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https://rda.sliit.lk/handle/123456789/3159
Title: | BlossomSnap: A Single Platform for all Anthurium Planters Based on The Sri Lankan Market |
Authors: | Rathnayake, R.M.S.T Tharika Pramodi, M.L.A.D. Gayathree, I. R Rashmika, L.K.R Gamage, M Gamage, A |
Keywords: | chatbot deep learning diagnosis extensively image processing machine learning natural language processing numerous substantial |
Issue Date: | 15-Oct-2022 |
Publisher: | Institute of Electrical and Electronics Engineers |
Citation: | R. M. S. T. Rathnayake, M. L. A. D. Tharika Pramodi, I. R. Gayathree, L. K. R. Rashmika, M. Gamage and A. Gamage, "BlossomSnap: A Single Platform for all Anthurium Planters Based on The Sri Lankan Market," 2022 IEEE 13th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON), Vancouver, BC, Canada, 2022, pp. 0135-0141, doi: 10.1109/IEMCON56893.2022.9946542. |
Series/Report no.: | 2022 IEEE 13th Annual Information Technology, Electronics and Mobile Communication Conference, IEMCON 2022;Pages 135 - 141 |
Abstract: | The popular and extensively grown flowering plant known as the Anthurium is prized for its beauty. In Sri Lanka, anthuriums have a substantial international market. Although it is a significant field that can be further developed by expanding the market, but it has led to a lack of attention, resources, and a moderate cost of production, as well as from the absence of an appropriate market channel, all of which have led to lower productivity and quality. As a result, Anthurium growers have numerous challenges both in terms of production and marketing. This paper introduces a novel mobile application 'BlossomSnap' which involves automating and significantly enhancing the outdated manual process. Using natural language processing, machine learning, and deep learning approaches, the proposed system analyzes the diseases, pests, varieties, and the highest quality plants to create a more secure growing environment. It will provide high-quality, cost effective, and timely services. The first step of anthurium plant disease and pest diagnosis is carried out using image processing, deep learning, and machine learning technologies. In order to identify the infection stage, the following steps involve extracting, classifying, and detecting images of Anthurium flowers and leaves. The accuracy was checked by comparing actual results taken from experts with the predicted results obtained from the proposed system. 'BlossomSnap' achieves an average accuracy of more than 80% and produces a better overall result. An in-place chatbot technology is intended to assist new planters with their problems. The Anthurium plant variety and quality detection methodology is used in concert with to determine the optimum market opportunity. |
URI: | https://rda.sliit.lk/handle/123456789/3159 |
ISBN: | 978-166546316-4 |
Appears in Collections: | Department of Information Technology |
Files in This Item:
File | Description | Size | Format | |
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BlossomSnap_A_Single_Platform_for_all_Anthurium_Planters_Based_on_The_Sri_Lankan_Market.pdf Until 2050-12-31 | 583.32 kB | Adobe PDF | View/Open Request a copy |
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