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Paper Title: Green Leaf Disease detection and Alertness using IoT
Authors Name: S.Prakash , K.Sabarinathan
Unique Id: IJSDR1912039
Published In: Volume 4 Issue 12, December-2019
Abstract: This paper talked about a framework utilizing raspberry PI to detect and prevent plant disease from spreading. The k means clustering algorithm was used for image analysis. It has numerous focal points for use in vast harvest ranches and in this way distinguishes indications of sickness naturally at whatever point they show up on plant leaves. In pharmaceutical research, the recognition of leaf ailment is essential and a critical theme for research, because it has the advantages of monitoring crops in the field in the form and thus automatically detects symptoms of disease by image processing using an algorithm clustering k - means. The term disease refers to the type of plant damage. This paper gives the best strategy to recognizing plant infections utilizing picture preparing and alarming the ailment brought about by IoT using Adafruit Cloud and showing the malady name on the framework proprietor's screen display. Automatic detection of symptoms of disease is useful for upgrading agricultural products. Completely automatic design and implementation of these technologies will make a significant contribution to the chemical application. The cost of pesticides and other products will be reduced. This will lead to an increase in farm productivity.
Keywords: Image processing, Raspberry Pi, Python, IoT
Cite Article: "Green Leaf Disease detection and Alertness using IoT", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.4, Issue 12, page no.180 - 184, December-2019, Available :http://www.ijsdr.org/papers/IJSDR1912039.pdf
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Publication Details: Published Paper ID: IJSDR1912039
Registration ID:191157
Published In: Volume 4 Issue 12, December-2019
DOI (Digital Object Identifier):
Page No: 180 - 184
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631

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