The Internet of Things in the Corporate Environment: Cross-Industry Perspectives and Implementation Issues

The Internet of Things in the Corporate Environment: Cross-Industry Perspectives and Implementation Issues

Kiran M. B. (Pandit Deendayal Petroleum University, India) and Martin George Wynn (University of Gloucestershire, UK)
DOI: 10.4018/978-1-7998-7712-7.ch008
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Abstract

The Internet of Things (IoT) is formed by a set of physical objects with embedded sensors, connected using a network so that they can collect and exchange data. Though the concept looks simple, its deployment in industry has enormous potential to bring major business benefits and radical change. This chapter examines IoT technology and how it is being used in the corporate environment. Based on a review of existing literature and case examples, the various definitions and elements of IoT are discussed, followed by an assessment of how IoT is being used and what benefits are being delivered. Some key emergent themes are then examined – security aspects, the significance of 5G networks, and the need for an IoT strategy and project implementation guidelines. The chapter concludes by outlining possible areas for future research and suggests a step-change in the mega-infrastructure connecting IoT devices is imminent.
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Introduction

The term “Internet of Things” (IoT) was reputedly first introduced by Kevin Ashton of the Massachusetts Institute of Technology in a presentation to Procter & Gamble in 1999. However, the concept of connected devices even then was not new, but rather built on the principles of local and wide area networks dating back to the 1970s, overlain with wireless technologies and the Internet. In a manufacturing context, it also built upon the supervisory control and data acquisition (SCADA) systems that became commonplace in the 1980s, as part of the shop floor data capture infrastructure that fed the Manufacturing Execution Systems (MES) and Enterprise Resource Planning (ERP) applications at the corporate level. Now, however, applications are much wider in scope. As Vodafone Business (2019) note “by IoT, we mean connecting sensors in things like cars, buildings and machines, enabling them to communicate about their status and environment and to be controlled remotely. It’s making possible everything from asset tracking and condition monitoring to preventative maintenance and autonomous cars. The uses of this technology are broad and constantly growing” (p.1). According to Gartner (cited in Zscaler and ThreatLabZ, 2019, p.2), in excess of 20 billion IoT devices were estimated to be in use by 2020, with more than 65 percent of all companies using IoT products of some sort. According to PaloAlto Networks (2021), in excess of 30% of all network-connected endpoints are IoT devices in a typical company today.

Following this introduction, this chapter first discusses a number of different perspectives regarding the IoT concept, and sets out the main components of IoT infrastructure. Then, through an assessment of a number of secondary sources, it identifies the main business areas where IoT technology is being deployed, and assesses the potential benefits of IoT deployment. This is followed by a discussion of a number of emergent themes. Finally, the conclusion summarises key issues, and suggests some possible areas for future research in this field of study.

Key Terms in this Chapter

Machine Learning: A technology used to make a computer-controlled device, to observe, understand and learn a given situation and make future predictions like a human brain.

Platform as a Service (PaaS): A cloud environment in which users can both develop and deploy systems and applications.

Fog Computing: The architecture of nodes that lie between the IoT devices and the cloud-based storage environment. These nodes can format and reduce data volumes before passing that data onto the cloud for onward processing and storage.

Internet of Things (IoT): The IoT is formed by a set of physical objects with embedded sensors, connected using a network so that they can collect and exchange data.

Application Programming Interface (API): A software product that allows two applications to talk to each other. Traditionally used to link on premise business applications, now of new significance in the cloud environment.

Edge Computing: Computation and data processing close to the point of capture of that data by IoT devices.

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