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Title: Intelligent disease detection system for greenhouse with a robotic monitoring system
Authors: Fernando, S
Nethmi, R
Silva, A
Perera, A
De Silva, R
Abeygunawardhana, P. K. W
Keywords: Intelligent Disease
Detection System
Robotic Monitoring System
Disease diagnosis
Image processing
Machine Learning
Issue Date: 10-Dec-2020
Publisher: IEEE
Citation: S. Fernando, R. Nethmi, A. Silva, A. Perera, R. De Silva and P. K. W. Abeygunawardhana, "Intelligent Disease Detection System for Greenhouse with a Robotic Monitoring System," 2020 2nd International Conference on Advancements in Computing (ICAC), 2020, pp. 204-209, doi: 10.1109/ICAC51239.2020.9357143.
Series/Report no.: 2020 2nd International Conference on Advancements in Computing (ICAC);Vol 1 Pages 204-209
Abstract: Greenhouse farming plays a significant role in the agricultural industry because of its controlled climatic features. Recent examinations have stated that the mean creation of the yields under greenhouses is lessening due to disease events in the plants. These foods have become an imposing undertaking because these plants are being assaulted by different bacterial diseases, micro-organisms, and pests. The chemicals are applied to the plants intermittently without thinking about the necessity of each plant. Several problems have occurred in the greenhouse environment due to these causes. Therefore, there is a huge necessity for a system to detect diseases at an early stage. This research focused on designing a system to detect disease, which causes yellowish in greenhouse plants. Plant yellowing can be considered a significant problem of plants that grow under greenhouse-controlled environments. Through this research is focused on the most important and one of the most attention-grabbing crop tomato. There are specific diseases that cause yellowish the tomato plant, and they have been identified. The techniques utilized for early recognition of infection are image processing, machine learning, and deep learning.
ISBN: 978-1-7281-8412-8
Appears in Collections:Research Papers - Dept of Computer Systems Engineering
Research Papers - IEEE
Research Papers - SLIIT Staff Publications

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