Automated Secure Computing for Next-Generation Systems

15Machine Learning-Based Solutions for Internet of Things-Based Applications

Varsha Bhatia¹* and Bhavesh Bhatia²

¹Department of Computer Science Engineering, DPG Institute of Technology and Management, Gurugram (Haryana), India

²Department of Computer Science, University of Western Ontario London, London, Ontario, Canada

Abstract

The growth of Internet-connected sensory devices, known as the Internet of Things (IoT), has led to the development of a range of services and applications across various sectors, including infrastructure, retail, transportation, and personal healthcare. Machine learning (ML) allows the IoT to extract meaningful information from an enormous amount of data. ML plays a vital role in coping with the growing demands of future IoT systems for businesses, governments, and individual users. The primary goal of IoT is to sense the physical environment and use intelligent methods for automated decision making as humans will do. This chapter will explore the various applications of IoT where machine learning helps to create intelligent systems as well as the potential future of IoT and machine learning and how these technologies can contribute to the development of communication devices. This chapter will consider the taxonomy of machine learning algorithms that can be applied to IoT and the ways in which machine learning can be used in IoT applications. This chapter will also discuss machine learning algorithms, IoT challenges, and emerging trends to make our ...