Please use this identifier to cite or link to this item: http://ir.futminna.edu.ng:8080/jspui/handle/123456789/18781
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dc.contributor.authorFolorunso, Taliha Abiodun-
dc.contributor.authorBala, Jibril Abdullahi-
dc.contributor.authorAdedigba, Adeyinka Peace-
dc.contributor.authorOlatunji, Babatunde Eric-
dc.contributor.authorMingyi, Caroline-
dc.date.accessioned2023-05-09T13:49:41Z-
dc.date.available2023-05-09T13:49:41Z-
dc.date.issued2022-
dc.identifier.citationTaliha Abiodun Folorunso, Jibril Abdullahi Bala, Adeyinka Peace Adedigba, Babatunde Eric Olatunji, and Caroline Mingyi. (2022). Internet of Things-Based Surveillance and Feeding System for Aquaculture Applications. Journal of Contents Computing, Vol. 4, No. 2, pp. 479-490. http://dx.doi.org/10.9728/jcc.2022.12.4.2.479en_US
dc.identifier.urihttp://repository.futminna.edu.ng:8080/jspui/handle/123456789/18781-
dc.description.abstractIn both developed and developing countries, the agricultural sector is playing a significant role in driving economic growth. In Nigeria, there has been an increased push to diversify the economy through agriculture, and aquaculture has been identified as a key sector to aid in this effort. However, the sector faces various challenges, such as poor water quality, feeding-related issues, pest control, disease, and predator control, resulting in reduced output and lower incomes. Previous research has aimed to provide solutions to these challenges, but some works only focus on monitoring water quality, disease, or surveillance against predators or theft, without considering feeding rates. Therefore, a monitoring and surveillance system is required to minimize death rates caused by hunger and increase productivity. This work presents the use of IoT to enable real-time monitoring in aquaculture. The system successfully initiated and terminated the feeding process in the pond within a 3-second timeframe and provided a live feed of the pond's activities to the farm remotely and in real-time. The system achieved a performance of 90% and 88.8% for accuracy and precision, respectively.en_US
dc.language.isoenen_US
dc.publisherJournal of Contents Computingen_US
dc.subjectIoTen_US
dc.subjectAquacultureen_US
dc.subjectFish-Feedingen_US
dc.subjectSurveillanceen_US
dc.titleInternet of Things-Based Surveillance and Feeding System for Aquaculture Applicationsen_US
dc.typeArticleen_US
Appears in Collections:Mechatronics Engineering

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