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JACIII Vol.21 No.2 pp. 211-220
doi: 10.20965/jaciii.2017.p0211
(2017)

Paper:

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Behavioural Response Analysis Using Vision Engineering (BRAVENet)

Reggie C. Gustilo* and Elmer P. Dadios**

*ECE Department, De La Salle University
2401 Taft Avenue, Manila, Philippines

**MEM Department, De La Salle University
2401 Taft Avenue, Manila, Philippines

Received:
July 25, 2016
Accepted:
October 31, 2016
Online released:
March 15, 2017
Published:
March 20, 2017
Creative Commons License
Keywords:
machine vision, aquaculture, fuzzy logic, intelligent systems
Abstract
A new engineering methodology is proposed to improve the automation process in monitoring the water quality in a small scale aquaculture system. Behavioural Response Analysis using Vision Engineering Network or BRAVENet is proposed, as a support system to a traditional sensor-based system, to monitor critical water quality parameters such as temperature, pH, salinity and dissolved oxygen. BRAVENet is based on the reactions or behavioural responses of tiger prawns to different water conditions. The performance of both the sensor-based system and BRAVENet are analysed and discussed. It is shown that the BRAVENet can identify unsafe levels of water parameters and is a good monitoring and prediction tool for water conditions especially those instances when industry grade sensors fail or become erroneous. Promising results show that BRAVENet can be used as a support system, if not as a replacement, in continuously monitoring the status of the critical water quality parameters of aquaculture systems.
Cite this article as:
R. Gustilo and E. Dadios, “Behavioural Response Analysis Using Vision Engineering (BRAVENet),” J. Adv. Comput. Intell. Intell. Inform., Vol.21 No.2, pp. 211-220, 2017.
Data files:
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Last updated on Oct. 01, 2024