In agriculture, pests are the major reason that causes low yield and greatly affects the crop. Cotton plays a major role in the textile industry and due to a lack of pest identification more amount of cotton crops is getting damaged. To solve this problem, Convolutional neural networks along with MobilenetV2 is used to detect the pests in the cotton plant by passing an RGB image to the proposed model and the model detects whether the pest is present in the crop or not with the accuracy rate of 96.31%. If the pest is present, then the farmer has to be ready with pesticide and if the pest is not present, the farmer has to give fertilizer based on soil properties. This can be done by using the Random Forest (RF) algorithm with an accuracy of 97.95%. This can help farmers to produce more yield.