Innovative Model of Internet of Things for Industrial Applications

Abstract

The internet of things is one of the most significant and promising innovations today. In this chapter, the authors proposed the dual probability-based energy estimation model in the wireless sensor network. The dual probability-based function measures the expected value of energy for the transmission of data. This function creates a subgroup of networks based on energy function and carries out the operation of energy management in the context sensor node data processing. This function also integrates cloud-based services with the sensor networks. The benefit of this function is that it increases the throughput of network and quality of service. The proposed model was simulated in MATLAB R-2014a environment, and the results were obtained using different scenarios of network density. Finally, the authors analyzed the performance of our proposed work with respect to the following metrics: data utility, energy consumptions, and data reconstruction error.