Applications of Deep Learning Models in Diverse Streams of IoT

Internet of Things (IoT) has gained enormous popularity in recent years. From obvious home automations to sophisticated medical procedures, IoT has gained considerable attention and applicability. But there are certain challenges also pertaining to apt use of IoT applications. The challenges range from generation of huge amount of data by sensors to security and privacy threats to IoT models. Malwares, energy consumption, and decision-making in healthcare or agriculture are few of the challenging aspects of IoT applications. The need of the time is to make IoT intelligent. Deep learning undoubtedly paves the way to put intelligence into IoT devices. Application of deep learning techniques helps IoT frameworks to handle difficult challenges more easily. For instance, deep learning models are very suitable to handle huge amount of data to find valuable inferences. Malware detection or optimisation of energy consumption in IoT applications finds right bid for deep learning models. In this chapter, we have gathered and compiled the applications of deep learning models in various fields of IoT. This chapter presents an in-depth study of these techniques in order to explore new horizons of applications of deep learning models in different areas of IoT.