AN IOT BASED PLANT LEAF DISEASE DETECTION USING MACHINE LEARNING AND AUTO SPRAYING MECHANISM

Main Article Content

R. Gowtham and Dr. R. Jebakumar

Abstract

Our Indian agricultural farming takes part a major function in area of producing crops or yield of the crops. Most of the people rely on agriculture for their sustainance in the world since the agriculture is the base for the development of economy in a country. This field of land farming provides various employment and job opportunities to major percentage of the people. The healthy or the unhealthy condition of the plants plays an important role in order to earn better profit for the agricultural people. This can be achieved by the continuous observing the condition of the plant health which is needed at various stages of plant growth because to prevent several number of diseases that affects plants while growing. This existence of diseases and pests may affect the act of judging the crop cultivation and has the ability to minimize the yield of crop essentially. Nowadays the system depends on naked eyes monitoring which is considered be a time taking process. Hence, there is a need for the automatic identification of plant diseases that can be adopted to identify the plant disease maximum at the beginning itself. So many number of disease tracking strategies are introduced by the farmers at the continuous intervals of times in order to eradicate the plant diseases. This automated disease identification and prevention system has been introduced by merging the advantages of IOT agricultural land monitoring system and some of the Machine Learning algorithm. We can also use variousIOT sensing devices such as thermal reading sensor, moisture sensor including color sensors depends on the difference withthe leaves case of the plants where the values that depends on temperature sensor, humidity sensor and color parameters thatare used to detect the presence of plant diseases and prevented using the automatic medicine spraying process.


 

Article Details

Section
Articles