MACHINE LEARNING REGRESSION TECHNIQUE FOR COTTON LEAF DISEASE DETECTION AND CONTROLLING USING IOT”
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Date
2019-06-17T09:58:17Z
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Abstract
“Cotton is one of the most important cash crops in India. Every year the production of cotton
is reducing due to the attack of the disease. Plant diseases are generally caused by pest
insect and pathogens and decrease the productivity to large-scale if not controlled within
time. This paper presents a system for detection and controlling of diseases on cotton leaf
along with soil quality monitoring. The work proposes a Support Vector Machine based
regression system for identification and classification of five cotton leaf diseases i.e.
Bacterial Blight, Alternaria, Gray Mildew, Cereospra, and Fusarium wilt. After disease
detection, the name of a disease with its remedies will be provided to the farmers using
android app. The Android App is also used to display the soil parameters values such as
humidity, moisture and temperature along with the water level in a tank. By using Android
app farmers can ON/OFF the relay to control the motor and sprinkler assembly according to
need. All this leaf disease detection system and sensors for soil quality monitoring are
interfaced using Arduino which make it independent and cost-effective system. The overall
classification accuracy of this proposed system is 83.26%.”
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1NH15EC013, 1NH15EC033, 1NH15EC009