Published Paper Details:

Crop management of certain agriculture region is depends on the climatic conditions of that region because climate can make huge impact on crop productivity. Real time weather data can helps to attain the good crop management. Data mining is the process of discovering of new pattern from large data sets, this technology which is employed in inferring useful knowledge that can be put to use from a vast amount of data, various data mining techniques such as classification, prediction, clustering and outlier analysis can be used for the purpose. Real time weather data can helps to attain good crop management. Weather is one of the meteorological data that is rich by important knowledge. In this project we include the hybrid model to improve the agriculture productivity by using data mining techniques. Yield prediction is very popular among farmers these days, which particularly contributes to the proper selection of crops for sowing. This makes the problem of predicting the yielding of crops an interesting challenge. Earlier yield prediction was performed by considering the farmer's experience on a particular field and crop. This work presents a system, which uses IOT techniques in order to predict the analyzed soil datasets. The category, thus predicted will indicate the yielding of crops.