Data-driven Interactive Crowd Management Systems for Metaverse Scenarios

Abstract

Understanding human behavior in urban settings has never been more accessible thanks to the growing accessibility of enormous volumes of data produced by people, cars, and other connected objects. We are entering a new era of innovation and creativity with the Metaverse. It will integrate comprehensive technologies such as 3D imaging, eXtended reality (XR), and advanced sensing into next-generation Internet services. Moreover, recent advances in disruptive technology, such as Artificial Intelligence (AI), and Machine Learning (ML), adding to the increasing decentralization of the Internet due to the possibility to deploy complex analytics across Edge-Cloud, are driving the further development of the Metaverse, as a 3D network of experiences and services. It allows users a sense of synchronous and persistent presence, with continuity of data, which highlights Crowd Management (CM) techniques to manage and control data-driven communications. CM techniques are vital in channelizing the data to help design mobile networks, control emergencies, and plan infrastructures. In this research, we will provide an overview of CM, its properties, and its functional breakdown following the integration of AI into CM. We will introduce the concept of Metaverse Crowd Management (MCM) and examine the various scenarios and associated challenges and opportunities.