1. My Scholar, Digital Library Repository, Universiti Malaysia Kelantan
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  3. Faculty of Earth Science - Other Publication
Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/2410
DC FieldValueLanguage
dc.contributor.authorShaparas Dalimanen_US
dc.contributor.authorNur Ain Najwa Mohd Adiben_US
dc.contributor.authorNazahatul Anis Amaludinen_US
dc.contributor.authorNoor Janatun Naim Jemalien_US
dc.contributor.authorAweng Eh Raken_US
dc.contributor.authorNordiana Abd Azizen_US
dc.date.accessioned2022-01-10T05:17:33Z-
dc.date.available2022-01-10T05:17:33Z-
dc.date.issued2021-09-
dc.identifier.isbn978-967-2912-89-7-
dc.identifier.urihttp://hdl.handle.net/123456789/2410-
dc.descriptionOthersen_US
dc.description.abstractWith the adaptability of Internet of Things technologies, oil palm tree growth data and fertilization management can be utilizing effortlessly and effectively. The context of conceptual framework comprises the loT technologies, image processing, machine learning and deep learning which focuses on environmental factors that effecting the oil palm tree growth that involve temperature, humidity, soil moisture content, light and nutrient will be analyses.en_US
dc.publisherUMK Publicationen_US
dc.titleSmart Fertilization Management for Oil Palm Tree Based on IOT and Deep Learning.en_US
dc.typeNationalen_US
dc.description.page15-16en_US
dc.title.titleofbooke-Proceedings for Carnival of Research and Innovation (CRI 2021) in conjunction with International Virtual Innovation & Invention Challenge (INTELLIGENT 2021) & Creative Innovation Carnival (CIC2021).en_US
dc.description.typeProceeding Papersen_US
dc.contributor.correspondingauthorshaparas@umk.edu.myen_US
item.fulltextWith Fulltext-
item.openairetypeNational-
item.grantfulltextopen-
crisitem.author.deptUniversiti Malaysia Kelantan-
crisitem.author.deptUNIVERSITI MALAYSIA KELANTAN-
crisitem.author.orcidhttps://orcid.org/0000-0003-2093-5113-
Appears in Collections:Faculty of Earth Science - Other Publication
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