Big Data Analytics for Internet of Things

3Machine Learning Techniques for IoT Data Analytics

Nailah Afshan¹ and Ranjeet Kumar Rout²

¹ Department of Computer Science and Engineering, Islamic University of Science and Technology, Pulwama, India

² Department of Computer Science and Engineering, National Institute of Technology, Srinagar, India

3.1 Introduction

“The most profound technologies are those that disappear. They weave themselves into the fabric of everyday life until they are indistinguishable from it.” This is the central statement made by Mark Weiser in his seminal paper in Scientific American in 1991 [1]. The statement fits quite well as far as the technology of IoT is concerned. IoT is among the most prevalent and rising technologies in the current era. The success and emergence of IoT have been possible due to tremendous technological advancements in recent years and rapid convergence of digital electronics, wireless communication, Internet protocols, computing systems, and micro‐electro‐mechanical systems (MEMS) [2–4]. It actually portrays the next progression phase of the Internet, with great advancement in its data processing abilities. Dynamic Internet revolutionized communication that in turn resulted in the birth of IoT. The future of IoT and its relation with the Internet has been beautifully stated by a senior researcher at HP Labs, Peter Hartwell as, “With a trillion sensors embedded in the environment – all connected by computing systems, software, and services – it will be possible to hear the ...