The given paper proposes a solution to the damage caused to the wheat grain via a sensor enabled wireless IOT network. The prototype uses Arduino UNO board and NODEMCU ESP8266 for obtaining and transferring data. The data of various parameters (like humidity, temperature, moisture, CO2 gas and pH) are collected and is then sent to the Google’s Firebase Cloud for data storage and management. From there, it is then sent to the ARIMA Machine Learning Model for prediction of relative humidity for the next five days which helps us to analyse the microbial activity inside the silo. Additionally, an ultrasonic sensor is used to detect the level of wheat grain in silo so that illegal activities like corruption can be prohibited. All the data collected, and results obtained is presented on an online dashboard for easy visualization via graphs and appropriate conclusions. The simulation of a real–time monitoring system along with the proposed shelf life as researched through different papers, journals and publications is also displayed on the online dashboard.

Keywords : Arduino, NodeMCU ESP8266, Firebase, Machine Learning, Data Analytics, ARIMA Model, Grading & Classification, Web Display, Data Visualisation.