University of Bahrain
Scientific Journals

Development of an IoT-based Intensive Aquaculture Monitoring System with Automatic Water Correction

Show simple item record Tolentino, Lean Karlo S. De Pedro, Celline P. Icamina, Jatt D. Navarro, John Benjamin E. Salvacion, Luigi James D. Sobrevilla, Gian Carlo D. Villanueva, Apolo A. Amado, Timothy M. Padilla, Maria Victoria C. Madrigal, Gilfred Allen M. 2020-07-21T14:42:03Z 2020-07-21T14:42:03Z 2020-07-01
dc.identifier.issn 2210-142X
dc.description.abstract Due to the depleting stocks of fish in the market, there have been an increased interest in aquaculture. However, raising fishes in an Intensive Aquaculture System results on a low-quality fish or even fish kills as fishes are being cultured in artificial tanks and cage systems, not on their natural habit. This paper presents a water quality monitoring system with automatic correction to monitor and maintain vital water quality parameters essential for fish growth, such as temperature, potential hydrogen (pH) level, oxidation-reduction potential, turbidity, salinity, and dissolved oxygen to achieve optimum yield using Arduino and Raspberry Pi 3B+ through LoRaWAN IoT Protocol. The system uses sensors, microcontrollers, and a web application for acquiring and monitoring data of six different water quality parameters and are maintained in a desired level optimal for fish growth using aquarium heater, motor for sodium bicarbonate distribution, solenoid valve and water pump that serves as correcting devices. The proponents measured the system’s efficiency and reliability through monitoring two intensive aquaculture setups – controlled and conventional setup. From the data gathered, the controlled setup greatly increased efficiency, reduced the work of fish farmers, avoided fish kills, and surpassed yield quality of the conventional setup. en_US
dc.language.iso en en_US
dc.publisher University of Bahrain en_US
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International *
dc.rights.uri *
dc.subject aquaculture en_US
dc.subject Arduino en_US
dc.subject Raspberry P en_US
dc.subject LoRaWAN en_US
dc.subject water temperature en_US
dc.subject pH level en_US
dc.subject oxidation-reduction potential en_US
dc.subject turbidity en_US
dc.subject salinity en_US
dc.subject dissolved oxygen en_US
dc.title Development of an IoT-based Intensive Aquaculture Monitoring System with Automatic Water Correction en_US
dc.type Article en_US
dc.volume 10 en_US
dc.pagestart 1355 en_US
dc.pageend 1365 en_US
dc.source.title International Journal of Computing and Digital Systems en_US
dc.abbreviatedsourcetitle IJCDS en_US

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