Fruit Disease Prediction Using Machine Learning Over Big Data
M.T Vasumathi1, M. Kamarasan2

1M.T Vasumathi, Department of Computer and Information Science, Annamalai University, Annamalainagar (Tamil Nadu), India.
2M. Kamarasan, Assistant Professor, Department of Computer and Information Science, Annamalai University, Annamalainagar (Tamil Nadu), India.
Manuscript received on 05 May 2019 | Revised Manuscript received on 17 May 2019 | Manuscript Published on 23 May 2019 | PP: 556-559 | Volume-7 Issue-6S5 April 2019 | Retrieval Number: F10980476S519/2019©BEIESP
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Abstract: Big Data Analytics (BDA) offers a stupendous part where there is a want of rebellious performance in managing massive quantity of facts th at handles 4 traits such as Volume Velocity ,Variety and Veracity. Agriculture is one of the fields which generate information constantly protecting all four traits with excellent growth. There are a number of challenges in processing agricultural records which deals with variety of structured and unstructured format. One of the challenges in agriculture industry comprises of fruit disease detection and control. For this purpose farmers had to monitor fruits continuously from harvest till its growth period. But this task is not aneasy one. Hence it requires proposing an efficient clever farming method which will help for better yield and growth with less human efforts. Image processing is a technique which will diagnose and classify external sickness within fruits through various images. For the control of the disease in the initial stage itself several images of the day to day condition of the fruit has to be monitored where a slight change calls for a remedy. As the number of images increases obviously big data come into play. This paper discusses the existing sytem in fruit disease detection and also proposes disease prediction using machine learning over big-data.
Keywords: Big Data Analytics, Machine Learning Fruit Disease Detection.
Scope of the Article: Big Data Application Quality Services