Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/973
Title: Auto Training an AI for Detecting Plant Disease Using Twitter Data Annexed With a Plant Anthology
Authors: Vasanthan, N.
Shimran, Mohamed
Ahkam, A.
Ishak, I.
Silva, C.
Kuruppu, T.A.
Keywords: Continuous Learning
Twitter
CNN
Auto-Keras
AutoML
Image Classification
Web Data Extraction
Business Intelligence
Issue Date: 9-Dec-2021
Publisher: 2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT
Abstract: Agricultural productivity plays a vital role in contributing to a nation’s economy. Farmers nowadays are concerned due to disease persistence in crops and plants, and it also affects the economy indirectly, so it is important to come up with a solution to detect plant diseases and educate the farmers about the solutions to retaliate against the diseases. Proper care is mandatory to safeguard the quality of plants. The existing traditional methods consume a massive amount of time and resources hence, it’s costly. Due to the importance of continuous monitoring, it seems impractical for a farmer to implement the traditional methods on large scale. The Traditional systems which are used lack the ability to identify diseases out of their predefined scope. As a solution, we came up with an autolearning system that identifies new plant diseases and provides remedies. This paper showcases the image processing techniques to detect plant diseases, Auto ML techniques to create new models for plants and corresponding diseases, Diseases are identified using image processing, Remedies are extracted for the given plant diseases using unstructured data from web data crawling. The business intelligence model uses NLP to provide ideas about the trending plants and plantrelated diseases are also discussed in this paper.
URI: http://rda.sliit.lk/handle/123456789/973
ISSN: 978-1-6654-0862-2/21
Appears in Collections:3rd International Conference on Advancements in Computing (ICAC) | 2021
Department of Computer systems Engineering-Scopes
Research Papers - IEEE

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