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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM42325
Volume:
9 |
3 |
Mar 2025
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.
This venture gives an AI-powered plant leaf disease detection device included with an automated pesticide sprinkler the usage of Raspberry Pi three. Leveraging deep mastering and pc vision, the gadget identifies leaf diseases through photo processing and initiates a targeted pesticide spray. A digicam module captures real-time images of plant leaves, and a trained convolutional neural network (CNN) version classifies diseases along with blight, mildew, or rust. based totally on detection, a relay-managed motor activates the pesticide sprayer. The gadget gives a cost-effective, power-green answer for actual-time precision agriculture, reducing chemical usage and enhancing crop fitness monitoring. key phrases – Plant disorder detection, Raspberry Pi, CNN, photograph Processing, IoT Agriculture, Precision Farming
KEYWORDS
Publication Date
5/6/2025
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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