Convergent Intelligence: A Unified Ontological Framework for IoT-Blockchain-AI Integration in Next-Generation Cloud Ecosystems

Mon, 29 Jun 2026 00:00:00 +0000

Cloud computing has developed to be a key technology in contemporary digital setups through allowing storage on a scale, shared computing, and on-demand provision of services. Over the last several years, the Internet of Things (IoT), blockchain, and Artificial Intelligence (AI) have emerged as technologies that can provide cloud platforms with many more functions. The IoT devices produce high volumes of data in real-time that can be easily stored and processed in cloud environments. AI can support smart data analytics and auto decision-making, whereas blockchain can support decentralised trust and secure transactions of data. Due to the combination of these technologies, there is a strong digital ecosystem that allows supporting more complex applications of smart cities, healthcare monitoring systems, industrial automation, and intelligent transportation networks. The given paper reviews the development of cloud computing within the framework of IoT, blockchain, and AI integration. It addresses the basics, architectural development and upcoming technological trends that are defining cloud ecosystems. The paper also outlines the open research challenges such as scalability constraints, interoperability problems, privacy issues and ethical issues. A methodological assessment and an analytical outcome prove that the combination of AI-based resource management and blockchain-related security systems can enhance the performance of cloud systems, their reliability, and trustworthiness. The results specify the need to create smart, safe, and scalable cloud structures with the capability to accommodate the upcoming generation of digital services.

Video and Document Watermarking and Copyright Protection Using Blockchain

Dipti Patil, Pranav Kapadne, Mehul Khambale, Sumedh Mayekar — Mon, 01 Jun 2026 00:00:00 +0000

Digitization of content has become a need in today’s digital world, and protecting content is much more challenging. Previously visible watermarks like logos, signs or special characters were used to mark or claim ownership. But various techniques like clipping, rotating and compression can be used to remove such a watermark. To ensure proper security, the watermark was supposed to be big and loud, which actually degrades the quality of the entity. Considering these challenges, invisible watermarking techniques such as LSB were implemented; however, they remained vulnerable to certain attacks. Watermarking modifies the frequency components of a video in a way that is imperceptible to the human eye but can be detected digitally. A certain design will be used to change the frequency and this pattern. This stamp will have all the information about the owner, like their name, contact information, the time the watermark was made, and so on. The SBP-DCT algorithm is used to embed watermarks in video frames, and PDF metadata steganography is implemented for document protection. If someone steals and posts a video without the owner's permission and the video has a label, the owner can check the information and send a copy of the rights to the person who posted it. The watermark is hidden and stored by Vidguard on the Blockchain network. Because of this, changing the information is also very hard on the blockchain.

Advancement of IoT in Blockchain Technology and its Applications (e-ISSN: 2583-7826)

Convergent Intelligence: A Unified Ontological Framework for IoT-Blockchain-AI Integration in Next-Generation Cloud Ecosystems

Video and Document Watermarking and Copyright Protection Using Blockchain