AI-Driven Blockchain Framework for Secure and Efficient IoT Data Analysis

Abstract

With the advent of the Internet of Things (IoT), which is used to link a vast number of intelligent and self-sufficient devices for a variety of purposes, ubiquitous computing has become a reality. Big data analytics greatly benefits from artificial intelligence, which provides precise data analysis instantly. However, there are certain problems with confidentiality, safety of training data, and centralized architecture when using artificial intelligence to build large data analyses. This article proposes a blockchain-based IoT architecture with AI, showcasing the combination of AI and blockchain for Internet of Things applications. Both qualitative and quantitative measurements are used to assess the suggested architecture's performance. In terms of qualitative evaluation, the explanation of Artificial-oriented BC as well as BC-oriented AI clarifies how blockchain technology and AI work together to address various issues. The performance of the proposed AI-BC IoT Framework structure is evaluated and compared with existing qualitative measuring techniques. According to the experimental analysis, the suggested framework outperforms the current cutting edge methods.