Deep learning for the internet of things: Potential benefits and use-cases

Deep learning for the internet of things: Potential benefits and use-cases

Blog Article

The massive number of sensors deployed in the Internet of Things (IoT) produce gigantic amounts of data for facilitating a wide range of applications.Deep Learning (DL) would undoubtedly play a role in generating valuable inferences from this massive volume of data and hence will assist in creating smarter IoT.In this abc material regard, exploring the potential of DL for IoT data analytics becomes highly crucial.This paper begins with a concise discussion on the Deep Neural Network (DNN) and its different architectures.The potential benefits that DL will bring to the IoT are also discussed.

Then, a detailed review of DL-driven IoT use-cases is presented.Moreover, this paper formulates a DL-based model for Human Activity Recognition (HAR).It carries out a performance comparison of the proposed model with other machine learning techniques to delineate the superiority redken shades 9gi of the DL model over other techniques.Apart from enlightening the potential of DL in IoT applications, this paper will serve as an impetus to encourage advanced research in the realm of DL-driven IoT applications.