Towards a Generic NFT-Driven Digital Twin Simulation Platform

A Systematic Literature Review

Abstract

A new approach to asset management and traceability emerges upon the integration of Non-Fungible Tokens (NFTs) and Digital Twin (DT) technology. While NFTs are widely used in digital art and gaming, their potential for securing real-world assets in DT simulations remains under-explored. A generic NFT-driven DT simulation platform could transform asset management by enhancing traceability, optimizing operations, and fostering sustainability within and across industries. In livestock management, DTs can model individual animals in real time, capturing data on health and growth. Linking this data to NFTs ensures ownership and provenance, improving traceability and accountability. Similarly, in manufacturing, DTs can identify inefficiencies, reducing waste and energy use. It is pressing to improve decision-making and operational efficiencies throughout distinct contexts. A Systematic Literature Review (SLR) was conducted following PRISMA. The goal was to build a solid, unbiased foundation for our research, contribute lasting value to the community, and identify where our work can make the most impact. From an initial set of 114 papers, the authors screened and classified the most relevant. This led to a final selection of 8 papers for full-text reading and in-depth analysis. They are presented in detail and compared in order to depict the current state of the art in the field. Results reveal a significant gap concerning the topic, particularly highlighting the absence of simulation environments that align with the previous proposal presented by the authors: a comprehensive NFT-driven and DT simulation platform that transforms NFT-based asset management from static ownership records to dynamic, provides simulation operational tools, enables real-time monitoring, predictive maintenance, and performance optimization for real-world assets.