Implementation of Cognitive Radio Model for Agricultural Applications Using Hybrid Algorithms.

In recent days there the farmers who are having enormous expanses of land are facing heavy loss due to sudden changes like monsoon and presence of high amount of CO₂. Therefore, this article presents a Cognitive Radio (CR) model for implementing in agricultural field to predict the parameters like CO₂ effect and strength of received signal. In order to monitor these parameters a new fanged technique with low cost implementation is necessary. Therefore, a low cost Effective CR Agricultural model has been incorporated by integrating the algorithms in two folds. The proposed method has the advantage that the strength of received signal will be higher even if the distance is too long. In addition the effect of CO₂ will also be reduced. The projected technique is compared with other existing techniques where, the implementation cost is much lesser and also the CR model proves to be a precise technique for agricultural applications. [ABSTRACT FROM AUTHOR]