Internet of Things and data mining: From applications to techniques and systems

Abstract

The Internet of Things (IoT) is the result of the convergence of sensing, computing, and networking technologies, allowing devices of varying sizes and computational capabilities (things) to intercommunicate. This communication can be achieved locally enabling what is known as edge and fog computing, or through the well‐established Internet infrastructure, exploiting the computational resources in the cloud. The IoT paradigm enables a new breed of applications in various areas including health care, energy management and smart cities. This paper starts off with reviewing these applications and their potential benefits. Challenges facing the realization of such applications are then discussed. The sheer amount of data stemmed from devices forming the IoT requires new data mining systems and techniques that are discussed and categorized later in this paper. Finally, the paper is concluded with future research directions. This article is categorized under: Fundamental Concepts of Data and Knowledge > Big Data Mining Application Areas > Health Care Application Areas > Industry Specific Applications

Text Data Security and Privacy in the Internet of Things: Threats, Challenges, and Future Directions

“…It is challenging to manage an enormous amount of user data. e fact cannot be denied that any single error in an algorithm will bring down the entire infrastructure [14].…”

A Novel Framework for Recommending Data Mining Algorithm in Dynamic IoT Environment

“…Data mining as a process of finding meaningful information, from hidden patterns has been studied frequently by the researchers for traditional data in diverse application system [1] [10]. However, there is still a scarcity of data mining research for IoT that considers the heterogeneity and diverse properties of IoT [7] [20].…”

“…The advancement of IoT in the last few years has promoted its adoption in diverse application areas including healthcare, transportation, industry management, and smart cities [1] [2] [3]. The huge volume of data from diverse domains has made data mining as an emerging field of IoT applications.…”

“…One of the major complexities in mining sheer IoT data samples is that the datasets are commonly aggregated from heterogeneous sources at a variable time [1] [8]. In addition, the data sources are also diverse in terms of technologies and domains [10].…”

The role of big data analytics in industrial Internet of Things

“…Big data in IIoT systems arise due to unbounded internal and external activities relevant to customers, business operations, production and machines [14]. BDA processes in IIoT systems manage the collected data using multiple transient and persistent storage systems that provide on-board, in-memory, in-network and large-scale distributed storage facilities across IIoT systems [15,16]. The granularity of data processing facilities for BDA processes in IIoT systems vary from resource-constrained IoT devices to resourceful large-scale distributed cloud computing systems [17].…”