Vol. 2 No. 78 (2022): “AgriScience and Technology” scientifi
ISSN 2579-2822
2023; 149–153
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Usage of Nvidia Jetson Nano in Agriculture as an Example of Plant Leaves Illness Real-Time Detection and Classification

D.M. Galstyan*, Eduard Harutyunyan, K.H. Nikoghosyan

“Open Soft Consult” Company. LLC Armenia · “Krisp” Company, Armenia · “Scylla” Company, Armenia

Received: 2024-12-27 · Published: 2023-08-22

© 2023 The Author(s) and the original publisher.

CC BY-NC 4.0 This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
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Originally published in Vol. 2 No. 78 (2022): “AgriScience and Technology” scientifi, 2023 — https://doi.org/10.52276/25792822-2022.2-149.

Original title
Usage of Nvidia Jetson Nano in Agriculture as an Example of Plant Leaves Illness Real-Time Detection and Classification
Authors
D.M. Galstyan, Eduard Harutyunyan, K.H. Nikoghosyan
Source journal
Vol. 2 No. 78 (2022): “AgriScience and Technology” scientifi
Published
2023-08-22
Licence
Creative Commons Attribution-NonCommercial 4.0 International
Original
https://doi.org/10.52276/25792822-2022.2-149

Abstract

Early prediction of plant illnesses can reduce the spread of the disease through efficient resource management and treatment planning. The goal of this article is to integrate the Jetson nanomachine with software based on a pre-trained CNN machine learning model which has been trained via healthy and diseased plant image data. The created video server uses the RTSP protocol to send video data to the Detection Engine. Detected diseases of the host are sent through the SMTP server at an adjustable frequency to the emails of the users. The developed system can be widely used in agriculture, making the fight against plant diseases more profitable and effective.
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