Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/1820
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dc.contributor.authorWickramasinghe, C. P-
dc.contributor.authorLakshitha, P. L. N-
dc.contributor.authorHemapriya, H. P. H. S-
dc.contributor.authorJayakody, A-
dc.contributor.authorRanasinghe, P. G. N. S-
dc.date.accessioned2022-03-31T05:22:31Z-
dc.date.available2022-03-31T05:22:31Z-
dc.date.issued2019-12-05-
dc.identifier.citationC. P. Wickramasinghe, P. L. N. Lakshitha, H. P. H. S. Hemapriya, A. Jayakody and P. G. N. S. Ranasinghe, "Smart Crop and Fertilizer Prediction System," 2019 International Conference on Advancements in Computing (ICAC), 2019, pp. 487-492, doi: 10.1109/ICAC49085.2019.9103422.en_US
dc.identifier.isbn978-1-7281-4170-1-
dc.identifier.urihttp://rda.sliit.lk/handle/123456789/1820-
dc.description.abstractAgricultural industry plays a major role in the process of economic development as well as the Gross Domestic Product of Sri Lanka. One of the significant issues in the industry is lacking an accurate way to identify the best crop that can be grown with the available soil fertility in a particular land. Since most of the farmers have a lack of knowledge about soil nutrients, they start cultivations by believing myths in society and few of them use scientific approaches. This research mainly focuses on suggesting the best crop according to soil fertility of land and also it recommends a fertilizer plan to optimize the amount of fertilizers applied for suggested crops. The paper presents a tool with embedded sensors that measure soil fertility and developed a cross- platform mobile application to suggest the best crops according to available soil fertility. Further, a fertilizer plan will be suggested to optimize fertilizer usage in order to increase profitability and avoid soil degradation. To evaluate the final product, the same soil sample was tested in the lab and using sensors embedded tool. Results obtained by those tests proven that both generate approximately equal Nitrogen (N), Phosphorus (P) and Potassium (K) values.en_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.ispartofseries2019 International Conference on Advancements in Computing (ICAC);Pages 487-492-
dc.subjectSmart Cropen_US
dc.subjectFertilizeren_US
dc.subjectPrediction Systemen_US
dc.titleSmart Crop and Fertilizer Prediction Systemen_US
dc.typeArticleen_US
dc.identifier.doi10.1109/ICAC49085.2019.9103422en_US
Appears in Collections:1st International Conference on Advancements in Computing (ICAC) | 2019
Department of Computer Systems Engineering-Scopes
Research Papers - Dept of Computer Systems Engineering
Research Papers - IEEE
Research Papers - SLIIT Staff Publications

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