Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/2169
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dc.contributor.authorGamage, M. P. A. W-
dc.contributor.authorKasthurirathna, D-
dc.contributor.authorParesith, M. M-
dc.contributor.authorThayakaran, S-
dc.contributor.authorSuganya, S-
dc.contributor.authorPuvipavan, P-
dc.date.accessioned2022-05-03T08:25:42Z-
dc.date.available2022-05-03T08:25:42Z-
dc.date.issued2019-10-
dc.identifier.urihttp://rda.sliit.lk/handle/123456789/2169-
dc.description.abstractThis paper present a way to aid farmers focusing on profitable vegetable cultivation in Sri Lanka. As agriculture creates an economic future for developing countries, the demand of modern technologies in this sector is higher. Key technologies used for this problem are Deep Learning, Machine Learning and Visualization. As the product, an android mobile application is developed. In this application the users should input their location to start the prediction process. Data preprocessing is started when the location is received to the system. The collected dataset divided into 3 parts. 80 percent for training, 10 percent for testing and 10 percent for validation. After that the model is created using LSTM RNN for vegetable prediction and ARIMA for price prediction. Finally, for given location profitable crop and predicted future price of vegetables are shown in the application. Other than the prediction, optimizing for multiple crop sowing according to the user requirements and visualizing cultivation and production data on map and graphs are also given in the application. This paper elaborates the procedure of model development, model training and model testing.en_US
dc.language.isoenen_US
dc.publisherhttps://ijisrt.com/agrogenius-crop-prediction-using-machine-learningen_US
dc.relation.ispartofseriesInternational Journal of Innovative Science and Research Technology ( IJISRT);Vol 4 Issue 10 Pages 243-249-
dc.subjectMachine Learningen_US
dc.subjectAndroid Applicationen_US
dc.subjectData preprocessingen_US
dc.subjectLSTMen_US
dc.subjectRNNen_US
dc.subjectARIMAen_US
dc.subjectLinear Programmingen_US
dc.subjectVisualizationen_US
dc.subjectPolygonsen_US
dc.titleAgro-Genius: Crop Prediction Using Machine Learningen_US
dc.typeArticleen_US
Appears in Collections:Research Papers - Open Access Research
Research Papers - SLIIT Staff Publications
Research Publications -Dept of Information Technology

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