Real Time Leaf Disease Detection Using Deep Learning Method
Authors
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Kalyani Government Engineering College, Nadia, West Bengal ,IN
Sagnik Ghosh -
Kalyani Government Engineering College, Nadia, West Bengal ,INBandana Barman
DOI:
https://doi.org/10.24906/isc/2021/v35/i4/210001Keywords:
CNN, Arduino IDE, Moister Sensor, OpenCV, Leaf Disease.Abstract
Due to regular occurrences of hot and humid climate of the country, crops are destroyed by invasion of certain diseases. As a result, entire farm gets affected and huge loss and damage happens for the farmers. This paper focuses on developing a system which detects at the onset of any disease by continuous monitoring of leaves. In addition, a moisture measuring device is also fitted which allows the microcontroller to spray water from a tank whenever there is a shortage. Secondly, leaf disease detection system achieved by deep learning, also instruct a second microcontroller to spray desired amount of pesticide as and where required. A web application made for this also instructs farmers what should be their next procedure whenever a certain disease is detected.The accuracy ofmodel is 94% when trained and tested on leaf dataset.Downloads
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