Digital Twin Simulation and Modeling Tools, Deep Learning Object Detection Technology, and Visual Perception and Sensor Fusion Algorithms in the Metaverse Commerce.

• Author: Kovacova, Maria

1. Introduction

   Immersive visualization systems, customer engagement tools, cognitive technologies, and augmented reality and 3D modeling tools configure livestream shopping events in shared virtual environments. The purpose of our systematic review is to examine the recently published literature on digital twin simulation and modeling tools, deep learning object detection technology, and visual perception and sensor fusion algorithms, and integrate the insights it configures on the metaverse commerce. By analyzing the most recent (2022) and significant (Web of Science, Scopus, and ProQuest) sources, our paper has attempted to prove that digital shopping journeys develop on ambient scene detection and operational modeling tools, forecasting user preferences and digital product purchase intentions in immersive virtual spaces. The actuality and novelty of this study are articulated by addressing metaverse customer engagement and virtual retail experiences, that is an emerging topic involving much interest. Our research problem is whether Behavioral predictive analytics on blockchain-based virtual worlds integrates geolocation data, digital twin simulation tools, and remote sensing technologies.

   In this review, prior findings have been cumulated indicating that augmented reality shopping tools articulate immersive and engaging content and multisensory customer experiences across interconnected virtual worlds. The identified gaps advance product customization services, immersive retail experiences, and entertaining metaverse events. Our main objective is to indicate that augmented reality shopping tools enhance immersive retail experiences by use of consumer location data in a blockchain-based virtual world. This systematic review contributes to the literature on immersive and interactive virtual environments by clarifying that immersive virtual retail experiences and consumer digital engagement develop on movement and behavior tracking tools in extended reality environments. This research endeavors to elucidate whether virtual retail experiences require deep learning algorithms and consumer behavior data in 3D immersive environments and virtual shopping malls. Our contribution is by integrating research findings indicating that data mining techniques and augmented reality shopping tools are pivotal in customer engagement behaviors as regards digital assets across a decentralized 3D digital world.

2. Theoretical Overview of the Main Concepts

   Virtual modeling and image recognition technologies, remote sensing systems, and augmented reality shopping tools determine consumer engagement metrics and purchasing decisions in virtual retail stores. Customer data analytics in immersive 3D virtual environments require predictive data mining algorithms, augmented reality shopping tools, and business intelligence operations. Customer traffic analytics and identification technology enable live e-commerce shopping in immersive virtual spaces. The manuscript is organized as following: theoretical overview (section 2), methodology (section 3), virtual asset sales in the decentralized metaverse (section 4), consumption patterns and customer decision journeys in the retail metaverse (section 5), virtual consumer engagement in the metaverse interactive environment (section 6), discussion (section 7), synopsis of the main research outcomes (section 8), conclusions (section 9), limitations, implications, and further directions of research (section 10).

3. Methodology

   Throughout April 2022, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including "metaverse commerce" + "digital twin simulation and modeling tools," "deep learning object detection technology," and "visual perception and sensor fusion algorithms." The search terms were determined as being the most employed words or phrases across the analyzed literature. As research published in 2022 was inspected, only 178 articles satisfied the eligibility criteria. By taking out controversial or ambiguous findings (insufficient/irrelevant data), outcomes unsubstantiated by replication, too general material, or studies with nearly identical titles, we selected 38 mainly empirical sources (Tables 1 and 2). Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AMSTAR, Dedoose, Distiller SR, and SRDR. Extracting and inspecting publicly accessible files (scholarly sources) as evidence, before the research began no institutional ethics approval was required (Figures 1-6).

4. Virtual Asset Sales in the Decentralized Metaverse

   Eye-tracking technologies, deep learning algorithms, and spatial analytics (Gibbert et al., 2022; Han et al., 2022; Liu et al., 2022; Nica et al., 2022) enhance metaverse brand experiences across extended reality environments. Digital shopping journeys develop on ambient scene detection and operational modeling tools, forecasting user preferences and digital product purchase intentions in immersive virtual spaces. Customer data analytics harness automated speech recognition tools across Internet of Things sensing infrastructures, immersive 3D environments, and virtual shopping malls.

   Predictive maintenance tools, real-time sensor data, and spatial computing technology (Chandra, 2022; Egliston and Carter, 2022; Hollensen et al., 2022; Kovacova et al., 2022) assist metaverse customer engagement and virtual retail experiences. Customer location tracking tools, sensing and computing technologies, and behavioral analytics enhance product customization services and augmented shopping experiences in the virtual commerce. Virtual modeling and image recognition technologies, remote sensing systems, and augmented reality shopping tools determine consumer engagement metrics and purchasing decisions in virtual retail stores.

   Decision support tools, machine vision algorithms, and granular journey data impact personalized digital shopping experiences in retail livestreaming (Almarzouqi et al. 2022; Jiang et al., 2022; Kraus et al., 2022; Rydell, 2022), driving consumer behavior as regards virtual asset sales in the decentralized metaverse. Internet of Things-based decision support systems, data computing capabilities, and predictive modeling algorithms improve virtual asset purchasing and live shopping events. Augmented reality shopping tools enhance immersive retail experiences by use of consumer location data in a blockchain-based virtual world. Virtual...