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

Monthly Journal for Science , Computer Science and Engineering

Volume4,November 2017,

Topic : Review on Crop Pests Forewarning With Weather Factors Using Machine Learning

Authors:Ms. Babita Sonare || Saurabh Zarkar, Priyanka Talele, Rohit Deshmukh, Utkarsha Shelake

Abstract:Overall climate change is nothing but diversity in the weather patterns of various regions of the world. The term "weather" refers to the short term changes in temperature, rainfall, and humidity of a region. With the up-gradation in data mining and its applications, data mining is extensively used to make smarter decisions in farming. Various meteorological data like- temperature, humidity, rainfall plays the vital roles in the growth of pests responsible for damaging the agricultural production. Effective forecasting of such pests on the basis of climate data can help the farmers to take prior actions to restrain the damages. This can also justify the use of pesticides, which are one of the sources behind soil pollution. In this study we are going to implement application, which gives the notification to farmers, if there is change in environment, so based on that changes which type of pest’s along with their population affects the crop, such type of notification will be generated on web service portal. Weather-based forecasting system can be treated as a part of the Agricultural Decision Support System, which is knowledge-based system. Web service portal is used to collect the data regarding physical parameters, using a sophisticated web service platform, using longitude and latitude concept..

Keywords: Agricultural Decision Support System (ADSS), Agriculture Prediction, Meteorological Data, Weather Monitoring, Web services.

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DOI: 01.1617/vol4/iss11/pid21643


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Dr. Allon Guez
Professor, Drexel University,
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ISSN(Online):2394-2320

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