Semantic approach for Data Analysis and Analytics in IoT with prospect of Agriculture 4 0

Abstract

newline Modern technology is one of the key components of any comprehensive innovation. Existing systems are limited in terms of productivity, security, and effectiveness. We can create a more intelligent, efficient, and productive agricultural system by integrating IoT into traditional agricultural practices. newlineWith the help of this research work, a novel approach for data analysis and data analytics for IoT system is introduced by developing deep CNN model. The Proposed Cat Swarm algorithm optimized Deep Convolutional Neural Network (CSA-optimized DCNN) is the research of soil moisture prediction, and irrigation control to tackle the challenges of the conventional researches, and to achieve better prediction accuracy. This research work introduced a road map for smart agriculture system for soil testing and crop prediction. newlineFuture work aims to refine data analysis and data analytics with advanced optimizations and develop the optimized smart system ensuring the energy consummation model. The DCNN optimized with the CSA adds an advantage as the algorithm optimizes the hyper-parameters of the DCNN to enhance efficiency of the research model. The obtained data from the sensor nodes are stored in the server and fetched when need to be processed and fed as the input to the DCNN, which is optimized with CSA optimization to enhance the performance. This entire work based on the data analysis and data analytic techniques to enhance the soil mineral content prediction and crop recommendation. newline