dc.contributor.author | Tolentino, Lean Karlo S. | |
dc.contributor.author | De Pedro, Celline P. | |
dc.contributor.author | Icamina, Jatt D. | |
dc.contributor.author | Navarro, John Benjamin E. | |
dc.contributor.author | Salvacion, Luigi James D. | |
dc.contributor.author | Sobrevilla, Gian Carlo D. | |
dc.contributor.author | Villanueva, Apolo A. | |
dc.contributor.author | Amado, Timothy M. | |
dc.contributor.author | Padilla, Maria Victoria C. | |
dc.contributor.author | Madrigal, Gilfred Allen M. | |
dc.date.accessioned | 2020-07-21T14:42:03Z | |
dc.date.available | 2020-07-21T14:42:03Z | |
dc.date.issued | 2020-07-01 | |
dc.identifier.issn | 2210-142X | |
dc.identifier.uri | https://journal.uob.edu.bh:443/handle/123456789/4040 | |
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.description.abstract | ||
dc.language.iso | en | en_US |
dc.publisher | University of Bahrain | en_US |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 International | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
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.identifier.doi | http://dx.doi.org/10.12785/ijcds/1001120 | |
dc.identifier.doi | ||
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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