Fuzzy Logic Based Alert on Cochliobolus Miyabeanus to Control the Rice Crop Loss
Dekka Satish1, K. Narasimha Raju2, Bonu Satish3, Koduru Suresh4, Dasari Manendra Sai5

1Dekka Satish *,CSE Department, LENDI, Viziangaram, (AP), India.
2Dr.K.NarasimhaRaju ,CSE Department, LENDI ,Viziangaram, (AP), India.
3Bonu Satish , CSE Department, LENDI, Viziangaram, (AP), India.
4Koduru Suresh , SAP Labs Bangalore,  India.
5Dasari Manendra Sai ,CSE Department, Sai Ganapathi Engineering College, (AP), India.
Manuscript received on January 23, 2020. | Revised Manuscript received on February 05, 2020. | Manuscript published on February 29, 2020. | PP: 3961-3964 | Volume-9 Issue-3, February 2020. | Retrieval Number:  C6511029320/2020©BEIESP | DOI: 10.35940/ijeat.C6511.029320
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Agriculture is a source of living in many areas and acts a backbone for the Indian economy. Agriculture crops are affected by fungus and bacteria to cause diseases in the plant. Brown spot is a serious hazard that takes place on leaves of the rice plant. The presence of fungus ‘Cochliobolus miyabeanus’ is the main factor for brown spot disease. The severity of the disease depends on growth of the fungus. The development of fungus depends on several factors such as temperature, humidity and rainfall. Whenever the disease occurs on a plant, level of the infection plays an importance in crop yield. Most of the farmer follow books or use their experience to detect the disease in rice plants which is a time-consuming process and requires lot of attention to produce more rice yield is a challenging task. Fuzzy logic is identified as powerful tool for disease detection. In this paper, fuzzy logic system is proposed to determine the level of presence of Cochliobolus miyabeanus and alert the farmer to take the primitive steps.
Keywords: Fuzzy Logic, Disease Determination, IoT, Rice Crop.