Agricultural Sensor Captured Data Analysis for Optimum Storage

As we know that data captured from various agricultural sensors is in the infinite sequence. This data can also be called as Agricultural Unstructured data. It is necessary to find out the useful information from the big volume of unstructured data for scientific analysis, predictions to improve agricultural productivity. In the preceding paper we are providing a framework which can solve the problem of randomly stored big data volume. This paper basically deals with classification of agricultural sensor generated data by distinguishing the classes according to sources as sensors such as soil moisture sensor, soil temperature sensor, heat sensor and so on. Each sensor produces variety of data which can be classified by using the proposed Pro-Brokering algorithm.