IJBTT

IoTs and Mobile Application Using Deep Learning Analytics for Leaf Disease Tracking in Bush Tomatoes

IoTs and Mobile Application Using Deep Learning Analytics for Leaf Disease Tracking in Bush Tomatoes
	© 2024 by IJETT Journal
	Volume-72 Issue-5
	Year of Publication : 2024
	Author : Wongpanya S. Nuankaew, Veerapat Thongdee, Weerachai Kojakung, Pratya Nuankaew
	DOI : 10.14445/22315381/IJETT-V72I5P115

How to Cite?

Wongpanya S. Nuankaew, Veerapat Thongdee, Weerachai Kojakung, Pratya Nuankaew, " IoTs and Mobile Application Using Deep Learning Analytics for Leaf Disease Tracking in Bush Tomatoes," International Journal of Engineering Trends and Technology, vol. 72, no. 5, pp. 141-148, 2024. Crossref, https://doi.org/10.14445/22315381/IJETT-V72I5P115

Abstract
The research objectives consist of two goals. The first objective is to study, design, and develop a low-bush tomato greenhouse control system. The second objective is to construct a mobile application using deep learning analytics for tracking leaf disease in bush tomatoes. The research data was a study of 400 diseased and normal tomato leaves. Information on tomato leaf diseases studied consisted of six diseases: Early blight, Leaf spot, Leaf blight, Late blight, Leaf mold, and Powdery mildew. The results showed that the developed system can respond effectively to detecting tomato leaf diseases. In addition, the application can perform treatment spraying tasks automatically and manually. From the research results, this research is beneficial and deserves further promotion and development.

Keywords
Leaf disease tracking, Internet of Things, Mobile application for Leaf disease, Deep learning, Treatment.

References
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