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AnthuCare: Smart Farming Application

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dc.contributor.author Fernando, Kirulu
dc.date.accessioned 2025-06-11T08:29:04Z
dc.date.available 2025-06-11T08:29:04Z
dc.date.issued 2024
dc.identifier.citation Fernando, Kirulu (2024) AnthuCare: Smart Farming Application. BSc. Dissertation, Informatics Institute of Technology en_US
dc.identifier.issn 2019324
dc.identifier.uri http://dlib.iit.ac.lk/xmlui/handle/123456789/2499
dc.description.abstract "Anthurium, a plant of significant value in the decorative horticulture industry, faces considerable challenges in its cultivation as a result of its susceptibility to various diseases, such as Bacterial Blight and Bacterial Wilt. These pathogens not only cause a reduction in the aesthetic and economic value of the plants but also place farmers and producers through considerable financial strain. Traditional methods of disease identification and control, which predominantly depend on human observation and general treatment approaches, often prove to be inadequate. As a consequence of their deficiency in precision, velocity, and specificity, treatment is postponed, and disease control is inadequate. This circumstance underscores the critical need for an innovative resolution that has the potential to transform the existing approaches to addressing Anthurium disease." en_US
dc.language.iso en en_US
dc.subject Machine learning en_US
dc.subject CNN en_US
dc.title AnthuCare: Smart Farming Application en_US
dc.type Thesis en_US


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