ABSTRACT
The Internet of Things (IoT) is becoming a common term and ample numbers of smart products are now available which use sensors, microcontrollers, or other kinds of intelligence to communicate or interchange the data or information among devices without or with least human intervention. IoT devices can be seen in almost every area, such as education, medical science, manufacturing, etc. However, these IoT devices generate a lot of data known as big data for analysis. Sometimes hackers misuse this vulnerable information and cause harm to the community. Therefore, secure and accurate solutions are necessary. Thus, Deep Learning as a branch of machine learning is helping society with its powerful features. Deep Learning is obtaining efficient results in almost all IoT application areas such as object analysis, image classification, forecasting, etc., with its intelligent ability to understand structured, unstructured, and semi-structured data. In this chapter, a detailed analysis is provided about the type of Deep Learning network architecture, such as Convolutional Neural Network (CNN), Recurrent Neural Network (RNN), Long Short-Term Memory (LSTM), and Edge computing, etc., which are used in different IoT application areas for more effective and precise results.
