International Research Journal of Innovations in Engineering and Technology - IRJIET International Open Access, Monthly, Peer Reviewed, Reputed Journal ISSN (online): 2581-3048

Impact Factor (2025): 6.9

DOI Prefix: 10.47001/IRJIET

An Integrated Platform for the Identification of Suitable Lands and Soil Conditions for Remunerative Crops in Sri Lanka

R.R.Nimesha ManchaleeDepartment of Information Technology, Sri Lanka Institute of Information Technology, Malabe, 10115, Sri LankaMadhushika A.H.DDepartment of Information Technology, Sri Lanka Institute of Information Technology, Malabe, 10115, Sri LankaW.G.H JanadeepaDepartment of Information Technology, Sri Lanka Institute of Information Technology, Malabe, 10115, Sri LankaP.D.A.M.ArachchigeDepartment of Information Technology, Sri Lanka Institute of Information Technology, Malabe, 10115, Sri LankaMr. Sathira HettiarachchDepartment of Information Technology – Computing (FOC), Sri Lanka Institute of Information Technology, Malabe, 10115, Sri LankaMrs. Devanshi GanegodaDepartment of Information Technology – Computing (FOC), Sri Lanka Institute of Information Technology, Malabe, 10115, Sri Lanka

Vol 7 No 11 (2023): Volume 7, Issue 11, November 2023 | Pages: 217-224

International Research Journal of Innovations in Engineering and Technology

OPEN ACCESS | Research Article | Published Date: 10-11-2023

doi Logo doi.org/10.47001/IRJIET/2023.711030

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Abstract

Agriculture in Sri Lanka faces several limitations that impact its development and productivity, including land constraints, climate change impacts, and limited technology adoption. To address these challenges, this research presents an integrated platform combining IoT, GIS mapping, remote sensing, and data analytics. The platform facilitates the identification of optimal lands and soil conditions for cultivating remunerative crops, including coconut, saffron, and vanilla. The study achieved a 98% accuracy in crop prediction using machine learning algorithms, and plant disease detection surpassed 95% accuracy. These results demonstrate the potential to revolutionize agriculture in Sri Lanka and contribute to economic growth and food security.

Keywords

Remunerative crops, machine learning in agriculture, smart agriculture


Citation of this Article

R.R.Nimesha Manchalee, Madhushika A.H.D, W.G.H Janadeepa, P.D.A.M.Arachchige, Mr. Sathira Hettiarachch, Mrs. Devanshi Ganegoda, “An Integrated Platform for the Identification of Suitable Lands and Soil Conditions for Remunerative Crops in Sri Lanka” Published in International Research Journal of Innovations in Engineering and Technology - IRJIET, Volume 7, Issue 11, pp 217-224, November 2023. Article DOI https://doi.org/10.47001/IRJIET/2023.711030

Licence Copyright (c) 2026 International Research Journal of Innovations in Engineering and Technology creative common licence This work is licensed under Creative common Attribution Non Commercial 4.0 Internation Licence
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