Open Access Journal

ISSN : 2394-2320 (Online)

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

Open Access Journal

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

ISSN : 2394-2320 (Online)

Cloud Based Plant Leaf Disease Detection System Using an Android Application

Author : P.Vanaja 1 E.Pavithra 2 P.Jotheswaran 3 N.Kumaresan 4 N.Sathiyapriya 5

Date of Publication :22nd March 2018

Abstract: Most of the population in India depends on agriculture and farming. Indian economy directly depends on agricultural production. The proper maintenance of plant growth includes various steps such as to examine the environmental factors and manage water supply for proper cultivation of plants. A traditional way of irrigation is not efficient and unreliable. Around 18% of crop yield is lost worldwide due to pest attack every year. Identification of plant disease is key to preventing the losses in the yield of agriculture product which is difficult to do manually. The project therefore involves a system architecture which allow user to achieve all above activities in real time so that farmers can view their farm details from remote location. It includes- 1.A module placed in a farm that contains various sensors and device for data conversion and transfer such that farm details and environmental factors are monitored and controlled correctly 2.Image processing for disease detection of visually seen symptoms of plant. Using an application the treatment is suggested to reduce the damage levels. The proposed system will thus improve in the productivity and benefit irrigation sector

Reference :

    1. Chandan Kumar, pramitee behera “A Low Cost Smart Irrigation Control System”, International Conference on Electronics and Communication System (icecs 2015) ieee 1146.
    2. Maryam Hazman,”Crop Irrigation Schedule Expert System“, 2015 Thirteenth International Conference on ICT and Knowledge Engineering.
    3. Shitala Prasad • Sateesh K. Peddoju • Debashis Ghosh “Multi-resolution mobile vision system for plant leaf disease Diagnosis”, Springer-Verlag London 2015
    4.  H. Al-Hiary, S. Bani-Ahmad, M. Reyalat, M. Braik and Z. ALRahamneh,” Fast and Accurate Detection and classification of Plant Diseases” International Journal of Computer Applications (0975 – 8887) Volume 17– No.1, March 2011.
    5. Plantix – an easy plant disease diagnostics tool plantix.net

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