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dc.contributor.authorKarunarathna, KKLD
dc.contributor.authorWijayarathne, WMSRB
dc.date.accessioned2026-03-11T05:08:51Z
dc.date.available2026-03-11T05:08:51Z
dc.date.issued2026-01
dc.identifier.urihttps://ir.kdu.ac.lk/handle/345/9049
dc.description.abstractThe paddy industry in Sri Lanka continues to be essential to both rural livelihoods and national food security. Small and medium-sized farmers deal with a number of ongoing issues, such as poor scheduling of farm operations, inconsistent fertilizer use, ineffective communication with agricultural officers, and restricted access to real-time weather and advisory information. This study presents GreenHarvest, a role-based agrarian information and notification platform to maximize paddy cultivation in Sri Lanka, in order to address aforementioned problems. Weather forecasting, calendar-based task scheduling, fertilizer requirement calculation, and a farmer specific notification service are all integrated into the system. The project employs Google Maps API for location tracking, Microsoft SQL Server as the database, and.NET for both frontend and backend development, GreenHarvest enables smooth communication between agrarian officers and farmers. Paddy farmers in Kuliyapitiya participated in a pilot study that assessed the system’s usability, accuracy, efficacy, and satisfaction. The results demonstrated high user satisfaction and significant gains in yield management and operational efficiency were demonstrated by the results. This study indicates that GreenHarvest is a practical digital solution that can improve decision-making, expedite agricultural advisory services, and assist Sri Lanka’s shift to a paddy cultivation model that is more sustainable, and data driven.en_US
dc.language.isoenen_US
dc.subjectgreenharvest, agrarian platform, role-based information management, task scheduling, digital agricultureen_US
dc.titleGreenHarvest: A Digital Agrarian Platform to Enhance Paddy Cultivation Efficiency through Role-Based Information Management in Sri Lankaen_US
dc.typeArticle Abstracten_US
dc.identifier.facultyFOCen_US
dc.identifier.journalFOCSSen_US
dc.identifier.issue6en_US
dc.identifier.pgnos18en_US


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