Yong-Chai Tan and Wei- Jian Goh
Department of Mechatronics and Biomedical Engineering, Faculty of Engineering and Science, Universiti Tunku Abdul Rahman, Kuala Lumpur, Malaysia
Research Journal of Applied Sciences, Engineering and Technology  2013  19:3658-3669
http://dx.doi.org/10.19026/rjaset.6.3573  |  © The Author(s) 2013
Received: January 05, 2013  |  Accepted: February 18, 2013  |  Published: October 20, 2013

Abstract

Dairy feeding causes significant water pollution. By controlling the proper amount of feed, reducing the waste to minimum will effectively reduce the problem of water contamination. In this project, a Sustainable Aquaculture Feed System (SAFS) has been designed and developed. It can automatically feed the fishes by estimating fishes’ appetite through machine vision. The discussion includes design and optimization of the vision system using Labview as well as the integration of various components in the SAFS. With the developed algorithm, the system is able to detect the presence of fishes and count the number of fishes. The outcome is able to estimate and infer the fish appetite. Therefore, the feeding time can be planned ahead. In addition, the system includes a Graphical User Interface (GUI) for monitoring, display the feeding status and sensors reading such as pH, turbidity and temperature.

Keywords:

Aquaculture, body, fish count and feeding, machine vision, smart system,


References


Competing interests

The authors have no competing interests.

Open Access Policy

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Copyright

The authors have no competing interests.

ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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