Impact of Deep Learning Techniques in IoT
M. Chandra Vadhana, P. Shanthi Bala, Immanuel Zion Ramdinthara · 2021
Deep Learning (DL) has significantly changed the way process of computing devices human-centric content such as speech, image recognition, and natural language processing. It is very useful for safety-critical applications such as driverless cars, aerospace, defense, medical research, and industrial automation. DL models exceed human-level performance in terms of accuracy. It is a subset of machine learning that performs end-to-end learning and can learn unsupervised data and also provides a very versatile, learnable framework for representing visual and linguistic information. DL plays a major role in IoT related services. It serves as an emerging solution for developing IoT systems enhanced with efficient, reliable, and effective DL models. The amalgamation of DL to the IoT environment makes the complex sensing and recognition tasks easier. It helps to automatically identify patterns and detect anomalies that are generated by IoT devices. This chapter discusses the impact of DL in the IoT environment.