Title: A Unified Artificial Intelligence, Blockchain, and Web 3.0 Framework for Secure, Scalable, and Intelligent Data-Driven Systems
Authors: Mohinder Sharma
Volume: 9
Issue: 12
Pages: 136-146
Publication Date: 2025/12/28
Abstract:
The rapid convergence of Artificial Intelligence (AI), Blockchain, Cloud Computing, Internet of Things (IoT), and emerging Web 3.0 technologies has significantly transformed modern data-driven systems. While each of these technologies has been studied independently, their isolated deployment often leads to limitations in scalability, security, interoperability, and intelligent decision-making. This paper presents a unified perspective on integrating AI-driven analytics, blockchain-enabled trust mechanisms, and decentralized Web 3.0 paradigms to build secure, scalable, and intelligent computing systems. Drawing on extensive prior research in cloud-based security, evolutionary optimization, intelligent resource allocation, database systems, and machine learning-based analytics, this study synthesizes existing approaches into a cohesive conceptual framework. The proposed integration addresses critical challenges related to data privacy, system performance, fault tolerance, and sustainability across diverse application domains, including healthcare, smart cities, financial systems, and intelligent web platforms. By consolidating insights from established studies, this paper provides a structured foundation for future research and development of next-generation intelligent and trustworthy digital ecosystems.