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Stream/Area:
-
Subject:
-
Paper ID:
10.55041/IJSREM34613
Volume:
8 |
5 |
May 2024
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Plant and tree populations must be preserved and supported in order to mitigate the growing issues brought about by food and water scarcity brought on by population increase and climate change. The occurrence of plant diseases is a major issue in agriculture as it severely reduces agricultural output. In order to overcome this difficulty, scientists are investigating novel approaches that make use of sensors and imaging to collect data on plant health in order to detect diseases early on. The goal of this project is to create a “Smart Plant Health Care System” that combines embedded technologies such as Arduino, Raspberry Pi, and Jetson Nano for pesticide remediation controlled by Arduino and image-based illness diagnosis. More specifically, convolutional neural networks (CNNs) are implemented for real-time illness diagnosis using the processing capacity and adaptability of the Raspberry Pi.
KEYWORDS
Publication Date
12/31/45433
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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No funding information available for this research.
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