Real Time Digital Image Processing of Agricultural Data

In my earlier articles, I had discussed about about application of Big data for gathering Insights on green revolution and witnessed about a research work on supply chain management using big data analytics on agriculture. Incrementally, got an opportunity to implement data science methodology (a game theory approach) to make the results of SCM as an incentive compatible one. However, in this article I am trying to discuss about a large scale digital image processing obtained using time-series photographs of agricultural fields and sensor data for parameters, that should be done parallely with the help of Big Data Analytics such that the result of this work can facilitate SCM process exponentially. We are focusing on using deep learning and machine learning techniques for identifying patterns for making predictins and decision making on large-scale stored / near real-time data sets. By this, we can identify the crop type, quality, maturity period for harvesting, early identification of bugs and diseases, soil quality attributes, early identification of need for soil nourishments etc., on a larger farms.