Development of an Intelligent Aquaculture Control System for Fish Farm”, Journal of Science Technology Mathematics and Education (JOSTMED)

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Date

2017-06-17

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Journal of Science Technology Mathematics and Education (JOSTMED)

Abstract

Fish farming has become an important practice worldwide and it has been existence for many years. The growing and cultivation of fish which is an important branch of agriculture has served as a source of protein, vitamin and oil for mankind. Manual method of feeding at any choice of tie and inadequate water level monitoring device has been identified to be a limitation affecting the survival of fish in the pond. To this extend, there is a need to constantly monitor water level in the pond due to the fact that water can be lost as a result of seepage and inadequate watershed area which also interferes with fish movement to see and capture prey. In this research, an intelligent aquaculture control system using a fuzzy logic approach has been developed. The developed system is capable of providing feed to fishes at a selected time interval and also detecting and maintaining the level of water in the fish pond by pumping water if the need arises. The overall system performance was achieved base don the system response from generated rules of the fuzzy logic system. This research can further be improved by using the internet and data transmission system for further analysis and remote monitoring of the fish pond.

Description

This paper presents the development of an intelligent aquaculture control system using a fuzzy logic approach to address key challenges in traditional fish farming, such as manual feeding and inadequate water level monitoring. Recognizing fish farming as a vital source of protein, vitamins, and oils, the study highlights the need for automated systems to ensure optimal fish survival and growth. The proposed system automates fish feeding at set intervals and monitors water levels, activating a pump when necessary to maintain suitable conditions in the pond. System performance was evaluated based on responses generated from fuzzy logic rules. The authors suggest future improvements by integrating internet connectivity and data transmission for enhanced analysis and remote monitoring.

Keywords

Feed, water, Pond, Fuzzy Logic, Membership Function

Citation

Maliki, D., Lawrence, C., Nuhu B. K., Abdullahi I. M., & Umar, B. U. (2017), “Development of an Intelligent Aquaculture Control System for Fish Farm”, Journal of Science Technology Mathematics and Education (JOSTMED), Vol. 13, No.2, pp45-51.

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