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Published Paper Details:
AI- Powered Early Plant Stress Detection Using Simulated Physiological Signals And LSTM With Streamlit Interface
Authors
Chandana R,Meghana J,Muddu Rathna,Vinay K
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Keywords
Plant Stress Detection, LSTM, Deep Learning, Chlorophyll, Leaf Temperature, Soil Moisture, Streamlit, Simulated Data
Abstract
Detection of Plant disease after the symptoms that is visible on the leaf is sometimes too late to prevent the crops being affecting by that since the disease spreads from one leaf to another through direct contact, Rain Splash, vectors, pruning tools etc .
Plants unfavourable condition which we commonly call as the stress ,which affects the plants health. So using the physiological signals like chlorophyll fluorescence ,leaf temperature and soil Moisture, we can detect whether plant is healthy or in stress. With the help of LSTM model we identify plants stress condition and it is visible using the interface streamlit.When we use the physiological signal data then there is less change of cutting the plant ,or removing the plant due to disease, as it is the signs that shown before the symptoms that arise on the leaves. So many research had done on this as they have used the single physiological signals in large form .But in are approach we have used the multi-fusion of physiological signal data is used.
IJCRT's Publication Details
Unique Identification Number - IJCRT2508473
Paper ID - 292598
Author type - Indian Author
Page Number(s) - e148-e155
Pubished in - Volume 13 | Issue 8 | August 2025
DOI (Digital Object Identifier) -
No Of Downloads - 82
Author Country - India, 560060, Bengaluru, Bengaluru, 560060, Other area not in list
Publisher Name - IJPUBLICATION | www.ijcrt.org | ISSN : 2320-2882
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Chandana R,Meghana J,Muddu Rathna,Vinay K, "AI- Powered Early Plant Stress Detection Using Simulated Physiological Signals And LSTM With Streamlit Interface", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.13, Issue 8, pp.e148-e155, August 2025, Available at :http://www.ijcrt.org/papers/IJCRT2508473.pdf
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