Virtual Reality and Augmented Reality for Industrial and Business Intelligence

Virtual Reality and Augmented Reality for Industrial and Business Intelligence

Karishma Desai, M. Dileep Kumar, Mohamed Omar Khairi, Normala S. Govindarajo, Vinod Sharma
Copyright: © 2024 |Pages: 22
DOI: 10.4018/979-8-3693-1103-5.ch004
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Abstract

The world of innovation and innovative technologies is rapidly proving its scope and benefits across the business sector featuring business intelligence tools. The traditional way of searching data sources, visualizing those data, and arriving at business decisions has transformed with tools of computational intelligence. Here the role of virtual reality (VR) and augmented reality (AR) comes into the picture. The current work looks into the possibilities of VR and AR in business, which support predictive analytics, customer analytics, business analytics, and data visualization aspects through systematic literature review and content analysis. In this paper, a systematic analysis of associations and features of both VR and AR has been done by detailing the outline, organization, management, and devices for business and industry intelligence. The objective of the current work is met with the insights and understanding of VR and AR in relation to business intelligence.
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Literature Review

Internet of Things (IIoT)

IoT or the Internet of Things has turned out to be the life and blood of several organizations which support them with analytical tools, applications, and services in certain domains. IoT enables smart technologies to be developed, tested, and applied in several functional processes. Major functions IoT and AI-integrated applications perform are sensing and actuating, data across the platforms through a unified structure, and enabling innovative applications. IoT makes use of data analytics and information interpretation using state-of-the-art technologies for sensing and cloud computing (Verma et al., 2019). Basically, IoT involves three components a) Hardware, which includes sensors, actuators, and entrenched communication hardware b) Middleware, which includes on-demand storage and computation techniques for data analytics and c) Presentation, which includes visualization and interpretation techniques that can be widely accessed on different platforms and can be planned for diverse application (Sethi & Sarangi, 2016)

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