Sensitivity Analysis for Safe Grainstorage using Big Data

India is the largest producer of Rice and Wheat which has gained the attention of small and large scale agricultural farmers, but storing these crops without wastage is a long time problem being faced by Food Corporation of India and by small farmers. The main cause of grain damage is due to our country's climatic condition. Prevention of grain damage due to climatic issue is a process. A Systematic approach of identifying suitable dates for storing different grains in a different specific location is been analyzed automatically using Big Data. Also the system will generate an automated alert of any unsafe climatic conditions in the grainstorage. Pattern evaluation and Handling huge volume of data are the two most important issues of this analysis, which has created a wide view for the research and analysis. Since each hourly climatic parameters needs to be analyzed for about 5 years, this analysis shows lots of Big Data advantages such as scalability, reliability, robustness volume management etc. An outline of Insect Infestation Detection Algorithm for safe grain storage report has been generated in this paper. A generic report on safe, unsafe and temporary unsafe dates are being generated for five years of climatic data. Using the report our algorithm generates alert signals if same such sequence of climatic pattern occurs in the upcoming years. Generating such signals will enable the Food Corporation of India to take necessary measure before grain damage.